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Clinical aspects of infectious diseases.

1. Introduction

2. overview of published articles, 3. conclusions, list of contributions.

• Sękowska, Alicja, Czyżewski, Krzysztof, Jaremek, Kamila, Zalas-Więcek, Patrycja, Zając-Spychała, Olga, Wachowiak, Jacek, Szmydki-Baran, Anna, Hutnik, Łukasz, Gietka, Agnieszka, Gryniewicz-Kwiatkowska, Olga, and et al. 2024. Infections with Klebsiella pneumoniae in Children Undergoing Anticancer Therapy or Hematopoietic Cell Transplantation: A Multicenter Nationwide Study. Journal of Clinical Medicine 13: 4078. https://doi.org/10.3390/jcm13144078 .
• Kokkoris, Stelios, Angelopoulos, Epameinondas, Gkoufa, Aikaterini, Christodouli, Foteini, Ntaidou, Theodora, Theodorou, Evangelia, Dimopoulou, Georgia, Vasileiadis, Ioannis, Kremmydas, Panagiotis, and Christina Routsi. 2024. The Diagnostic Accuracy of Procalcitonin and Its Combination with Other Biomarkers for Candidemia in Critically Ill Patients. Journal of Clinical Medicine 13: 3557. https://doi.org/10.3390/jcm13123557 .
• Pleșca, Vlad Ștefan, Miron, Victor Daniel, Marinescu, Adrian Gabriel, Drăgănescu, Anca Cristina, Pleșca, Anca Doina, Săndulescu, Oana, Voiosu, Cătălina, Hainăroșie, Răzvan, and Anca Streinu-Cercel. 2024. Hospitalizations for Acute Otitis and Sinusitis in Patients Living with HIV: A Retrospective Analysis of a Tertiary Center in Romania. Journal of Clinical Medicine 13: 3346. https://doi.org/10.3390/jcm13113346 .
• Hieber, Hannah, Pricoco, Rafael, Gerrer, Katrin, Heindrich, Cornelia, Wiehler, Katharina, Mihatsch, Lorenz L., Haegele, Matthias, Schindler, Daniela, Donath, Quirin, Christa, Catharina, and et al. 2024. The German Multicenter Registry for ME/CFS (MECFS-R). Journal of Clinical Medicine 13: 3168. https://doi.org/10.3390/jcm13113168 .
• Hertz, Mathias Amdi, Johansen, Isik Somuncu, Rosenvinge, Flemming S., Brasen, Claus Lohman, Andersen, Eline Sandvig, Heltborg, Anne, Skovsted, Thor Aage, Petersen, Eva Rabing Brix, Cartuliares, Mariana Bichuette, Nielsen, Stig Lønberg, and et al. 2024. The Diagnostic Accuracy of Procalcitonin, Soluble Urokinase-Type Plasminogen Activator Receptors, and C-Reactive Protein in Diagnosing Urinary Tract Infections in the Emergency Department—A Diagnostic Accuracy Study. Journal of Clinical Medicine 13: 1776. https://doi.org/10.3390/jcm13061776 .
• Corona-Nakamura, Ana Luisa, Arias-Merino, Martha Judith, Miranda-Novales, María Guadalupe, Nava-Jiménez, David, Delgado-Vázquez, Juan Antonio, Bustos-Mora, Rafael, Cisneros-Aréchiga, Aldo Guadalupe, Aguayo-Villaseñor, José Francisco, Hernández-Preciado, Martha Rocio, and Mario Alberto Mireles-Ramírez. 2023. Intraspinal and Intracranial Neurotuberculosis, Clinical and Imaging Characteristics and Outcomes in Hospitalized Patients: A Cohort Study (2000–2022). Journal of Clinical Medicine 12: 4533. https://doi.org/10.3390/jcm12134533 .
• Candel, Francisco Javier, Salavert, Miguel, Basaras, Miren, Borges, Marcio, Cantón, Rafael, Cercenado, Emilia, Cilloniz, Catian, Estella, Ángel, García-Lechuz, Juan M., Montero, José Garnacho, and et al. 2023. Ten Issues for Updating in Community-Acquired Pneumonia: An Expert Review. Journal of Clinical Medicine 12: 6864. https://doi.org/10.3390/jcm12216864 .
• Candel, Francisco Javier, Salavert, Miguel, Estella, Angel, Ferrer, Miquel, Ferrer, Ricard, Gamazo, Julio Javier, García-Vidal, Carolina, del Castillo, Juan González, González-Ramallo, Víctor José, Gordo, Federico, and et al. 2023. Ten Issues to Update in Nosocomial or Hospital-Acquired Pneumonia: An Expert Review. Journal of Clinical Medicine 12: 6526. https://doi.org/10.3390/jcm12206526 .
• Satora, Małgorzata, Grunwald, Arkadiusz, Zaremba, Bartłomiej, Frankowska, Karolina, Żak, Klaudia, Tarkowski, Rafał, and Krzysztof Kułak. 2023. Treatment of Vulvovaginal Candidiasis—An Overview of Guidelines and the Latest Treatment Methods. Journal of Clinical Medicine 12: 5376. https://doi.org/10.3390/jcm12165376 .
• Maryam, Sajida, Krukiewicz, Katarzyna, Haq, Ihtisham Ul, Khan, Awal Ayaz, Yahya, Galal, and Simona Cavalu. 2023. Interleukins (Cytokines) as Biomarkers in Colorectal Cancer: Progression, Detection, and Monitoring. Journal of Clinical Medicine 12: 3127. https://doi.org/10.3390/jcm12093127 .
• Petakh, Pavlo, Oksenych, Valentyn, and Oleksandr Kamyshnyi. 2024. Corticosteroid Treatment for Leptospirosis: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine 13: 4310. https://doi.org/10.3390/jcm13154310 .
• Nahra, Raquel, Darvish, Shahrzad, Gandhi, Snehal, Gould, Suzanne, Floyd, Diane, Devine, Kathy, Fraimow, Henry, Dibato, John E., and Jean-Sebastien Rachoin. 2024. Impact of Povidone Application to Nares in Addition to Chlorhexidine Bath in Critically Ill Patients on Nosocomial Bacteremia and Central Line Blood Stream Infection. Journal of Clinical Medicine 13: 2647. https://doi.org/10.3390/jcm13092647 .
• Moppert, Justyna, Łężyk-Ciemniak, Eliza, and Małgorzata Pawłowska. 2024. Encephalitis in the Course of HHV-7 Infection in an Infant. Journal of Clinical Medicine 13: 418. https://doi.org/10.3390/jcm13020418 .
• Popa, Gabriela Loredana, Popa, Alexandru Cosmin, Mastalier, Bogdan, Crețu, Carmen Michaela, and Mircea Ioan Popa. 2023. Complicated Clinical Course of a Patient with Multivisceral Cystic Echinococcosis Requiring Extensive Surgical and Medical Treatment. Journal of Clinical Medicine 12: 5596. https://doi.org/10.3390/jcm12175596 .

Conflicts of Interest

• Worldometer: COVID-19 Coronavirus Pandemic. Available online: https://www.worldometers.info/coronavirus/ (accessed on 1 August 2024).
• World Health Organization. Global Hepatitis Report 2024: Action for Access in Low and Middle Income Countries. Published on 9 April 2024. Available online: https://www.who.int/publications/i/item/9789240091672 (accessed on 1 August 2024).
• GBD HIV Collaborators. Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: The Global Burden of Disease Study 2019. Lancet HIV 2021 , 8 , E633–E651. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• GBD 2021 Tuberculosis Collaborators. Global, regional, and national age specific progress towards the 2020 milestones of the WHO End TB Strategy: A systematic analysis for the Global Burden of Disease Study 2021. Lancet Infect. Dis. 2024 , 24 , 698–725. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Center for Disease Control. World Malaria Day 2024. Available online: https://www.cdc.gov/malaria/features/world-malaria-day/index.html (accessed on 1 August 2024).

Share and Cite

Waheed, Y. Clinical Aspects of Infectious Diseases. J. Clin. Med. 2024 , 13 , 4853. https://doi.org/10.3390/jcm13164853

Waheed Y. Clinical Aspects of Infectious Diseases. Journal of Clinical Medicine . 2024; 13(16):4853. https://doi.org/10.3390/jcm13164853

Waheed, Yasir. 2024. "Clinical Aspects of Infectious Diseases" Journal of Clinical Medicine 13, no. 16: 4853. https://doi.org/10.3390/jcm13164853

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Favorable Antiviral Effect of Metformin on SARS-CoV-2 Viral Load in a Randomized, Placebo-Controlled Clinical Trial of COVID-19

D. R. B. and J. D. H. contributed equally to this work.

Potential conflicts of interest. J. B. B. reports contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support by NIH, PCORI, Bayer, Boehringer-Ingelheim, Carmot, Corcept, Dexcom, Eli Lilly, Insulet, MannKind, Novo Nordisk, and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, Aqua Medical Inc, AstraZeneca, Boehringer-Ingelheim, CeQur, Corcept Therapeutics, Eli Lilly, embecta, GentiBio, Glyscend, Insulet, Mellitus Health, Metsera, Moderna, Novo Nordisk, Pendulum Therapeutics, Praetego, Stability Health, Tandem, Terns Inc, and Vertex.; personal compensation for expert testimony from Medtronic MiniMed; participation on advisory boards for Altimmune, AstraZeneca, and Insulet; a leadership role for the Association of Clinical and Translational Science; and stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, Praetego, and Stability Health. M. A. P. receives consulting fees from Opticyte and Cytovale. A. B. K. has served as an external consultant for Roche Diagnostics; received speaker honoraria from Siemens Healthcare Diagnostics, the American Kidney Fund, the National Kidney Foundation, the American Society of Nephrology, and Yale University Department of Laboratory Medicine; research support unrelated to this work from Siemens Healthcare Diagnostics, Kyowa Kirin Pharmaceutical Development, the Juvenile Diabetes Research Foundation, and the NIH; support for travel from College of American Pathologists Point-Of-Care Testing Committee; participation on an advisory board for the Minnesota Newborn Screening Advisory Committee; grants from NIH and JDRF for multiple unrelated clinical research projects and Kyowa Kirin Pharmaceutical Development and Siemens Healthcare Diagnostics for unrelated clinical research studies; and leadership roles for the American Board of Clinical Chemistry, Association for Diagnostics and Laboratory Medicine (ADLM) Evidence-Based Laboratory Medicine Subcommittee, and ADLM Academy Test Utilization Committee. M. R. R. reports consulting fees from 20/20 Gene Systems for coronavirus disease 2019 testing. D. B. R. reports grants from the NIH NCATS ACTIV-6 Steering Committee Chair. K. C. reports stock or stock options for United Health Group. C. T. B. reports consulting fees from NCATS/DCRI and the ACTIV-6 Executive Committee and support for travel from Academic Medical Education. All other authors report no potential conflicts.

All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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• Figures & tables

Carolyn T Bramante, Kenneth B Beckman, Tanvi Mehta, Amy B Karger, David J Odde, Christopher J Tignanelli, John B Buse, Darrell M Johnson, Ray H B Watson, Jerry J Daniel, David M Liebovitz, Jacinda M Nicklas, Ken Cohen, Michael A Puskarich, Hrishikesh K Belani, Lianne K Siegel, Nichole R Klatt, Blake Anderson, Katrina M Hartman, Via Rao, Aubrey A Hagen, Barkha Patel, Sarah L Fenno, Nandini Avula, Neha V Reddy, Spencer M Erickson, Regina D Fricton, Samuel Lee, Gwendolyn Griffiths, Matthew F Pullen, Jennifer L Thompson, Nancy E Sherwood, Thomas A Murray, Michael R Rose, David R Boulware, Jared D Huling, COVID-OUT Study Team , Favorable Antiviral Effect of Metformin on SARS-CoV-2 Viral Load in a Randomized, Placebo-Controlled Clinical Trial of COVID-19, Clinical Infectious Diseases , Volume 79, Issue 2, 15 August 2024, Pages 354–363, https://doi.org/10.1093/cid/ciae159

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Metformin has antiviral activity against RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanism appears to be suppression of protein translation via targeting the host mechanistic target of rapamycin pathway. In the COVID-OUT randomized trial for outpatient coronavirus disease 2019 (COVID-19), metformin reduced the odds of hospitalizations/death through 28 days by 58%, of emergency department visits/hospitalizations/death through 14 days by 42%, and of long COVID through 10 months by 42%.

COVID-OUT was a 2 × 3 randomized, placebo-controlled, double-blind trial that assessed metformin, fluvoxamine, and ivermectin; 999 participants self-collected anterior nasal swabs on day 1 (n = 945), day 5 (n = 871), and day 10 (n = 775). Viral load was quantified using reverse-transcription quantitative polymerase chain reaction.

The mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (−0.56 log 10 copies/mL; 95% confidence interval [CI], −1.05 to −.06; P = .027). Those who received metformin were less likely to have a detectable viral load than placebo at day 5 or day 10 (odds ratio [OR], 0.72; 95% CI, .55 to .94). Viral rebound, defined as a higher viral load at day 10 than day 5, was less frequent with metformin (3.28%) than placebo (5.95%; OR, 0.68; 95% CI, .36 to 1.29). The metformin effect was consistent across subgroups and increased over time. Neither ivermectin nor fluvoxamine showed effect over placebo.

In this randomized, placebo-controlled trial of outpatient treatment of SARS-CoV-2, metformin significantly reduced SARS-CoV-2 viral load, which may explain the clinical benefits in this trial. Metformin is pleiotropic with other actions that are relevant to COVID-19 pathophysiology.

NCT04510194.

(See the Invited Commentary by Siedner and Sax on pages 292–4.)

COVID-OUT was a multisite, phase 3, quadruple-blinded, placebo-controlled, randomized clinical trial to test whether outpatient treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevented severe coronavirus disease 2019 (COVID-19) [ 1 ].

The selection of metformin was motivated by in silico modeling, in vitro data, and human lung tissue data that showed that metformin decreased SARS-CoV-2 viral growth and improved cell viability [ 2–4 ]. The in silico modeling identified protein translation as a key process in SARS-CoV-2 replication, similar to protein mapping of SARS-CoV-2 [ 3 ]. Metformin inhibits the mechanistic target of rapamycin (mTOR) [ 5 ], which controls protein translation [ 6 , 7 ]. Metformin has shown in vitro antiviral actions against the Zika virus and against hepatitis C via mTOR inhibition [ 8–11 ].

Severe COVID-19 was defined using a binary, 4-part composite outcome (1 reading <94% SpO 2 on a home oximeter/emergency department visit/hospitalization/death) through 14 days and was not significant. After removing the 1 oxygen reading <94% component per the prespecified statistical analysis plan (SAP), metformin reduced the odds of emergency department visits/hospitalizations/death by day 14 by 42%, of hospitalization/death by day 28 by 58%, and of long COVID diagnoses by day 300 by 42% [ 1 , 12 ].

Here, we present the viral load quantification from samples obtained during the COVID-OUT trial. The trial used a 2 × 3 factorial design of parallel treatments to efficiently assess 3 medications: immediate-release metformin, ivermectin, and fluvoxamine at doses not previously studied in COVID-19 trials.

Study Design, Sample, and Oversight

COVID-OUT was an investigator-initiated, multisite, phase 3, quadruple-blinded, placebo-controlled randomized clinical trial ( Supplementary Tables 1 and 2 ) [ 1 ] that enrolled from 30 December 2020 to 28 January 2022. COVID-OUT was decentralized to prevent SARS-CoV-2 spread. The participants, care providers, investigators, and outcomes assessors remained blinded to treatment allocation.

Institutional review boards (IRBs) at each site and the Advarra Central IRB approved the protocol. An independent data and safety monitoring board (DSMB) monitored safety and efficacy. All analyses and covariates were prespecified in the SAP, which was submitted to the DSMB before enrollment ended and submitted in February 2022 with the primary outcome manuscript and then published [ 1 ]. An independent monitor oversaw study conduct per the Declaration of Helsinki, Good Clinical Practice Guidelines, and local requirements.

COVID-OUT excluded low-risk individuals, limiting enrollment to standard-risk adults aged 30 to 85 years with a body mass index (BMI) in the overweight or obesity categories, documented + SARS-CoV-2 within 3 days, and no prior confirmed SARS-CoV-2 infection. Pregnant women were randomized to metformin or placebo and not to ivermectin or fluvoxamine. Exclusion criteria included hospitalized, symptom onset >7 days prior, and unstable heart, liver, or kidney failure [ 1 ].

Metformin dosing was as follows: 500 mg on day 1, 500 mg twice daily on days 2–5, and 500 mg in the morning and 1000 mg in the evening on days 6–14. Fluvoxamine dosing was as follows: 50 mg on day 1 and 50 mg twice daily on days 2–14. Ivermectin dosing was as follows: a median of 430  µg/kg/day (range, 390 to 470  µg/kg/day) for 3 days.

Clinical and Virologic End Points

The primary end point was severe COVID-19 by day 14, defined using a binary, 4-part composite end point: 1 reading <94% SpO 2 on home oximeter/emergency department visit/hospitalization/death due to COVID-19. Secondary end points included hospitalization or death by day 28 and long COVID over the 10-month follow-up. The virologic secondary end point was overall viral load in follow-up, adjusted for baseline viral load as prespecified in the SAP.

Self-collection of anterior nares samples was an optional component of the randomized trial. Supply chain shortages caused administrative censoring of 78 participants who did not receive materials for collecting day 1, day 5, or day 10 samples; 3 did not receive materials for day 5 or day 10 samples ( Supplementary Figure 1, Supplementary Tables 3–6 ).

Laboratory Procedures

Participants received written instructions with pictures on self-collecting from the anterior mid-turbinate, which has excellent concordance with professionally collected nasal swabs [ 13 ]. Viral load was measured via reverse-transcription quantitative polymerase chain reaction using N1 and N2 targets in the SARS-CoV-2 nucleocapsid protein, with relative cycle threshold values converted to absolute copy number via calibration to droplet digital polymerase chain reaction. Detailed methods can be found in Supplementary Table 7 .

While participant self-collection may vary between participants, self-collection of samples is done by the same individual at baseline and follow-up. Thus, participant self-collection may have less variability between baseline and follow-up than when study or clinical staff obtain samples.

Statistical Analyses

We evaluated randomized study drug assignment on the impact of log 10 -transformed viral load on day 5 and day 10 with a linear Tobit regression model where the effect of study drugs was allowed to differ on day 5 and day 10. This was decided a priori as a rigorous analytic approach to account for left censoring due to the viral load limit of quantification. Repeated measures were accounted for using clustered standard errors within participants. Analyses of viral loads estimated the adjusted mean reduction averaged over time and the adjusted mean reduction at day 5 and day 10. We evaluated impact over time on the probability of viral load being undetectable using generalized estimating equations with a logistic link; estimates are reported as adjusted odds ratios (ORs) and 95% confidence intervals (CIs).

The COVID-OUT trial was a 2 × 3 factorial design of parallel distinct treatments ( Supplementary Table 2 ). All analyses were adjusted for baseline viral load, vaccination status, time since last vaccination for those vaccinated before enrollment, receipt of other study medications within factorial trial, laboratory that processed the nasal swabs, and exact time and date of specimen collection. Additional details and the results of the analyses with dropping of adjustment variables are presented in Supplementary Tables 8 and 9 .

To handle missing values, we used multiple imputation with chained equations to multiply impute missing viral load outcomes and vaccination status. Missing covariate information was jointly imputed along with missing outcomes using random forests for the univariate imputation models. Along with outcome and vaccination status information, imputation models were informed by sex, BMI, symptom duration, race/ethnicity, baseline comorbidities, clinical outcomes, and enrollment time categorized by the dominant pandemic variant. Complete case analysis without imputation of missing data is presented in Supplementary Figures 2–4 . Heterogeneity of effect was assessed across a priori subgroups of baseline characteristics. Starting metformin in <4 days of symptom onset is a subgroup that aligns with antiviral trials and reflects real-world use, as metformin is widely available.

Among 1323 randomized participants in the COVID-OUT trial, 999 (76%) chose to participate in the optional substudy and provided at least 1 nasal swab sample ( Table 1 , Supplementary Figure 1 ). The demographics of the participants who submitted swabs were similar to those who did not submit nasal swabs ( Supplementary Tables 3–5 ). Day 1 samples were provided by 945 participants, 871 provided day 5 samples, and 775 provided day 10 samples ( Supplementary Table 6 ). The overall viral load was a median of 4.88 log 10 copies/mL (interquartile range [IQR], 2.99 to 6.18) on day 1, 1.90 (IQR, 0 to 3.93) on day 5, and 0 (IQR, 0 to 1.90 with 0 representing the limit of quantification) on day 10.

Baseline Characteristics of Participants Who Submitted Any Nasal Swab

Values are percent (n) or median (interquartile range) unless specified. Cardiovascular disease defined as hypertension, hyperlipidemia, coronary artery disease, past myocardial infarction, congestive heart failure, pacemaker, arrhythmias, or pulmonary hypertension.

Abbreviation: BMI, body mass index.

a Unknown n = 22.

The overall mean SARS-CoV-2 viral load reduction with metformin was −0.56 log 10 copies/mL (95% CI, −1.05 to −0.06) greater than placebo across all follow-up ( P = .027). The antiviral effect of metformin compared with placebo was −0.47 log 10 copies/mL (95% CI, −0.93 to −0.014) on day 5 and −0.64 log 10 copies/mL (95% CI, −1.42 to 0.13) on day 10 ( Figure 1 ). Neither ivermectin nor fluvoxamine had virologic effect ( Figure 2 , Supplementary Figure 2 , Supplementary Tables 8–10 ).

Effect of metformin versus placebo on viral load over time, detectable viral load, and rebound viral load. A , Adjusted mean change in log10 copies per milliliter (viral load) from baseline (day 1) to day 5 and day 10 for metformin (lower line) and placebo (upper line). Mean change estimates are based on the adjusted, multiply imputed Tobit analysis (the primary analytic approach) that corresponds to the overall metformin analysis presented in Figure 2 . B , Adjusted percent of viral load samples that were detectable at day 1, day 5, and day 10. The percent viral load detected estimates were based on the adjusted, multiply imputed logistic generalized estimating equations (GEE) analysis corresponding to the overall metformin analysis depicted in Figure 3 . Odds ratios correspond to adjusted effects on the odds ratio scale. C , Bar chart depicting the percent of participants whose day 10 viral load was greater than the day 5 viral load and the odds ratio for having viral load rebound using the multiply imputed logistic GEE. Abbreviation: CI, confidence interval.

Overall results for metformin, ivermectin, and fluvoxamine on viral load; heterogeneity of treatment effect of metformin versus placebo. This is a forest plot that depicts the effect of active medication compared with control on log10 copies per milliliter (viral load), overall, and at day 5 and day 10. Viral Effect* denotes the adjusted mean change in viral load in log10 copies per milliliter with 95% confidence intervals for the adjusted mean change. Analyses were conducted using the primary analytic approach, a multiply imputed Tobit model. The vertical dashed line indicates the value for a null effect. The top 3 rows show ivermectin, the next 3 rows show fluvoxamine, and the following 3 rows show metformin. Below these, the effect of metformin compared with placebo is shown by a priori subgroups of baseline characteristics. Abbreviation: CI, confidence interval.

When the adjustment covariates were dropped one at a time—baseline viral load, vaccination status, time since last vaccination, other study medications within the factorial trial, and the laboratory processing the nasal swabs—in addition to dropping all adjustment covariates, the results were similar. The range in the estimated average effect was −0.51 log 10 copies/mL (95% CI, −1.04 to 0.01; P = .056) to −0.66 log 10 copies/mL (95% CI, −1.215 to −0.097; P = .021) with the latter arising from the unadjusted model ( Supplementary Table 9 ).

Those in the metformin group were less likely to have a detectable viral load than those in the placebo group (OR, 0.72; 95% CI, .55 to .94; Figure 1) . This effect was higher at day 10 (OR, 0.65; 95% CI, .43 to .98) when 1500 mg/d of metformin was being prescribed than at day 5 (OR, 0.79; 95% CI, .60 to 1.05) when 1000 mg/d was prescribed. Viral rebound was defined as having a higher viral load at day 10 than day 5. In the placebo group, 5.95% (22 of 370) of participants had viral rebound compared with 3.28% (12 of 366) in the metformin group (adjusted OR, .68; 95% CI, .36 to 1.29) for metformin compared with placebo ( Figure 1) .

Metformin's effect on continuous viral load and conversion to undetectable viral load was consistent across a priori identified subgroups of baseline characteristics ( Figures 2 and 3 ). Subgroups should be interpreted with caution because of low power, risk of making multiple comparisons without correction, and sparse data bias. One subgroup warrants additional detail for interpretation. The antiviral effect on geometric log 10 scale was greater among those with baseline viral loads <100 000 copies/mL (mean −1.17 log 10 copies/mL reduction) than among those with >100 000 copies/mL (mean −0.49 log 10 copies/mL reduction); although the reduction in absolute copies per milliliter would be greater among those with higher viral loads ( Figures 2 and 3 ). Mean, median viral load levels are presented in Supplementary Table 11 ; sensitivity analyses are presented in Supplementary Figures 5–7 and Supplementary Table 12 .

Overall results for metformin, ivermectin, and fluvoxamine on detectability of viral load; heterogeneity of treatment effect of metformin versus placebo. This is a forest plot that depicts the effect of active medication compared with control on the proportion of participants with a detectable viral load, overall and at days 5 and 10. Estimate* denotes the adjusted mean risk difference in the percent of samples with detected viral load with 95% confidence intervals for the adjusted risk difference. The vertical dashed line indicates the value for a null effect. The estimated risk differences are derived from the adjusted, multiply imputed logistic generalized estimating equations (GEE) analytic approach. The top 3 rows show ivermectin, the next 3 rows show fluvoxamine, and the following 3 rows show metformin. Below these, the effect of metformin compared with placebo is shown by a priori subgroups of baseline characteristics. Abbreviation: CI, confidence interval.

In the virologic end point of the COVID-OUT phase 3, randomized trial, metformin significantly reduced SARS-CoV-2 viral load over 10 days [ 1 ]. The mean reduction was −0.56 log 10 copies/mL greater than placebo. The antiviral response is consistent with the statistically significant and clinically relevant effects of metformin in preventing clinical outcomes: severe COVID-19 (emergency department visit, hospitalization, or death) through day 14, hospitalization or death by day 28, and the diagnosis of long COVID [ 1 , 12 ]. The magnitude of effect on clinical outcomes was larger when metformin was started earlier in the course of infection at <4 days from symptom onset, with metformin reducing the odds of severe COVID-19 by 55% (OR, 0.45; 95% CI, .22 to .93) and of long COVID by 65% (hazard ratio = 0.35; 95% CI, .15 to .95; Figure 4) . An improved effect size for clinical outcomes when therapies are started earlier in the course of infection is consistent with an antiviral action [ 14 ].

Overview of results from the COVID-OUT trial. This is a forest plot that combines the severe, acute coronavirus disease 2019 outcome as well as the long-term follow-up outcome from the COVID-OUT trial [ 1 , 12 ]. Two a priori subgroups from the COVID-OUT trial are also presented: pregnant individuals and those who started the study drug within 4 days of symptom onset, to match the primary analytic sample of other antivirals. Abbreviations: COVID-19, coronavirus disease 2019; ITT, intention to treat; mITT, modified intention to treat; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

The objective of the COVID-OUT trial was to determine whether metformin prevented severe COVID-19. Severe COVID-19 was defined with a binary, 4-part composite outcome (<94% SpO 2 on a home oximeter/emergency department visit/hospitalization/death) at a time when the implications of “silent hypoxia” were unknown and fears of overwhelmed emergency services caused concern that deaths would occur at home before patients reached the emergency department. As a scientific community, we now understand that 1 reading below 94% is not severe COVID-19. An accurate definition of severe COVID-19 (emergency department visit/hospitalization/death) was ascertained within the same data-generation process. In such situations, recommendations are sometimes made based on the totality of evidence from a single randomized trial [ 15–17 ].

The antiviral effect in this phase 3, randomized trial is also consistent with emerging data from other trials. In a phase 2, randomized trial with 20 participants, the metformin group had better clinical outcomes, achieved an undetectable viral load 2.3 days faster than placebo ( P = .03), and had a larger proportion of patients with an undetectable viral load at 3.3 days in the metformin group ( P = .04) [ 18 ]. A recent in vitro study showed that metformin decreased infectious SARS-CoV-2 titers and viral RNA in 2 cell lines, Caco2 and Calu3, at a clinically appropriate concentration [ 19 ].

Conversely, an abandoned randomized trial testing extended-release metformin 1500 mg/d without a dose titration did not report improved SARS-CoV-2 viral clearance at day 7 [ 20 ]. Several differences between the Together Trial and the COVID-OUT trial are important for understanding the data. First, the Together Trial allowed individuals already taking metformin to enroll and be randomized to placebo or more metformin [ 20 , 21 ]. To compare starting metformin versus placebo, the authors excluded those already taking metformin at baseline and reported that emergency department visit or hospitalization occurred in 9.2% (17 of 185) randomized to metformin compared with 14.8% (27 of 183) randomized to placebo (relative risk, 0.63; 95% confidence interval, .35 to 1.10, Probability of superiority = 0.949) [ 22 ]. Thus, the Together Trial results for starting metformin versus placebo are similar. Second, 1500 mg/day without escalating the dose over 6 days would cause side effects, especially if the study participant was already taking metformin [ 23 ]. Third, extended-release and immediate-release metformin have different pharmacokinetic properties. Immediate-release metformin has higher systemic exposure than extended-release metformin, which may improve antiviral actions, but this is not known [ 24 , 25 ]. Given the similar clinical outcomes between immediate and extended-release, a direct comparison of the 2 may be important for understanding pharmacokinetics against SARS-CoV-2.

In comparison with other SARS-CoV-2 antivirals, when considering all enrolled participants, at day 5, the antiviral effect over placebo was 0.47 log 10 copies/mL for metformin, 0.30 log 10 copies/mL for molnupiravir, and 0.80 log 10 copies/mL for nirmatrelvir/ritonavir [ 26 , 27 ]. At day 10, the viral load reduction over blinded placebo was 0.64 log 10 copies/mL for metformin, 0.35 log 10 copies/mL for nirmatrelvir, and 0.19 log 10 copies/mL for molnupiravir [ 26 , 27 ]. We note that the 3 trials enrolled different populations and at different times and locations during the pandemic. In the COVID-OUT metformin trial, half were vaccinated [ 1 , 12 ].

The magnitude of metformin's antiviral effect was larger at day 10 than at day 5 overall and across subgroups, which correlates with the dose titration from 1000 mg on days 2–5 to 1500 mg on days 6–14. The dose titration to 1500 mg over 6 days used in the COVID-OUT trial was faster than typical use. When used chronically, that is, for diabetes, prediabetes, or weight loss, metformin is slowly titrated to 2000 mg daily over 4–8 weeks. While metformin's effect on diabetes control is not consistently dose-dependent, metformin's gastrointestinal side effects are known to be dose-dependent [ 25 ]. Thus, despite what appears to be dose-dependent antiviral effects, a faster dose titration should likely only be considered in individuals with no gastrointestinal side effects from metformin.

When assessing for heterogeneity of effect, metformin was consistent across subgroups. Metformin's antiviral effect in vaccinated versus unvaccinated of −0.48 versus −0.86 log 10 copies/mL at day 10 mirrors nirmatrelvir, for which the effect in seropositive participants was smaller than in the overall trial population, −0.13 versus −0.35 log 10 copies/mL at day 10 [ 26 ]. Effective primed memory B- and T-cell anamnestic immunity prompting effective response by day 5 in vaccinated persons may account for this trend in both trials. Subgroups should be interpreted with caution because of low power and multiple comparisons [ 28 ].

Both nirmatrelvir and molnupiravir are pathogen-directed antiviral agents. Therapeutics may have an important role in targeting host factors rather than viral factors, as targeting the host may be less likely to induce drug-resistant viral variants through mutation–selection [ 11 , 29 ]. We did not study the mechanism for the antiviral activity or an antiinflammatory action in this trial. Previous work has shown that metformin's inhibition of mTOR complex 1 may depend on AMP-activated protein kinase (AMPK) at low doses but not high doses [ 5 ]. An AMPK-independent inhibition of mTOR may be more efficient. Additionally, metformin demonstrates a dose-dependent ability to inhibit interleukin (IL)-1, IL-6, and tumor necrosis factor-alpha in the presence of lipopolysaccharide, inflammatory products that correlate with COVID-19 severity [ 30 , 31 ].

In addition to antiviral activity, metformin appears to have relevant antiinflammatory actions. In mice without diabetes, metformin inhibited mitochondrial ATP and DNA synthesis to evade NLRP3 inflammasome activation [ 32 ]. In macrophages of mice without diabetes infected with SARS-CoV-2, metformin inhibited inflammasome activation, IL-1 production, and IL-6 secretion and also increased the IL-10 antiinflammatory response to lipopolysaccharide, thereby attenuating lipopolysaccharide-induced lung injury [ 32 ]. In a recent assay of human lung epithelial cell lines, metformin inhibited the cleavage of caspase-1 by NSP6, inhibiting the maturation and release of IL-1, a key factor that mediates inflammatory responses [ 7 ]. The idea of pleiotropic effects is being embraced in novel therapeutics being developed for both antiviral and anti-inflammatory actions [ 33 ].

Strengths of our study include the large sample size and detailed participant information collected, including the exact time and date of specimen collection. One limitation was the sampling time frame of only day 1, day 5, and day 10 due to limited resources. By day 10 post-randomization, 77% of participants in the placebo group and 86% in the metformin group had an undetectable viral load. As viral load is lower in vaccinated persons [ 34 ], this degree of undetectable viral loads differs from findings from earlier clinical trials conducted in unvaccinated participants without known prior infection [ 26 , 27 ]. Sampling earlier and more frequently, that is, day 1, day 3, day 6, and day 9 in future trials, may better characterize differences in viral shedding earlier in the infection and over time, dependent on the duration of therapy and timing of enrollment.

Future work could assess whether synergy exists between metformin and direct SARS-CoV-2 antivirals, as previous work showed that metformin improved sustained virologic clearance of hepatitis C virus and improved outcomes in other respiratory infections [ 35–37 ]. The biophysical modeling that motivated this trial predicts additive/cooperative effects in combination with transcription inhibitors. Combination therapy might decrease selective pressure, and metformin has few medication interactions, so treatment with metformin could continue beyond 5 days while home medications are restarted. Additionally, continuing metformin could reduce symptom rebound, given its effects on T-cell immunity [ 38 , 39 ]. Further data are needed to understand whether decreased viral load and faster viral clearance decrease onward transmission of SARS-CoV-2.

Metformin is safe in children and pregnant individuals with and without preexisting diabetes [ 40–42 ]. Individuals with or without diabetes do not need to check blood sugar when taking metformin. Historical concerns about lactic acidosis were driven by other biguanides; metformin does not increase risk of lactic acidosis [ 43 ]. Metformin improves outcomes in patients with heart, liver, and kidney failure, as well as during hospitalizations and perioperatively [ 44–48 ].

In a large randomized, controlled trial conducted in nonhospitalized, standard-risk adults, metformin reduced the incidence of severe COVID-19 by day 14, of hospitalizations by day 28, and of long COVID diagnosis by day 300. In this virologic analysis, we found a corresponding significant reduction in viral load with metformin compared with placebo and a lower likelihood of viral load rebound. While 22% of participants in the trial were enrolled during the Omicron era, metformin has not been assessed in individuals with a history of prior infection and thus should be trialed in the current state of the pandemic. Metformin is currently being trialed in low-risk adults [ 49 ].

Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.

Disclaimer. The funders had no influence on the design or conduct of the trial and were not involved in data collection or analysis, writing of the manuscript, or decision to submit for publication. The authors assume responsibility for trial fidelity and the accuracy and completeness of the data and analyses.

Financial support . The fluvoxamine placebo tablets were donated by the Apotex Pharmacy. The ivermectin placebo and active tablets were donated by the Edenbridge Pharmacy. The trial was funded by the Parsemus Foundation, Rainwater Charitable Foundation, Fast Grants, and the UnitedHealth Group Foundation. C. T. B. was supported by grants (KL2TR002492 and UL1TR002494) from the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) and by a grant (K23 DK124654) from the National Institute of Diabetes and Digestive and Kidney Diseases of the NIH. J. B. B. was supported by a grant (UL1TR002489) from NCATS. J. M. N. was supported by a grant (K23HL133604) from the National Heart, Lung, and Blood Institute (NHLBI) of the NIH. D. J. O. was supported by the Institute for Engineering in Medicine, University of Minnesota Office of Academic and Clinical Affairs COVID-19 Rapid Response Grant, the Earl E. Bakken Professorship for Engineering in Medicine, and by grants (U54 CA210190 and P01 CA254849) from the National Cancer Institute of the NIH. D. M. L. receives funding from NIH RECOVER (OT2HL161847). L. K. S. was supported by NIH grants (18X107CF6 and 18X107CF5) through a contract with Leidos Biomedical and by grants from the HLBI of the NIH (T32HL129956) and the NIH (R01LM012982 and R21LM012744). M. A. P. receives grants from the Bill and Melinda Gates Foundation (INV-017069), Minnesota Partnership for Biotechnology and Medical Genomics (00086722) and NHLBI (OT2HL156812).

Bramante CT , Huling JD , Tignanelli CJ , et al.  Randomized trial of metformin, ivermectin, and fluvoxamine for Covid-19 . New Engl J Med 2022 ; 387 : 599 – 610 .

Google Scholar

Castle BT , Dock C , Hemmat M , et al.  Biophysical modeling of the SARS-CoV-2 viral cycle reveals ideal antiviral targets. bioRxiv 111237 [Preprint]. June 16, 2020. Available from: https://doi.org/10.1101/2020.05.22.111237 .

Gordon DE , Jang GM , Bouhaddou M , et al.  A SARS-CoV-2 protein interaction map reveals targets for drug repurposing . Nature 2020 ; 583 : 459 – 68 .

Schaller MA , Sharma Y , Dupee Z , et al.  Ex vivo SARS-CoV-2 infection of human lung reveals heterogeneous host defense and therapeutic responses . JCI Insight 2021 ; 6 : e148003 .

Howell JJ , Hellberg K , Turner M , et al.  Metformin inhibits hepatic mTORC1 signaling via dose-dependent mechanisms involving AMPK and the TSC complex . Cell Metab 2017 ; 25 : 463 – 71 .

Bailey CJ . Metformin: historical overview . Diabetologia 2017 ; 60 : 1566 – 76 .

Garcia EY . Flumamine, a new synthetic analgesic and antiflu drug . Philippine Med Assoc 1950 ; 26 : 287 – 93 .

Singh S , Singh PK , Suhail H , et al.  AMP-activated protein kinase restricts Zika virus replication in endothelial cells by potentiating innate antiviral responses and inhibiting glycolysis . J Immunol 2020 ; 204 : 1810 – 24 .

Cheng F , Ramos da Silva S , Huang IC , Jung JU , Gao SJ . Suppression of Zika virus infection and replication in endothelial cells and astrocytes by PKA inhibitor PKI 14-22 . J Virol 2018 ; 92 : e02019 – 17 .

Del Campo JA , García-Valdecasas M , Gil-Gómez A , et al.  Simvastatin and metformin inhibit cell growth in hepatitis C virus infected cells via mTOR increasing PTEN and autophagy . PLoS One 2018 ; 13 : e0191805 .

Maiese K . The mechanistic target of rapamycin (mTOR): novel considerations as an antiviral treatment . Curr Neurovasc Res 2020 ; 17 : 332 – 7 .

Bramante CT , Buse JB , Liebovitz DM , et al.  Outpatient treatment of COVID-19 and incidence of post-COVID-19 condition over 10 months (COVID-OUT): a multicentre, randomised, quadruple-blind, parallel-group, phase 3 trial . Lancet Infect Dis 2023 ; 23 : 1119 – 29 .

Mannan N , Raihan R , Parvin US , et al.  Detection of SARS-CoV-2 RNA by reverse transcription-polymerase chain reaction (RT-PCR) on self-collected nasal swab compared with professionally collected nasopharyngeal swab . Cureus 2022 ; 14 : e25618 .

Gil Martínez V , Avedillo Salas A , Santander Ballestín S . Antiviral therapeutic approaches for SARS-CoV-2 infection: a systematic review . Pharmaceuticals (Basel) 2021 ; 14 : 736 .

Pocock SJ , Rossello X , Owen R , Collier TJ , Stone GW , Rockhold FW . Primary and secondary outcome reporting in randomized trials: JACC state-of-the-art review . J Am Coll Cardiol 2021 ; 78 : 827 – 39 .

Pocock SJ , Stone GW . The primary outcome fails—what next? New Engl J Med 2016 ; 375 : 861 – 70 .

Dahlöf B , Devereux RB , Kjeldsen SE , et al.  Cardiovascular morbidity and mortality in the Losartan Intervention For Endpoint reduction in hypertension study (LIFE): a randomised trial against atenolol . Lancet 2002 ; 359 : 995 – 1003 .

Ventura-Lopez C , Cervantes-Luevano K , Aguirre-Sanchez JS , et al.  Treatment with metformin glycinate reduces SARS-CoV-2 viral load: an in vitro model and randomized, double-blind, phase IIb clinical trial . Biomed Pharmacother 2022 ; 152 : 113223 .

Parthasarathy H , Tandel D , Siddiqui AH , Harshan KH . Metformin suppresses SARS-CoV-2 in cell culture . Virus Res 2022 ; 323 : 199010 .

Reis G , Dos Santos Moreira Silva EA , Medeiros Silva DC , et al.  Effect of early treatment with metformin on risk of emergency care and hospitalization among patients with COVID-19: the TOGETHER randomized platform clinical trial . Lancet Reg Health Am 2022 ; 6 : 100142 .

Expression of concern – Effect of early treatment with metformin on risk of emergency care and hospitalization among patients with COVID-19: the TOGETHER randomized platform clinical trial. Lancet Reg health Am 2024 ; 31 : 100703 .

Mills EJ . Email communications to D. Boulware and C. Bramante on 1/5/24, 1/12/24 .

Henry RR , Frias JP , Walsh B , et al.  Improved glycemic control with minimal systemic metformin exposure: effects of metformin delayed-release (metformin DR) targeting the lower bowel over 16 weeks in a randomized trial in subjects with type 2 diabetes . PLoS One 2018 ; 13 : e0203946 .

DeFronzo RA , Buse JB , Kim T , et al.  Once-daily delayed-release metformin lowers plasma glucose and enhances fasting and postprandial GLP-1 and PYY: results from two randomised trials . Diabetologia 2016 ; 59 : 1645 – 54 .

Buse JB , DeFronzo RA , Rosenstock J , et al.  The primary glucose-lowering effect of metformin resides in the gut, not the circulation: results from short-term pharmacokinetic and 12-week dose-ranging studies . Diabetes Care 2016 ; 39 : 198 – 205 .

Hammond J , Leister-Tebbe H , Gardner A , et al.  Oral nirmatrelvir for high-risk, nonhospitalized adults with Covid-19 . New Engl J Med 2022 ; 386 : 1397 – 408 .

Jayk Bernal A , Gomes da Silva MM , Musungaie DB , et al.  Molnupiravir for oral treatment of Covid-19 in nonhospitalized patients . New Engl J Med 2022 ; 386 : 509 – 20 .

Greenland S , Mansournia MA , Altman DG . Sparse data bias: a problem hiding in plain sight . BMJ 2016 ; 352 : i1981 .

Pérez-Pérez M-J , Saiz J-C , Priego E-M , Martín-Acebes MA . Antivirals against (re)emerging flaviviruses: should we target the virus or the host? ACS Med Chem Lett 2022 ; 13 : 5 – 10 .

Rodrigues TS , de Sa KSG , Ishimoto AY , et al.  Inflammasomes are activated in response to SARS-CoV-2 infection and are associated with COVID-19 severity in patients . J Exp Med 2021 ; 218 : e20201707 .

Hyun B , Shin S , Lee A , et al.  Metformin down-regulates TNF-α secretion via suppression of scavenger receptors in macrophages . Immune Netw 2013 ; 13 : 123 – 32 .

Xian H , Liu Y , Rundberg Nilsson A , et al.  Metformin inhibition of mitochondrial ATP and DNA synthesis abrogates NLRP3 inflammasome activation and pulmonary inflammation . Immunity 2021 ; 54 : 1463 – 77.e11 .

Barnette KG , Gordon Michael S , Rodriguez D , et al.  Oral sabizabulin for high-risk, hospitalized adults with Covid-19: interim analysis . NEJM Evidence 2022 ; 1 : EVIDoa2200145 .

Bramante CT , Proper JL , Boulware DR , et al.  Vaccination against SARS-CoV-2 is associated with a lower viral load and likelihood of systemic symptoms . Open Forum Infect Dis 2022 ; 9 : ofac066 .

Goto M , Perencevich EN . Metformin and infections: what is the next step in this decades-long story? Clin Infect Dis 2023 ; 76 : 1245 – 6 .

Mohammed T , Bowe M , Plant A , Perez M , Alvarez CA , Mortensen EM . Metformin use is associated with lower mortality in veterans with diabetes hospitalized with pneumonia . Clin Infect Dis 2023 ; 76 : 1237 – 44 .

Yu J-W , Sun L-J , Zhao Y-H , Kang P , Yan B-Z . The effect of metformin on the efficacy of antiviral therapy in patients with genotype 1 chronic hepatitis C and insulin resistance . Int J Infect Dis 2012 ; 16 : e436 – 41 .

Wabitsch S , McCallen JD , Kamenyeva O , et al.  Metformin treatment rescues CD8+ T-cell response to immune checkpoint inhibitor therapy in mice with NAFLD . J Hepatol 2022 ; 77 : 748 – 60 .

Xu L , Wang X , Chen Y , et al.  Metformin modulates T cell function and alleviates liver injury through bioenergetic regulation in viral hepatitis . Front Immunol 2021 ; 12 : 638575 .

Boggess KA , Valint A , Refuerzo JS , et al.  Metformin plus insulin for preexisting diabetes or gestational diabetes in early pregnancy: the MOMPOD randomized clinical trial . JAMA 2023 ; 330 : 2182 – 90 .

Dunne F , Newman C , Alvarez-Iglesias A , et al.  Early metformin in gestational diabetes: a randomized clinical trial . JAMA 2023 ; 330 : 1547 – 56 .

Mauras N , DelGiorno C , Hossain J , et al.  Metformin use in children with obesity and normal glucose tolerance — effects on cardiovascular markers and intrahepatic fat . J Pediatr Endocrinol Metab 2012 ; 25 : 33 – 40 .

Smith FC , Stocker SL , Danta M , et al.  The safety and pharmacokinetics of metformin in patients with chronic liver disease . Aliment Pharmacol Ther 2020 ; 51 : 565 – 75 .

Zhang X , Harmsen WS , Mettler TA , et al.  Continuation of metformin use after a diagnosis of cirrhosis significantly improves survival of patients with diabetes . Hepatology 2014 ; 60 : 2008 – 16 .

Eurich DT , Weir DL , Majumdar SR , et al.  Comparative safety and effectiveness of metformin in patients with diabetes mellitus and heart failure: systematic review of observational studies involving 34,000 patients . Circ Heart Fail 2013 ; 6 : 395 – 402 .

Clegg LE , Jing Y , Penland RC , et al.  Cardiovascular and renal safety of metformin in patients with diabetes and moderate or severe chronic kidney disease: observations from the EXSCEL and SAVOR-TIMI 53 cardiovascular outcomes trials . Diabetes Obes Metab 2021 ; 23 : 1101 – 10 .

Chang LL , Umpierrez GE , Inzucchi SE . Management of hyperglycemia in hospitalized, non-critically ill adults . New Engl J Med 2022 ; 387 : 1040 – 2 .

Reitz KM , Marroquin OC , Zenati MS , et al.  Association between preoperative metformin exposure and postoperative outcomes in adults with type 2 diabetes . JAMA Surgery 2020 ; 155 : e200416 .

Narayanasamy S , Curtis LH , Hernandez AF , et al.  Lessons from COVID-19 for pandemic preparedness: proceedings from a multistakeholder think tank . Clin Infect Dis 2023 ; 77 : 1635 – 43 .

Author notes

• coronavirus
• antiviral agents
• outpatients
• viral load result
• severe acute respiratory syndrome
• post-acute covid-19 syndrome

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• Research Article
• Open access
• Published: 16 August 2024

Epidemiological features and temporal trends of the co-infection between HIV and tuberculosis, 1990–2021: findings from the Global Burden of Disease Study 2021

• Shun-Xian Zhang 1 , 2   na1 ,
• Ji-Chun Wang 3   na1 ,
• Jian Yang 3 ,
• Shan Lv 2 ,
• Lei Duan 2 ,
• Li-Guang Tian 2 ,
• Mu-Xin Chen 2 ,
• Qin Liu 2 ,
• Fan-Na Wei 2 ,
• Xin-Yu Feng 4 ,
• Guo-Bing Yang 5 ,
• Yong-Jun Li 5 ,
• Yu Wang 1 ,
• Xiao-Jie Hu 1 ,
• Ming Yang 1 ,
• Zhen-Hui Lu 1 ,
• Shao-Yan Zhang 1 ,
• Shi-Zhu Li 2 &
• Jin-Xin Zheng   ORCID: orcid.org/0000-0003-1476-1903 4  

Infectious Diseases of Poverty volume  13 , Article number:  59 ( 2024 ) Cite this article

360 Accesses

Metrics details

The co-infection of human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) and tuberculosis (TB) poses a significant clinical challenge and is a major global public health issue. This study aims to elucidate the disease burden of HIV-TB co-infection in global, regions and countries, providing critical information for policy decisions to curb the HIV-TB epidemic.

The ecological time-series study used data from the Global Burden of Disease (GBD) Study 2021. The data encompass the numbers of incidence, prevalence, mortality, and disability-adjusted life year (DALY), as well as age-standardized incidence rate (ASIR), prevalence rate (ASPR), mortality rate (ASMR), and DALY rate for HIV-infected drug-susceptible tuberculosis (HIV-DS-TB), HIV-infected multidrug-resistant tuberculosis (HIV-MDR-TB), and HIV-infected extensively drug-resistant tuberculosis (HIV-XDR-TB) from 1990 to 2021. from 1990 to 2021. The estimated annual percentage change (EAPC) of rates, with 95% confidence intervals ( CI s), was calculated.

In 2021, the global ASIR for HIV-DS-TB was 11.59 per 100,000 population (95% UI: 0.37–13.05 per 100,000 population), 0.55 per 100,000 population (95% UI: 0.38–0.81 per 100,000 population), for HIV-MDR-TB, and 0.02 per 100,000 population (95% UI: 0.01–0.03 per 100,000 population) for HIV-XDR-TB. The EAPC for the ASIR of HIV-MDR-TB and HIV-XDR-TB from 1990 to 2021 were 4.71 (95% CI: 1.92–7.59) and 13.63 (95% CI: 9.44–18.01), respectively. The global ASMR for HIV-DS-TB was 2.22 per 100,000 population (95% UI: 1.73–2.74 per 100,000 population), 0.21 per 100,000 population (95% UI: 0.09–0.39 per 100,000 population) for HIV-MDR-TB, and 0.01 per 100,000 population (95% UI: 0.00–0.03 per 100,000 population) for HIV-XDR-TB in 2021. The EAPC for the ASMR of HIV-MDR-TB and HIV-XDR-TB from 1990 to 2021 were 4.78 (95% CI: 1.32–8.32) and 10.00 (95% CI: 6.09–14.05), respectively.

Conclusions

The findings indicate that enhancing diagnostic and treatment strategies, strengthening healthcare infrastructure, increasing access to quality medical care, and improving public health education are essential to combat HIV-TB co-infection.

Graphical Abstract

Acquired immune deficiency syndrome (AIDS) is a chronic, systemic, and fatal infectious disease caused by the human immunodeficiency virus (HIV) [ 1 ]. HIV disrupts the function of immune T cells and macrophages, particularly reducing the levels and activity of CD4  +  T lymphocytes, leading to immunosuppression and opportunistic infections (OPIs) [ 2 , 3 ]. Tuberculosis (TB), caused by Mycobacterium tuberculosis ( Mtb ), is one of the most common OPIs in persons living with HIV (PLWH). Primarily a respiratory disease, TB is chronic and wasting, with a prolonged course often resulting in fatal outcomes [ 1 ].

HIV and TB pose significant global public health challenges, contributing substantially to morbidity and mortality worldwide [ 4 , 5 , 6 ]. In 2021, there were 7.5 million newly diagnosed and officially notified TB cases globally, with 0.63 million individuals co-infected with HIV [ 5 , 6 ]. Despite the implementation of standardized TB chemotherapy over 30 years ago, TB remains the leading cause of death from a single infectious agent. In 2021, TB caused 1.3 million deaths, including 1.13 million among HIV-negative individuals and 0.17 million among PLWH [ 5 , 6 ]. Globally, approximately 39.0 million individuals were PLWH in 2023, and 0.63 million died from AIDS-related illnesses[ 6 ].

In nature, host species often harbor multiple pathogens, making co-infection common [ 7 , 8 ]. The interaction between different microorganisms can alter infection outcomes and significantly impact disease progression. Co-infection with HIV and TB leads to more severe clinical symptoms and faster disease progression compared to single infections [ 7 ]. Patients co-infected with HIV and TB have a significantly higher mortality risk than those with either infection alone, earning the designation "deadly human co-infection" [ 1 , 6 ]. Despite the standardized treatment of PLWH using highly active antiretroviral therapy (HAART), the mortality rate for HIV-positive TB patients was 5.96 times higher than for HIV-negative TB cases [ 5 , 6 ].

A comprehensive understanding of the burden and epidemiological trends of HIV-TB co-infection is crucial for assessing progress towards ending the epidemic and guiding policy formulation and program implementation [ 1 , 5 , 6 ]. The Global Burden of Disease (GBD) Study 2021 evaluates disease burden by examining rates and numbers of incidence, prevalence, deaths, and disability-adjusted life years (DALYs) worldwide [ 9 , 10 ]. It provides essential foundational data, enabling the exploration of the epidemiological characteristics of HIV-TB co-infection. The study aims to describe the epidemiological features of HIV-associated drug-susceptible tuberculosis (HIV-DS-TB), HIV-associated multidrug-resistant tuberculosis (HIV-MDR-TB), and extensively drug-resistant tuberculosis in HIV-positive individuals (HIV-XDR-TB) across regions, countries and territories from 1990 to 2021 [ 1 , 9 , 10 ]. These conclusions underscore the urgency of HIV-TB control within the global health framework and provide a scientific basis for developing more effective public health strategies and programs to curb HIV-TB transmission.

Date source

The GBD Study 2021 scientifically and comprehensively evaluated the burden of diseases, injuries, and risk factors across different age and gender groups globally, providing data on 371 diseases or injuries and 88 risk factors from 204 countries and territories spanning 1990 to 2021 [ 1 , 9 , 10 ]. The study utilized the Disease Modeling-Bayesian meta-regression (DisMod-MR) tool (version 2.1), employing Bayesian priors, regularization, and trimming (MR-BRT) modeling. This tool integrated all available morbidity and mortality data, along with epidemiological and spatial relationships, to produce internally consistent disease burden estimates. Detailed information on the design, data collection, and estimation methods is available elsewhere [ 1 , 9 , 10 ].

For HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB, data on incident cases, incidence rates, prevalence numbers, prevalence rates, death numbers, mortality rates, DALYs numbers, and DALY rates were obtained from the Institute for Health Metrics and Evaluation (IHME) website ( https://vizhub.healthdata.org . Additional file 1 ). These indices were categorized by year, age group, gender, region, and country or territory.

The GBD 2021 estimated various risk factors for mortality and DALYs [ 9 , 10 ]. Data on age-standardized mortality rates (ASMRs) and age-standardized DALY rates due to risk factors (level 2) were utilized in this study (Additional file 1 ). The Socio-demographic Index (SDI) was calculated in GBD 2021 to represent the combined level of health-related social and economic conditions in each region. The SDI values were scaled from 0.00 to 1.00 and multiplied by 100, categorize countries and territories into five development levels: low (< 0.46), low-middle (0.46–0.60), middle (0.61–0.69), high-middle (0.70–0.81), and high (> 0.81) [ 9 , 10 ].

Case definition

The International Classification of Diseases (ICD)-10 code for HIV-TB co-infection is B20.0 [ 9 , 10 ]. HIV-DS-TB is defined as tuberculosis in HIV-positive individuals that is susceptible to both isoniazid and rifampicin. HIV-MDR-TB refers to tuberculosis in HIV-positive individuals that is resistant to the two most effective first-line anti-tuberculosis drugs, isoniazid and rifampicin, but not resistant to any fluoroquinolones or second-line injectable drugs (amikacin, kanamycin, or capreomycin). HIV-XDR-TB is tuberculosis in HIV-positive individuals that is resistant to isoniazid, rifampicin, any fluoroquinolone, and at least one second-line injectable drug (Additional file 1 ) [ 1 , 9 , 10 ].

Statistical analysis

The disease burden of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB was quantified using the age-standardized incidence rates (ASIRs), age-standardized prevalence rates (ASPRs), ASMRs, and age-standardized DALY rates, and the numbers for incidence, prevalence, death, and DALYs were also recorded. Age-standardized rates (ASRs, per 100,000 people) from all age groups, specific rates from specific age groups, and numbers were extracted from the GBD 2021 database. Corresponding data are presented as estimates with 95% uncertainty intervals ( UIs) [ 9 , 10 ]. The formula for calculating ASR is:

where \(a_{i}\) the age-specific rate in the \(i\) th age group and \(w_{{\text{i}}}\) is the number of people in the standard population within each age group. \(N\) represents the number of age groups. The 95% UIs were defined as the 2.5th and 97.5th values of the ordered 1000 draws.

The percentage changes in numbers and rates (incidence, prevalence, death, and DALYs) from 1990 to 2021 were calculated using the formula [ 1 , 9 , 10 ]:

Percentage changes = (value behind –value before )/value before  × 100%. The GBD database used UIs instead of precise statistical values. Consequently, when comparing two numerical values (numbers, rates, or percentages), Statistical significance could not be directly calculated; if the UIs overlapped, it indicated no significant difference ( P  > 0.05). Conversely, if the UIs did not overlap, a statistical difference existed ( P  < 0.05).

Smoothing spline models were used to evaluate the association between ASRs (ASIRs, ASMRs, ASPRs, age-standardized DALY rates for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB) and the SDI across global, five SDI regions, 21 geographical regions, 204 countries and territories. Smooth splines using the Locally Weighted Scatterplot Smoothing method were fitted, which automatically determines the degree, number, and location of knots based on the data and the span parameter [ 1 , 9 , 10 , 11 ]. Spearman's rank correlation coefficient was used to verify the correlations between ASRs and SDI. A P -value of less than 0.05 was considered statistically significant.

The estimated annual percentage change (EAPC) of ASRs was calculated to describe the trend fluctuation of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB from 1990 to 2021. It involved a linear regression model \(y = \alpha + \beta x + \varepsilon\) , where \(y\) is equal to natural logarithm of (ASR), \(x\) signifies the calendar year, and \(\varepsilon\) denotes an independent, normally distributed error term [ 4 ]. The EAPC is then calculated as 100 × (e β – 1), the EAPC and their 95% confidence intervals ( CI s) are utilized to describe trends over specified time intervals [τ j—1 , τ j ]. If the upper limit of the EAPC (95% CIs ) is less than zero, the rate exhibits a statistically significant declining trend over the observed period. Conversely, if the lower limit of the EAPC (95% CI s) is greater than zero, the rate shows a statistically significant increasing trend. When the EAPC (95% CI ) includes 0, the change in ASR is considered statistically non-significant, indicating that the observed trend is not statistically different from no change [ 4 ].

The Bayesian age-period-cohort (BAPC) model, using default parameters, was employed to examine the multiplicative effects of age, period, and cohort [ 11 , 12 ]:

\(\eta_{ij} \, = \,\mu \, + \,\alpha_{i} + \,\beta_{j} \, + \,\gamma_{k}\) . In this model, \(\eta_{ij}\) stand for the ASR, \(\mu\) denotes the intercept, and \(\alpha_{i}\) and \(\gamma_{k}\) were age, period, and cohort effects, respectively.

All statistical analyses were conducted using R software (version 4.4.1. R Foundation for Statistical Computing, Vienna, Austria. https://cran.r-project.org ).

Incidence and temporal trend

In 2021, the global ASIR for HIV-DS-TB was 11.59 per 100,000 population (95% UI: 10.37–13.05 per 100,000 population). For HIV-MDR-TB, the ASIR was 0.55 per 100,000 population (95% UI: 0.38–0.81 per 100,000 population), and for HIV-XDR-TB, it was 0.02 per 100,000 population (95% UI: 0.01–0.03 per 100,000 population. Table 1 ). Additionally, the EAPC for the ASIR of HIV-DS-TB and HIV-MDR-TB from 1990 to 2021 were −0.67 (95% CI: −1.81, 0.05) and 4.71 (95% CI: 1.92–7.59), respectively. The EAPC for the ASIR of HIV-XDR-TB from 1991 to 2021 was 13.63 (95% CI: 9.44–18.01).

In 2021, the global incidence of HIV-DS-TB was 955,221 individuals (95% UI: 854,661–1,075,240 individuals), HIV-MDR-TB was 45,589 individuals (95% UI: 31,326–66,723 individuals), and HIV-XDR-TB was 1606 individuals (95% UI: 1164–2183 individuals) (Additional file 1 : Table S1).

In 2021, the ASIR for HIV-DS-TB was 13.19 per 100,000 population (95% UI: 11.79–14.85 per 100,000 population) among females, compared to 10.03 per 100,000 population (95% UI: 9.00–11.28 per 100,000 population) among males. The ASIR for HIV-DS-TB was higher in females than in males ( P  < 0.05. Table 1 ). However, there were no significant differences in the ASIR for HIV-MDR-TB and HIV-XDR-TB between males and females (all P  > 0.05. Table 1 ). Compared to 1990, the ASIR for both HIV-DS-TB and HIV-MDR-TB increased in both genders, but the increase in ASIR for HIV-MDR-TB was significantly higher than that for HIV-DS-TB in both males and females (both P  < 0.05. Table 1 ).

In 2021, the highest ASIR for HIV-DS-TB and HIV-MDR-TB was observed in the low SDI region, while the lowest ASIR was in the high SDI region. For HIV-XDR-TB, the highest ASIR was recorded in the high-middle SDI region, with the lowest in the high SDI region (Table  1 ). From 1990 to 2021, the ASIR for HIV-DS-TB began to decline across all five SDI regions after 2005. For HIV-MDR-TB, the ASIR remained stable only in the middle SDI region, while it decreased in the other four SDI regions. In recent years, the ASIR of HIV-XDR-TB has remained relatively stable in the high, high-middle, and middle SDI regions (Additional file 1 : Fig. S1 A–C).

In 2021, the highest ASIR for HIV-DS-TB and HIV-MDR-TB were recorded in sub-Saharan Africa, while the highest ASIR for HIV-XDR-TB was observed in Eastern Europe. Compared to 1990, regions with increasing ASIR for HIV-DS-TB included Oceania, South Asia, Southeast Asia, and North Africa and the Middle East (all P  < 0.05. Table 1 ). Regions where the ASIR for HIV-DS-TB decreased included Central Asia, Central Europe, Australasia, Western Europe, Southern Latin America, high-income North America, the Caribbean, Andean Latin America, Central Latin America, and Tropical Latin America (all P  < 0.05. Table 1 ). For HIV-MDR-TB, the largest increase in ASIR was observed in Oceania, followed by South Asia and Central Asia (all P  < 0.05. Table 1 ). Conversely, the ASIR for HIV-MDR-TB decreased in Western Europe and high-income North America (both P  < 0.05. Table 1 ).

In 2021, the country with the highest ASIR for HIV-DS-TB was Lesotho. For HIV-MDR-TB and HIV-XDR-TB, the highest ASIR was observed in Eswatini. Compared to 1990, the country with the greatest increase in ASIR for both HIV-DS-TB and HIV-MDR-TB in 2021 was Pakistan (both P  < 0.05. Additional file 1 : Table S2).

Prevalence and temporal trend

In 2021, the global ASPR for HIV-DS-TB was 20.41 per 100,000 population (95% UI: 18.14–22.82 per 100,000 population). For HIV-MDR-TB, the ASPR was 0.87 per 100,000 population (95% UI: 0.59–1.29 per 100,000 population), and for HIV-XDR-TB, it was 0.02 per 100,000 population (95% UI: 0.02–0.03 per 100,000 population. Table 2 ). The EAPC for the ASPR of HIV-DS-TB and HIV-MDR-TB from 1990 to 2021 were −0.71 (95% CI: −1.77, 0.37) and 4.97 (95% CI: 2.32–7.70), respectively, while the EAPC for the ASPR of HIV-XDR-TB from 1991 to 2021 was 13.79 (95% CI: 10.03–17.67).

In 2021, the global prevalence of HIV-DS-TB was 1,682,115 cases (95% UI: 1,494,990–1,881,082 persons), the prevalence of HIV-MDR-TB was 71,455 cases (95% UI: 48,999–106,009 persons), and the prevalence of HIV-XDR-TB was 1727 cases (95% UI: 1241–2427 persons. Additional file 1 : Table S3).

In 2021, the ASPR for HIV-DS-TB, HIV-MDR-TB and HIV-XDR-TB showed no significant differences between genders (all P  > 0.05). Compared to 1990, the ASPR of HIV-DS-TB and HIV-MDR-TB increased in both females and males (all P  < 0.05. Table 2 ).

In 2021, the highest ASPR for HIV-DS-TB and HIV-MDR-TB was observed in the low SDI region, while the lowest was in the high SDI region. For HIV-XDR-TB, the highest ASPR was found in the high-middle SDI region, and the lowest in the high SDI region. From 1990 to 2021, the ASPR for HIV-DS-TB and HIV-MDR-TB initially increased across all five SDI regions but started to decline after 2010. Conversely, the ASPR for HIV-XDR-TB has been rapidly rising in the low SDI region and slowly increasing in the high and middle SDI regions (Additional file 1 : Fig.S2 A–C).

In 2021, the highest ASPR for HIV-DS-TB and HIV-MDR-TB were recorded in Southern sub-Saharan Africa. For HIV-XDR-TB, the highest ASPR was in Eastern Europe. Compared to 1990, regions with increased ASPR for HIV-DS-TB in 2021 included Oceania, South Asia, Southeast Asia, East Asia, and North Africa and the Middle East (all P  < 0.05. Table 2 ). Conversely, the ASPR for HIV-DS-TB decreased in Western Europe and high-income North America (both P  < 0.05. Table 2 ). The regions with the most significant increases in ASPR for HIV-MDR-TB were Oceania, followed by South Asia and Central Asia (all P  < 0.05. Table 2 ). The ASPR for HIV-MDR-TB decreased only in high-income North America ( P  < 0.05, Table  2 ).

In 2021, the country with the highest ASPR for HIV-DS-TB was Lesotho. For HIV-MDR-TB and HIV-XDR-TB, the highest ASPR were observed in Eswatini. Compared to 1990, the country with the most significant increases in HIV-DS-TB and HIV-MDR-TB prevalence rates by 2021 was Pakistan (both P  < 0.05. Additional file 1 : Table S2).

Mortality and temporal trend

In 2021, the global ASMR for HIV-DS-TB was 2.22 per 100,000 population (95% UI: 1.73–2.74 per 100,000 population), for HIV-MDR-TB it was 0.21 per 100,000 population (95% UI: 0.09–0.39 per 100,000 population), and for HIV-XDR-TB it was 0.01 per 100,000 population (95% UI: 0.00–0.02 per 100,000 population. Table 3 ). The EAPC for the ASMR of HIV-DS-TB from 1990 to 2021 was −1.56 (95% CI: −3.22, 0.12), and for HIV-MDR-TB it was 4.78 (95% CI: 1.32–8.32). The EAPC for the ASMR of HIV-XDR-TB from 1993 to 2021 was 10.00 (95% CI: 6.09–14.05).

In 2021, the global number of deaths due to HIV-DS-TB was 182,597 individuals (95% UI: 141,923–225,076 individuals), for HIV-MDR-TB it was 17,458 (95% UI: 7574–32,229 individuals), and for HIV-XDR-TB it was 840 (95% UI: 385–1492 individuals. Additional file 1 : Table S4).

In 2021, there was no significant difference in the ASMR for HIV-DS-TB, HIV-MDR-TB and HIV-XDR-TB between males and females (all P  > 0.05. Table 3 ). Compared to 1990, the ASMR for HIV-DS-TB did not show significant changes in either gender ( P  > 0.05. Table 3 ). However, the ASMR for HIV-MDR-TB significantly increased in both males and females (both P  < 0.05. Table 3 ).

In 2021, the highest ASMR for HIV-DS-TB and HIV-MDR-TB were observed in the low SDI region, while the lowest rates were in the high SDI region. Conversely, the highest ASMR for HIV-XDR-TB was recorded in the high-middle SDI region, with the lowest in the high SDI region (Table  3 ). From 1990 to 2021, the ASMR for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB initially increased and then decreased across the five SDI regions (Additional file 1 : Fig. S3 A–C). Notably, post-2010, these rates generally declined. However, the decrease in ASMR for HIV-XDR-TB markedly slowed (Additional file 1 : Fig. S3 A–C).

In 2021, the highest ASMR for HIV-DS-TB and HIV-MDR-TB was found in Southern sub-Saharan Africa, while the highest ASMR for HIV-XDR-TB was in Eastern Europe. Compared to 1990, regions with an increased ASMR for HIV-DS-TB in 2021 included South Asia, Oceania, Southern sub-Saharan Africa, Southeast Asia, East Asia, high-income Asia Pacific, and Southern Latin America (all P  < 0.05. Table 3 ). In contrast, Western Europe and high-income North America experienced a decline in ASMR for HIV-DS-TB (both P  < 0.05. Table 3 ). The regions with the largest increase in ASMR for HIV-MDR-TB were South Asia, Oceania, and Central Asia (all P  < 0.05. Table 3 ). Conversely, Western Europe and high-income North America were the regions with a decline in ASMR for HIV-MDR-TB (both P  < 0.05. Table 3 ).

In 2021, the country with the highest ASMR for HIV-DS-TB was Lesotho. For both HIV-MDR-TB and HIV-XDR-TB, the highest ASMR was in Eswatini. Compared to 1990, the country with the largest increase in ASMR for HIV-DS-TB in 2021 was Pakistan, while the country with the largest increase in ASMR for HIV-MDR-TB was Cambodia (all P  < 0.05. Additional file 1 : Table S2).

DALY and temporal trend

In 2021, the global age-standardized DALY rate for HIV-DS-TB was 122.54 per 100,000 population (95% UI: 96.79–149.60 per 100,000 population), for HIV-MDR-TB it was 11.48 per 100,000 population (95% UI: 5.31–20.78 per 100,000 population), and for HIV-XDR-TB it was 0.51 per 100,000 population (95% UI: 0.24–0.91 per 100,000 population. Table 4 ). In addition, the EAPC for the age-standardized DALY rates of HIV-DS-TB and HIV-MDR-TB from 1990 to 2021 were −1.74 (95% CI: −3.36, −0.09) and 4.65 (95% CI: 1.25–8.17), respectively. The EAPC for the age-standardized DALY rate of HIV-XDR-TB from 1991 to 2021 was 19.35 (95% CI: 10.93–28.42).

In 2021, the DALY numbers for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB were 9,910,866 individuals (95% UI: 7,825,966–12,110,494 individuals), 925,471 (95% UI: 413,530–1,668,293 individuals), and 42,095 individuals (95% UI: 19,698–74,093 individuals), respectively (Additional file 1 : Table S5).

In 2021, the age-standardized DALY rates for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB showed no significant differences between females and males (both P  > 0.05; Table  4 ). Compared to 1990, the age-standardized DALY rate for HIV-DS-TB in 2021 did not exhibit significant changes in either gender. However, the DALY rate for HIV-MDR-TB showed a significant upward trend in both genders (both P  < 0.05; Table  4 ).

In 2021, the highest age-standardized DALY rates for HIV-DS-TB and HIV-MDR-TB were recorded in the low SDI region, while the lowest rates were observed in the high SDI region. For HIV-XDR-TB, the highest age-standardized DALY rate was found in the high-middle SDI region, with the lowest in the high SDI region (Table  4 ). From 1990 to 2021, the age-standardized DALY rates for HIV-DS-TB and HIV-MDR-TB initially increased across the five SDI regions but began to decline thereafter. In contrast, the age-standardized DALY rate for HIV-XDR-TB has shown a very slow decline in recent years (Additional file 1 : Fig. S4 A–C).

In 2021, the highest age-standardized DALY rates for HIV-DS-TB and HIV-MDR-TB were found in Southern sub-Saharan Africa, while Eastern Europe had the highest rate for HIV-XDR-TB. In 2021, compared to 1990, regions with increased age-standardized DALY rates for HIV-DS-TB included Oceania, South Asia, East Asia, Southeast Asia, Southern sub-Saharan Africa, and high-income Asia Pacific (all P  < 0.05. Table 4 ). Conversely, Western Europe and high-income North America saw decreases in the age-standardized DALY rates for HIV-DS-TB in 2021 (both P  < 0.05. Table 4 ). The age-standardized DALY rate for HIV-MDR-TB increased in most of the 21 regions, with the largest increases observed in South Asia, Oceania, and Central Asia (all P  < 0.05. Table 4 ). Western Europe and high-income North America were the only regions where the age-standardized DALY rate for HIV-MDR-TB decreased (both P  < 0.05. Table 4 ).

In 2021, Lesotho had the highest age-standardized DALY rate for HIV-DS-TB, while Eswatini had the highest rates for both HIV-MDR-TB and HIV-XDR-TB. Compared to 1990, Pakistan showed the largest increases in age-standardized DALY rates for both HIV-DS-TB and HIV-MDR-TB in 2021 (both P  < 0.05; Additional file 1 : Table S2).

Age and gender distribution

In 2021, the age-specific incidence rate of HIV-DS-TB was higher in females than in males for the age groups 15–19, 20–24, 25–29, and 31–34 years (all P  < 0.05), with no significant differences in other age groups (all P  > 0.05). Similarly, the incidence rate of HIV-MDR-TB was higher in females than in males in the 20–24 age group ( P  < 0.05), with no significant differences in other age groups (all P  > 0.05). No significant differences in the incidence rate of HIV-XDR-TB were observed between males and females across all age groups (all P  > 0.05. Additional file 1 : Fig. S5 A–C).

In 2021, the age-specific prevalence rate of HIV-DS-TB was higher among females than males in the age groups 15–19, 20–24, 25–29, and 31–34 years, with no significant differences in other age groups (all P  > 0.05). For HIV-MDR-TB, the prevalence rate was higher in females than males in the 20–24 age group, with no significant differences in other age groups (all P  > 0.05). The prevalence rate of HIV-XDR-TB showed no significant differences between males and females across all age groups (all P  > 0.05. Additional file 1 : Fig. S6 A–C).

In 2021, the age-specific mortality rate of HIV-DS-TB was higher in females than males in the 20–24 and 25–30 age groups (all P < 0.05), with no significant differences in other age groups (all P  > 0.05). There were no significant differences in the age-specific mortality rates of HIV-MDR-TB and HIV-XDR-TB between males and females across all age groups (all P  > 0.05. Additional file 1 : Fig. S7 A–C).

In 2021, the age-specific DALY rate for HIV-DS-TB was higher in females than males in the 15–19, 20–24, and 25–29 age groups (all P  < 0.05), with no significant differences in other age groups (all P  > 0.05). The age-specific DALY rates for HIV-MDR-TB and HIV-XDR-TB showed no significant differences between males and females across all age groups (all P  > 0.05. Additional file 1 : Fig. S8 A–C).

Association between ASRs and SDI

In 2021, across 204 countries and territories, the ASIR ( r  = −0.707, P  < 0.001), ASPR ( r  = −0.720, P  < 0.001), ASMR ( r  = −0.702, P  < 0.001), and age-standardized DALY rate ( r  = −0.717, P  < 0.001) of HIV-DS-TB all demonstrated strong inverse relationship with SDI (Additional file 1 : Fig. S9 A–D). Similarly, for HIV-MDR-TB, negative correlations were observed between SDI and ASIR ( r  = −0.644, P  < 0.001), ASPR ( r  = −0.679, P  < 0.001), ASMR ( r  = −0.668, P  < 0.001), and the age-standardized DALY rate ( r  = −0.675, P  < 0.001. Additional file 1 : Fig. S10 A–D). For HIV-XDR-TB, the negative correlations with SDI were also significant across ASIR ( r  = −0.489, P  < 0.001), ASPR ( r  = −0.503, P  < 0.001), ASMR ( r  = −0.466, P  < 0.001), and the age-standardized DALY rate ( r  = −0.468, P  < 0.001. Additional file 1 : Fig.S11 A–D).

From 1990 to 2021, the ASIR ( r  = −0.731, P  < 0.001), ASPR ( r  = −0.755, P  < 0.001), ASMR ( r  = −0.697, P  < 0.001), and age-standardized DALY rate ( r  = −0.698, P  < 0.001) for HIV-DS-TB exhibited significant negative correlations with the SDI. However, these trends were not uniform across all regions. In Southern, Eastern, and Western sub-Saharan Africa, these metrics initially increased rapidly with rising SDI, reached a peak, and then declined sharply with further increases in SDI (Additional file 1 : Fig. S12A–D). For HIV-MDR-TB, similar negative correlations were observed between SDI and ASIR ( r  = −0.573, P  < 0.001), ASPR ( r  = −0.611, P  < 0.001), ASMR ( r  = −0.572, P  < 0.001), and the age-standardized DALY rate ( r  = −0.572, P  < 0.001). In Southern, Eastern, and Western sub-Saharan Africa, these indicators initially rose rapidly with increasing SDI, peaked, and then declined sharply (Additional file 1 : Fig. S13 A–D). Furthermore, when the SDI is below 0.75, the ASIR, ASPR, ASMR, and age-standardized DALY rate for HIV-XDR-TB increase gradually with rising SDI. However, once the SDI surpasses 0.80, these indicators decline rapidly with further increases in SDI (Additional file 1 : Fig.S14 A–D).

Risk factors for ASMR and age-standardized DALY rate

Globally, the primary risk factors for the ASMR and age-standardized DALY rate of HIV-DS-TB from 1990 to 2021 were (in descending order): unsafe sex, drug use, and intimate partner violence. In global, middle SDI, and low-middle SDI regions, the contribution of unsafe sex to the ASMR and age-standardized DALY rate of HIV-DS-TB has been increasing. In high SDI regions, drug use has increasingly contributed to the ASMR and age-standardized DALY rate of HIV-DS-TB (Additional file 1 : Fig. S15 A–B).

For HIV-MDR-TB, the contribution of drug use to the ASMR and age-standardized DALY rate initially increased and then declined in high-middle and high SDI regions from 1990 to 2021. However, unsafe sex remained the largest contributor to the ASMR and age-standardized DALY rate throughout this period (Additional file 1 : Fig. S15 C–D).

The primary risk factors for the ASMR and age-standardized DALY rate of HIV-XDR-TB were (in descending order): unsafe sex, drug use, and intimate partner violence. However, the contributions of these factors varied by region. In high-middle SDI regions, drug use surpassed unsafe sex as the leading contributor to the ASMR and age-standardized DALY rate. In low SDI regions, intimate partner violence contributed more to the ASMR and age-standardized DALY rate than drug use (Additional file 1 : Fig. S15 E–F).

Projecting disease burden

The study projects the ASR and EAPC for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB from 2022 to 2035. It highlights that the ASIR, ASPR, and ASMR for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB are expected to show an increasing trend globally (Table  5 . Figure  1 . Additional file 1 : Table S6).

The ASR of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB was assessed globally from 1990 to 2021, with forecasted ASR values projected for 2022 to 2035 ASR age-standardized incidence rate, HIV-DS-TB HIV-infected drug-susceptible tuberculosis, HIV-MDR-TB HIV-infected multidrug-resistant tuberculosis without extensive drug resistance, HIV-XDR-TB HIV-infected extensively drug-resistant tuberculosis

The study presents the global burden of HIV-TB co-infection based on data from the GBD 2021 database. The findings indicate that the decline in the ASIR for HIV-MDR-TB and HIV-XDR-TB is notably slow in middle-income and low-income countries, underscoring the ongoing severity of HIV-TB as a global public health issue. Furthermore, HIV-TB remains a significant and unresolved threat in sub-Saharan Africa and Asia. The study provides essential insights for policymakers and health administrators to develop targeted measures for HIV-TB prevention and control.

Early screening essential for controlling HIV-TB co-infection transmission

The study found that the ASIR of HIV-XDR-TB is decreasing in low-income regions but increasing in middle-income and high-middle-income regions. This discrepancy is attributed to the low disease detection capabilities in resource-limited areas. Early detection of infection sources and timely implementation of preventive measures are essential to interrupting the transmission of infectious diseases. HIV-TB co-infection is a significant public health concern, as the diseases exacerbate each other, increasing the risk of morbidity and mortality. Early detection and treatment of HIV-TB co-infected individuals are therefore crucial for controlling both TB and HIV/AIDS epidemics [ 5 , 6 ].

World Health Organization recommends bidirectional screening as the primary strategy for identifying HIV-TB co-infected patients. Regardless of the TB prevalence and HIV infection levels in a country or region, all TB patients should undergo HIV antibody testing, and all HIV-positive individuals should be screened for active TB. This approach aims to strengthen the prevention and control of these two severe chronic infectious diseases simultaneously [ 13 ]. Studies have shown that the proportion of TB diagnoses among newly identified PLWH is significantly higher than among previously known HIV-positive patients [ 5 , 6 ]. The finding underscores the necessity of comprehensive TB screening, particularly for newly diagnosed HIV-positive individuals.

Previously, TB screening among PLWH primarily relied on symptomatic indicators of TB, with traditional methods such as acid-fast bacilli smear microscopy, TB culture, and immunological tests (e.g., tuberculin skin test, interferon-γ release assay (IGRA)) playing a crucial role, especially in resource-limited settings [ 14 ]. However, advances in diagnostic technologies have facilitated earlier TB diagnosis in HIV-positive individuals. New methods and technologies, such as the Gene Xpert MTB/RIF molecular diagnostic technique, offer advantages like shorter detection times and simpler operation, reducing TB diagnosis time from weeks to mere hours. Next-generation sequencing provides rapid diagnostic guidance, particularly in cases of rare or multiple pathogen co-infections in PLWH [ 14 , 15 ]. In addition, certain biomarkers have demonstrated diagnostic value for HIV-TB co-infection [ 16 ]. Recently, multi-omics approaches have also provided new avenues for the early diagnosis of TB in PLWH [ 17 ]. In summary, future efforts should focus on enhancing the proactive detection of HIV-TB co-infected individuals through highly sensitive and specific screening methods and continually optimizing screening strategies. Achieving and maintaining high rates of TB testing among HIV/AIDS patients and HIV antibody testing among TB patients is essential for effectively controlling the spread of HIV-TB.

HAART, anti-TB treatment with new drugs, and public health services can significantly reduce the transmission of HIV-TB co-infection

This study found that the ASMR of HIV-DS-TB has declined rapidly in high-income regions but has decreased very slowly in low-income countries. Moreover, the ASMR for HIV-MDR-TB and HIV-XDR-TB is increasing in low-income countries and regions. This disparity is largely attributed to the accessibility of medical resources and the standardized management and treatment of patients in developed countries, in contrast to the limited accessibility of medical resources in low-income countries.

Individuals with advanced HIV/AIDS are particularly susceptible to severe illnesses and death, even after initiating HARRT, and the most common cause of death is pulmonary TB, cryptococcal meningitis, and severe bacterial infections [ 18 ]. Due to the long-term immunosuppression experienced by AIDS patients, immune reconstitution is essential to alleviate this suppression. HAART effectively suppresses viral replication, restores the damaged cellular immune function in PLWH, and achieves immune reconstitution. This treatment reduces the occurrence of opportunistic infections, delays disease progression, improves quality of life, and extends the lifespan of patients [ 18 , 19 ]. In addition, Strengthening the diagnosis of OPIs among PLWH, particularly MDR-TB and XDR-TB, is crucial. Antiretroviral and anti-TB medications should be administered continuously and immediately upon diagnosis, regardless of the environment or patient relocation. Additionally, it is imperative to address factors that hinder continuous treatment, such as stigma and discrimination in healthcare settings, remote facility locations, transportation and opportunity costs, and long waiting times [ 4 ].

The study found that the incidence of HIV-TB co-infection was highest among patients aged 15–39 years. This can be attributed to increased social activities, higher exposure, risky behaviors, and greater mobility within this age group. Interestingly, HIV-TB co-infection was more common in females than in males, contrasting with the global trend where TB is more prevalent in males [ 20 ]. Additionally, among individuals co-infected with HIV and TB, females had a higher mortality rate than males, consistent with previous studies [ 21 , 22 ]. This disparity may be due to unsafe sexual practices and intimate partner violence, which are significant factors contributing to the gender differences in HIV burden in high-prevalence countries. These findings highlight the substantial role of gender-specific health risk factors in HIV and TB co-infection and underscore the urgency and importance of targeted prevention and treatment strategies for women in these high-burden regions [ 23 ]. Failing to recognize the specific drivers of HIV-TB epidemics in different countries impedes the adaptation of the ‘END TB Strategy’ at the national level. The results of this analysis can inform the design of future studies aimed at identifying country-specific drivers of TB using individual-level data [ 23 ].

In sub-Saharan Africa, the estimated HIV incidence among men who have sex with men (MSM) in 2020 was nearly 5 cases per 100 person-years, which is 27 to 150 times higher than that of the general adult male population (aged 15 and above) in the region [ 24 ]. Young people from key populations are particularly vulnerable, struggling to maintain health and safety in environments characterized by stigma, discrimination, harassment, punitive laws, and social taboos [ 6 , 25 ]. In the Asia–Pacific region, HIV infection rates among young MSM have more than doubled in Indonesia (from 6% in 2011 to 13% in 2019), nearly quadrupled in Malaysia (from 6% in 2012 to 15% in 2022), and almost quadrupled in Vietnam (from 3% in 2011 to 11% in 2022) [ 26 ]. The increase in new HIV cases, coupled with frequent social activities among adolescents, insufficient HIV and TB diagnostic capacities, and inadequate health services and medical supplies, has led to a rise in HIV-TB co-infection incidence and mortality in Southeast Asian and African countries.

The study found that in low- and middle-income regions such as Africa, the Middle East, and South Asia, the incidence and mortality rates of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB are decreasing very slowly. Several factors contribute to this issue. Poverty, malnutrition, overcrowded living conditions, and inadequate healthcare infrastructure are widespread in these regions, facilitating the spread of TB [ 27 ]. Additionally, insufficient monitoring leads to over 50% of newly diagnosed HIV infections being at an advanced AIDS stage. This is driven by stigma and discrimination, side effects of medications, affordability issues, and unreliable healthcare services [ 28 , 29 ]. Approximately one-quarter of PLWH discontinue HAART within six months of initiation, and over one-fifth of those on HAART do not achieve viral suppression [ 30 ]. In low- and lower-middle-income regions, PLWH have significantly lower CD4 + T-cell counts post-HAART compared to those in upper-middle and high-income countries, contributing to increased OPIs.

In many regions with a high prevalence of TB and HIV, patients face limited access to quality healthcare, diagnostic services, and effective treatments. This scarcity of medical services leads to delays in diagnosis and treatment, exacerbating the spread of TB, including drug-resistant strains, and increasing patient mortality [ 31 ]. Furthermore, in areas with inadequate treatment supervision, the overuse or misuse of TB medications contributes to the emergence of drug-resistant TB strains, accelerating the spread of the disease. Insufficient public health education leads to misunderstandings about TB, delays in seeking medical care, and poor adherence to treatment regimens. These factors accelerate the spread of Mtb strains, increasing the incidence and mortality of HIV-TB co-infection [ 32 , 33 ]. Insufficient public health education leads to misunderstandings about TB, delays in seeking medical care, and poor adherence to treatment regimens. These factors accelerate the Mtb transmission, increasing the incidence and mortality of HIV-TB co-infection [ 32 , 33 ].

Control strategies and measures derived from the One Health approach can curb HIV-TB transmission

In the new era, preventing and controlling the HIV-TB epidemic necessitates a One Health approach integrating medical, social, economic, and environmental interventions [ 34 , 35 , 36 , 37 ]. Essential strategies include coordinated care, routine screening, and holistic treatment plans. Strengthening healthcare infrastructure through improved accessibility, capacity building, and efficient supply chain management will enhance care delivery. Public health policies must prioritize comprehensive national strategies, adequate funding, and robust surveillance systems.

In controlling HIV-TB co-infection, community engagement through awareness campaigns, the deployment of community health workers, and stigma reduction programs is essential to enhance public understanding and support. Addressing social determinants of health, such as poverty alleviation, improved living conditions, and increased education and employment opportunities, is crucial. Additionally, research and innovation should focus on vaccine development, new treatment regimens, and implementation science. International collaboration through global partnerships, funding mechanisms, and technical assistance can bolster national and regional efforts [ 34 , 35 , 36 , 37 , 38 ]. This multifaceted approach aims to reduce the incidence and improve outcomes of HIV-TB co-infection.

Several limitations of this study need to be acknowledged. First, the inherent limitations of the GBD 2021 study methodology affect the accuracy and completeness of model estimates. Missing HIV and TB data from some countries and regions significantly impact these estimates. Additionally, variations in data quality, accuracy, and comparability can introduce biases [ 9 , 10 ]. Data on the incidence, prevalence, mortality, and DALYs of HIV-MDR-TB and HIV-XDR-TB are insufficient in some regions, particularly for HIV-XDR-TB, as surveillance for XDR-TB only began in 1991 in a few countries, with many lacking the capacity for such surveillance, leading to data gaps [ 4 ]. Second, the GBD 2021 database relies on model fitting rather than real-world data, potentially resulting in overestimation or underestimation. Third, the rates for HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB in 204 countries and territories were calculated based on a globally standardized population to ensure comparability. However, these standardized rates may not accurately represent the true disease burden of HIV-TB co-infection in each country. Fourth, EAPC estimates the average trend over the past three decades without accounting for the uncertainty of these rates. While EAPC is accurate under linear trends, it can be misleading when rates exhibit non-linear trends, such as U-shaped, V-shaped, or L-shaped patterns. Fifth, a comprehensive assessment of the disease burden should consider broader economic, familial, and social impacts. Sixth, the GBD 2021 data lack comprehensive information on overall HIV-TB co-infection, hindering a holistic assessment of the situation. Future studies should employ multidimensional analyses to enhance the accuracy and robustness of the results.

The findings indicate a critical need for enhanced diagnostic and treatment strategies in low- and middle-income countries where the burden of HIV-TB co-infection remains high. Strengthening healthcare infrastructure, increasing accessibility to quality medical care, and improving public health education are pivotal in combating the dual epidemic. Moreover, the development of new screening technologies and comprehensive management plans tailored to high-burden regions could significantly reduce the incidence and mortality associated with HIV-TB co-infection. Addressing social determinants of health and ensuring sustained political and financial commitment are crucial for achieving long-term control and eventual eradication of HIV and TB.

Availability of data and materials

The datasets analysed during the current study are available at http://ghdx.healthdata.org/gbd-results-tool .

Abbreviations

Acquired immune deficiency syndrome

Age-standardized mortality rate

Age-standardized incidence rate

Age-standardized prevalence rate

Age-standardized rate

Bayesian age-period-cohort

Confidence interval

Disability-adjusted life years

Disease-model-Bayesian meta-regression

Drug-susceptible tuberculosis

Annual percentage changes

Guidelines for Accurate and Transparent Health Estimates Reporting

Global Burden of Disease

Highly active anti-retroviral therapy

Human immunodeficiency virus

HIV-infected drug-susceptible tuberculosis

HIV-infected multidrug-resistant tuberculosis without extensive drug resistance

HIV-infected extensively drug-resistant tuberculosis

Institute for Health Metrics and Evaluation

International Classification of Diseases

Interferon-γ release assay

Multidrug-resistant tuberculosis without extensive drug resistance

Bayesian priors, regularisation, and trimming

Men who have sex with men

Mycobacterium tuberculosis

Opportunistic infections

Person living with HIV

Sociodemographic Index

• Tuberculosis

Uncertainty interval

GBD 2021 Tuberculosis Collaborators. Global, regional, and national age-specific progress towards the 2020 milestones of the WHO End TB Strategy: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Infect Dis. 2024;24:698–725.

Article   Google Scholar  

Zhang SX, Kang FY, Chen JX, Tian LG, Geng LL. Risk factors for blastocystis infection in HIV/AIDS patients with highly active antiretroviral therapy in Southwest China. Infect Dis Poverty. 2019;8:89.

Article   PubMed   PubMed Central   Google Scholar  

Zhang SX, Wang JC, Li ZW, Zheng JX, Zhou WT, Yang GB, et al. Impact factors of Blastocystis hominis infection in persons living with human immunodeficiency virus: a large-scale, multi-center observational study from China. Infect Dis Poverty. 2023;12:82.

Wang Y, Jing W, Liu J, Liu M. Global trends, regional differences and age distribution for the incidence of HIV and tuberculosis co-infection from 1990 to 2019: results from the global burden of disease study 2019. Infect Dis. 2022;54:773–83.

Article   CAS   Google Scholar  

World Health Organization. Global tuberculosis report. 2023. https://www.who.int/publications/i/item/9789240083851 . Accessed 30 May 2024.

The Joint United Nations Programme on HIV/AIDS (UNAIDS). 2023 UNAIDS GLOBAL AIDS UPDAT. https://thepath.unaids.org . Accessed 30 May 2024.

Bell LCK, Noursadeghi M. Pathogenesis of HIV-1 and mycobacterium tuberculosis co-infection. Nat Rev Microbiol. 2018;16:80–90.

Article   CAS   PubMed   Google Scholar  

Deffur A, Mulder NJ, Wilkinson RJ. Co-infection with Mycobacterium tuberculosis and human immunodeficiency virus: an overview and motivation for systems approaches. Pathog Dis. 2013;69:101–13.

GBD 2021 Risk Factors Collaborators. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403:2162–203.

GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403:2133–61.

Zhang T, Sun L, Yin X, Chen H, Yang L, Yang X. Burden of drug use disorders in the United States from 1990 to 2021 and its projection until 2035: results from the GBD study. BMC Public Health. 2024;24:1639.

Wang W, Wang Y, Wang F, Chen H, Qin X, Yang L, et al. Notable dysthymia: evolving trends of major depressive disorders and dysthymia in China from 1990 to 2019, and projections until 2030. BMC Public Health. 2024;24:1585.

Qi CC, Xu LR, Zhao CJ, Zhang HY, Li QY, Liu MJ, et al. Prevalence and risk factors of tuberculosis among people living with HIV/AIDS in China: a systematic review and meta-analysis. BMC Infect Dis. 2023;23:584.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Yu Q, Guo J, Gong F. Construction and validation of a diagnostic scoring system for predicting active pulmonary tuberculosis in patients with positive T-SPOT based on indicators associated with coagulation and inflammation: a retrospective cross-sectional study. Infect Drug Resist. 2023;16:5755–64.

Dai Y, Cai Y, Wang X, Zhu J, Liu X, Liu H, et al. Autoantibody-mediated erythrophagocytosis increases tuberculosis susceptibility in HIV patients. mBio. 2020;11:e03246-19.

CAS   PubMed   PubMed Central   Google Scholar  

Rambaran S, Maseko TG, Lewis L, Hassan-Moosa R, Archary D, Ngcapu S, et al. Blood monocyte and dendritic cell profiles among people living with HIV with mycobacterium tuberculosis co-infection. BMC Immunol. 2023;24:21.

Liebenberg C, Luies L, Williams AA. Metabolomics as a tool to investigate HIV/TB co-infection. Front Mol Biosci. 2021;8:692823.

Ford N, Chiller T. CD4 cell count: a critical tool in the human immunodeficiency virus response. Clin Infect Dis. 2022;74:1360–1.

Kendall MA, Lalloo U, Fletcher CV, Wu X, Podany AT, Cardoso SW, et al. Safety and pharmacokinetics of double-dose lopinavir/ritonavir + rifampin versus lopinavir/ritonavir + daily rifabutin for treatment of human immunodeficiency virus-tuberculosis coinfection. Clin Infect Dis. 2021;73:706–15.

GBD Tuberculosis Collaborators. Global, regional, and national burden of tuberculosis, 1990–2016: results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 Study. Lancet Infect Dis. 2018;18:1329–49.

GBD 2019 Tuberculosis Collaborators. Global, regional, and national sex differences in the global burden of tuberculosis by HIV status, 1990–2019: results from the Global Burden of Disease Study 2019. Lancet Infect Dis. 2022;22:222–41.

GBD 2019 HIV Collaborators. Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019. Lancet HIV. 2021;8:e633–51.

Preuc C, Humayun M, Yang Z. Varied trends of tuberculosis and HIV dual epidemics among different countries during 2000–2020: lessons from an ecological time-trend study of 9 countries. Infect Dis. 2023;55:567–75.

Stannah J, Soni N, Lam JKS, Giguère K, Mitchell KM, Kronfli N, et al. Trends in HIV testing, the treatment cascade, and HIV incidence among men who have sex with men in Africa: a systematic review and meta-analysis. Lancet HIV. 2023;10:e528–42.

Baggaley R, Armstrong A, Dodd Z, Ngoksin E, Krug A. Young key populations and HIV: a special emphasis and consideration in the new WHO consolidated guidelines on HIV prevention, diagnosis, treatment and care for key populations. J Int AIDS Soc. 2015;18:19438.

The Joint United Nations Programme on HIV/AIDS (UNAIDS). Putting young key populations first: HIV and young people from key populations in the Asia and Pacific region. 2022. https://thepath.unaids.org . Accessed 30 May 2024.

Cadmus SI, Akinseye VO, Taiwo BO, Pinelli EO, van Soolingen D, Rhodes SG. Interactions between helminths and tuberculosis infections: implications for tuberculosis diagnosis and vaccination in Africa. PLoS Negl Trop Dis. 2020;14(6):e0008069.

Kranzer K, Ford N. Unstructured treatment interruption of antiretroviral therapy in clinical practice: a systematic review. Trop Med Int Health. 2011;16:1297–313.

Article   PubMed   Google Scholar  

Galjour J, Havik PJ, Aaby P, Rodrigues A, Hoemeke L, Deml MJ, et al. Chronic political instability and HIV/AIDS response in Guinea-Bissau: a qualitative study. Infect Dis Poverty. 2021;10:68.

Carmona S, Bor J, Nattey C, Maughan-Brown B, Maskew M, Fox MP, et al. Persistent high burden of advanced HIV disease among patients seeking care in South Africa’s National HIV program: data from a nationwide laboratory cohort. Clin Infect Dis. 2018;66:S111–7.

Cords O, Martinez L, Warren JL, O’Marr JM, Walter KS, Cohen T, et al. Incidence and prevalence of tuberculosis in incarcerated populations: a systematic review and meta-analysis. Lancet Public Health. 2021;6:e300–8.

Zhang S, Qiu L, Wu D, Zhang S, Pan C, Li C, Xiao H, Huang F, Wang H, Jiang F, Zhang H, Zheng P, Lu Z. Predictors for treatment outcomes in patients with multi-drug resistant tuberculosis - China, 2018–2020. China CDC Wkly. 2022;4:907–11.

PubMed   PubMed Central   Google Scholar  

Lu ZH, Yang M, Pan CH, Zheng PY, Zhang SX. Multi-modal deep learning based on multi-dimensional and multi-level temporal data can enhance the prognostic prediction for multi-drug resistant pulmonary tuberculosis patients. SOH. 2022;01:100004.

Google Scholar  

Zhang Q, Liu J, Han L, Li X, Zhang C, Guo Z, et al. How far has the globe gone in achieving One Health? Current evidence and policy implications based on global One Health index. SOH. 2024;03:100064.

Morris R, Wang S. Building a pathway to One Health surveillance and response in Asian countries. SOH. 2024;03:100067.

Huang L, He J, Zhang C, Liu J, Guo Z, Lv S, et al. China’s One Health governance system: the framework and its application. SOH. 2023;02:100039.

Chen J, He J, Bergquist R. Challenges and response to pandemics as seen in a One Health perspective. SOH. 2022;01:100010.

Chen Y, Chen W, Cheng Z, Chen Y, Li M, Ma L, et al. Global burden of HIV-negative multidrug- and extensively drug-resistant tuberculosis based on Global Burden of Disease Study 2021. SOH. 2024;3:100072.

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Acknowledgements

The authors appreciate the works by the GBD Study 2021 collaborators.

The study was supported by the fund of the Shanghai Natural Science Foundation (23ZR1464000, 23ZR1463900), the International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion from Shanghai Municipality Government (21410750200), Medical Innovation Research Special Project of the Shanghai 2021 "Science and Technology Innovation Action Plan"(21Y11922500, 21Y11922400), the Three-year Action Plan for Promoting Clinical Skills and Innovation Ability of Municipal Hospitals (SHDC2022CRS039), the Talent Fund of Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine (LH001.007), and the Bill & Melinda Gates foundation. The Funders had no role in the study design or in the collection, analysis, and interpretation of the data, writing of the report, or decision to submit the article for publication.

Author information

Shun-Xian Zhang and Ji-Chun Wang have contributed equally to this work.

Authors and Affiliations

Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China

Shun-Xian Zhang, Yu Wang, Xiao-Jie Hu, Ming Yang, Zhen-Hui Lu & Shao-Yan Zhang

National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, National Center for International Research on Tropical Diseases; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Shanghai, 200025, China

Shun-Xian Zhang, Shan Lv, Lei Duan, Yan Lu, Li-Guang Tian, Mu-Xin Chen, Qin Liu, Fan-Na Wei & Shi-Zhu Li

Department of Science and Technology, Chinese Center for Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, 102206, China

Ji-Chun Wang & Jian Yang

School of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China

Xin-Yu Feng & Jin-Xin Zheng

Gansu Provincial Center for Disease Control and Prevention, Lanzhou, 730000, China

Guo-Bing Yang & Yong-Jun Li

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Contributions

JC-W and SZ-L conceived, designed the manuscript. YW, XJ-H, MY, ZH-L and SY-Z did a literature search and download the data. JY, SL, LD, YL, LG-T, MX-C, QL, FN-W, GB-Y and YJ-L analysis and interpretation, compiled tables and figures, XY-F, SX-Z and JX-Z drafted the manuscript, proofed and interpreted the report. SZ-Z and JC-W contributed equally to this paper. SZ-L and JX-Z are the corresponding authors. All authors participated in data analysis, interpretation, discussion and writing of the manuscript, and all authors read and approved the final version of the paper.

Corresponding authors

Correspondence to Shi-Zhu Li or Jin-Xin Zheng .

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Supplementary Information

40249_2024_1230_moesm1_esm.docx.

Supplementary material 1. Contains materials used throughout the study. Table S1: The number of incidence cases of HIV, HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB individuals in 2021, and percentage change of the number of incidence case were analyzed across GBD regions. Table S2: Age-standardized rates of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB in 2021, and percentage change of age-standardized rates in 204 countries and territories. Table S3: The number of prevalence cases of HIV, HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB individuals in 2021, and percentage change of number of prevalence cases were analyzed across GBD regions. Table S4: The number of death cases of HIV, HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB individuals in 2021, and percentage change of number of death cases were analyzed across GBD regions. Table S5: The number of DALY cases of HIV, HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB individuals in 2021, and percentage change of the number of DALY cases were analyzed across GBD regions. Table S6: Predicted age-standardized rates of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB spanning 2022–2035, based on the Bayesian Age-Period-Cohort Model. Fig. S1: The trends in the age-standardized incidence rate for HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB varied across the five SDI regions. Fig. S2: The trends in the age-standardized prevalence rate for HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB varied across the five SDI regions. Fig. S3: The trends in the age-standardized mortality rate for HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB varied across the five SDI regions. Fig. S4: The trends in the age-standardized DALY rates for HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB varied across the five SDI regions. Fig. S5: The specific incidence rate of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB showed notable differences across age and gender distributions in 2021. Fig. S6: The specific prevalence rate of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB showed notable differences across age and gender distributions in 2021. Fig. S7: The specific mortality rate of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB showed notable differences across age and gender distributions in 2021. Fig. S8: The specific age-standardized DALY rate of HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB showed notable differences across age and gender distributions in 2021. Fig. S9: The association between the SDI and the age-standardized incidence rate, mortality rate, and DALY rate of HIV-DS-TB across 204 countries and regions in 2021. Fig. S10: The association between the SDI and the age-standardized incidence rate, death rate, and DALY rate of HIV-MDR-TB across 204 countries and regions in 2021. Fig. S11: The association between the SDI and the age-standardized incidence rate, death rate, and DALY rate of HIV-XDR-TB across 204 countries and regions in 2021. Fig.S12: The association between the age-standardized incidence rate, prevalence rate, mortality rate, and DALY rate of HIV-DS-TB with the SDI from 1990 to 2021. Fig. S13: The association between the age-standardized incidence rate, prevalence rate, mortality rate, and DALY rate of HIV-MDR-TB with the SDI from 1990 to 2021. Fig. S14: The association between the age-standardized incidence rate, prevalence rate, mortality rate, and DALY rate of HIV-XDR-TB with the SDI from 1990 to 2021. Fig. S15: The association between risk factors and the age-standardized mortality rate, age-standardized DALY rate of HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB from 1990 to 2021.

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Zhang, SX., Wang, JC., Yang, J. et al. Epidemiological features and temporal trends of the co-infection between HIV and tuberculosis, 1990–2021: findings from the Global Burden of Disease Study 2021. Infect Dis Poverty 13 , 59 (2024). https://doi.org/10.1186/s40249-024-01230-3

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Epidemiology and Transmission Dynamics of Infectious Diseases and Control Measures

Sukhyun ryu.

1 Department of Preventive Medicine, Konyang University College of Medicine, Daejeon 35365, Republic of Korea

June Young Chun

2 Department of Internal Medicine, National Cancer Center, Goyang 10408, Republic of Korea

3 Department of Applied Mathematics, Kyung Hee University, Yongin 17104, Republic of Korea

Daesung Yoo

4 Veterinary Epidemiology Division, Animal and Plant Quarantine Agency, Gimcheon 39660, Republic of Korea

Yongdai Kim

5 Department of Statistics, Seoul National University, Seoul 08826, Republic of Korea

Sheikh Taslim Ali

6 WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

7 Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, Hong Kong, China

Byung Chul Chun

8 Department of Preventive Medicine, Korea University College of Medicine, Seoul 02841, Republic of Korea

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The epidemiology and transmission dynamics of infectious diseases must be understood at the individual and community levels to improve public health decision-making for real-time and integrated community-based control strategies. Herein, we explore the epidemiological characteristics for assessing the impact of public health interventions in the community setting and their applications. Computational statistical methods could advance research on infectious disease epidemiology and accumulate scientific evidence of the potential impacts of pharmaceutical/nonpharmaceutical measures to mitigate or control infectious diseases in the community. Novel public health threats from emerging zoonotic infectious diseases are urgent issues. Given these direct and indirect mitigating impacts at various levels to different infectious diseases and their burdens, we must consider an integrated assessment approach, ‘One Health’, to understand the dynamics and control of infectious diseases.

1. Introduction

Infectious diseases, including seasonal and emerging respiratory virus infections such as influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have caused several epidemics and pandemics and significantly disrupted daily life. During the coronavirus 2019 (COVID-19) pandemic, we observed that public health and social measures (PHSMs) reduced the burden of the pandemic and other directly transmitted respiratory virus infections in many countries by reducing their transmissibility and susceptibility in the community [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Therefore, to reduce the overall burden of respiratory infections in the community, it is important to consider the direct and indirect impacts of PHSMs on diseases with similar transmission characteristics. Infectious disease epidemiology, a branch of epidemiology that studies why infectious diseases emerge and how they spread, can provide helpful information on developing and designing intervention strategies in different settings, from households (or small settings) to communities (or large settings). Such studies are often conducted by using and assimilating the syndromic, virological, and digital data, obtained from outbreak investigations, ongoing surveillance, and seroprevalence surveys. This data is enhanced with the advancement of statistical methods, mathematical modeling, and efficient computational tools. Herein, we explore an overview on the research scopes of developing epidemiological tools and possible applications for assessing the impact of PHSMs in the community and for infectious disease control with the necessity of the One Health paradigm, rather than review the specific technical details of methods.

2. Epidemiological Data Assimilation and Augmentation

The true epi-curves of any infectious disease are always challenging at the community level. The overall burden of these directly transmitted infectious diseases in the community starts with the infections, healthcare-seeking, hospitalization, severity (admission to the intensive care unit), and mortality from each disease ( Figure 1 ). The syndromic information on the morbidity and mortality of these diseases is not free from biases and is often underestimated. We can only observe the tip of the ‘iceberg’ of total infections in the community. These data are the basis of epidemiological analyses, and the outcomes are highly data-driven. The improvements in data observation, surveillance systems, integration, and assimilation techniques, and data retrieval and reconstruction are crucial for understanding disease characteristics and transmission dynamics [ 3 , 8 , 9 , 10 , 11 ]. Therefore, correctly estimating the proportion of asymptomatic infections [ 12 ], identifying the case definitions over time [ 9 ], and nowcasting true infections [ 3 , 8 , 11 ] could lead to real-time epi-curves for any disease.

The burden pyramid of infectious disease and epidemiological severity parameters. The clinical spectrum of infectious diseases and the possible surveillance system at each level. Note: SARI = severe acute respiratory infection, IFR = infection fatality rate, sCFR = symptomatic cases fatality rate, sCHR = symptomatic hospitalization rate, HFR = hospitalization fatality rate.

3. Inferring Epidemiological Parameters and Assessing the Impact of PHSMs

Public health authorities often monitor the severity and status of an epidemic by assessing the transmission activity or/and the intensity (i.e., transmissibility) across the epidemic. For example, PHSMs, such as contract tracing, case isolations, hand hygiene, wearing a face mask, and social distancing, could affect people’s behavior and change the transmission activity or transmissibility of the underlining virus circulation in the community. The estimates of epidemiological parameters including the generation interval, effective reproductive number ( R t ), and superspreading potential ( k ) could reflect the transmission activity or the transmissibility of an epidemic and are used to infer the impact of these PHSMs ( Figure 2 ).

Epidemiological parameters to assess the impact of public health and social measures. ( A ) Epidemic curve with the transmission chain of the infectious diseases (a measure of transmission activity). ( B ) Daily effective reproductive number ( R t ) of the infectious diseases (a measure of transmissibility). ( C ) Serial interval distribution of the infectious diseases in two different epidemic periods. ( D ) Risk for superspreading events for infectious diseases during two different epidemic periods. Note: presented here are the outcomes of COVID-19 in South Korea, modified from [ 13 , 14 ].

The time-varying instantaneous reproduction number ( R t ) defines the average number of secondary cases generated from a typical primary case at time t ( Figure 2 B). The transmissibility of infectious diseases changes over time and is driven by several extrinsic factors, such as PHSMs and vaccination. Public health authorities widely use R t to assess the effectiveness of PHSMs and to inform their policy [ 15 , 16 ].

The generation interval, the time between the infection events in successive cases in a transmission chain ( Figure 3 ), is essential to estimating R t . However, the generation interval is difficult to infer with syndromic or clinical data since the infection process often goes unobserved. Therefore, it is usually approximated using a clinical measure, serial interval, the time between illness onset in successive cases in a transmission chain [ 15 , 17 ] ( Figure 2 C). The serial interval distribution is usually kept constant across the epidemic for a specific infectious disease, but recent studies report that it might change over time, accounting for the changes in PHSMs, such as case isolation and case profiles [ 17 , 18 ]. The time-varying estimate of effective serial interval distributions could improve the estimates of real-time R t and reduce the biases in using constant serial intervals over epidemics. This would better elucidate the effectiveness of PHSMs against disease transmission.

Schematic illustration of the generation interval and serial interval under biological and clinical processes. The latent period is the interval between the time of infection and when an individual becomes infectious, and the infectious period is the length of the time during which an individual can transmit a pathogen. The incubation period is the interval between the time of infection and the illness onset. The generation interval is the time between the infection events in successive cases in a transmission chain (i.e., between infector and infectee), and the serial interval is the time between the illness onset from infector to infectee.

However, the R t and effective serial interval distribution do not reflect the individual variation of infectiousness. Therefore, the dispersion parameter ( k ) can be used to demonstrate the individual level of heterogeneity in transmission ( Figure 2 D). For example, a smaller k indicates the negative binomial distribution has a longer tail, meaning the individual variation in secondary cases is higher and the epidemic is more likely to be a superspreading event [ 19 , 20 , 21 ]. Furthermore, the estimate of the dispersion parameter may change over time due to the impact of PHSMs. Therefore, the time-varying dispersion parameter ( k t ) is proposed to account for the temporal changes in transmission heterogeneity at the individual level.

Post-COVID, many countries are relaxing PHSMs. However, there remains a significant knowledge gap regarding the association between the relaxation of PHSMs and changes in these epidemiological parameters [ 22 ]. Some studies reported that these parameters could potentially be reshaped for COVID-19 variants and subvariants [ 13 , 23 ] and would have an impact on other infectious disease dynamics. This could lead to an increase in the infection burden for future infectious diseases in different countries and settings [ 4 , 24 , 25 ].

4. An Improved Statistical Model with Age-Varying and Multi-Strain Susceptibility of Infections

During the COVID-19 pandemic, the pre-symptomatic transmission potential of SARS-CoV-2 hindered effective PHSMs. It is difficult to identify the transmission onset time as it is problematic to precisely determine who is infected and when. However, detailed contact-tracing exercises allow us to reconstruct transmission chains based on onset-time information, possibly using the infection timing with known potential exposure dates. Combining this data with known information regarding infector and infectee symptom onset, the incubation period and serial interval distributions can be inferred ( Figure 3 ).

Infectious disease transmission depends on the number of infectious and susceptible individuals in the population and their effective contacts. For example, the stochastic susceptible–infectious–recovered compartmental model assumes a homogenous population and indicates the high likelihood of effective contact among identical age groups. All individuals in the population are not equally susceptible to infection. Therefore, information on age-specific infection, the probability of infection, and the contact matrix could be used to develop an age-structured compartment model [ 26 , 27 ]. For instance, early in the COVID-19 pandemic in 2020, few cases were reported among children [ 26 ], and an age-varying transmission matrix of infector–infectee pairs was observed (i.e., children had a higher probability of transmission to or from adults) [ 14 ]. Since public health authorities in many countries have reported an age-stratified number of COVID-19 cases daily, the age-specific force of infection (i.e., age-specific susceptibility of infection) could be estimated using the Bayesian inference method with the Markov chain Monte Carlo procedure [ 26 , 28 , 29 ].

Thus, the age-specific COVID-19 vaccination uptake and the effectiveness of vaccination can be applied to the susceptible population in an age-structured compartment model for COVID-19 [ 28 , 29 ]. In addition, many countries have changed their COVID-19 surveillance from an active to a passive scheme, and many COVID-19 cases have not been reported due to changes in health-seeking behaviors and a lack of contact tracing ( Figure 1 ). Therefore, to identify the age-varying susceptibility of SARS-CoV-2 infection, seroprevalence studies have been conducted in many locations during the Omicron wave of SARS-CoV-2. In addition, a community longitudinal seroprevalence survey may improve epidemic modeling and pharmaceutical intervention strategies by elucidating the immune dynamic of SARS-CoV-2 at the individual and population levels.

Post-COVID-19, the co-circulation of multiple viruses in the community could address several crucial questions on cross-protection from natural infections due to similar viruses, the seasonality of multiple pathogens, and their integrated burden and impact on healthcare facilities. These create opportunities to develop a holistic quantitative approach.

5. Optimization of PHSMs Using Artificial Intelligence

The design of optimal intervention strategies is crucial to respond to epidemics or pandemics in real time. The optimization theory under optimal control problems is well-established [ 30 , 31 ]. However, optimization theory for individual-based models (or network models) has a relatively short history and is currently under development. Game theory can provide good methods for the optimization of individual-based models, while dynamic or geometric programming allows for the optimization of network-based models. The optimization problems (optimal control or dynamic programming) often require pre-determined information (priors) [ 30 , 31 ], and optimization frameworks using artificial intelligence (AI) provide an alternative approach to answering epidemiological questions. For example, it can be used to identify when to screen or treat infected individuals in a resource-limited setting and various infectious diseases (foot and mouth disease in animal infectious diseases [ 32 ] and human influenza in 2009 in England [ 33 ]).

AI-based research is a growing field, and has been applied in many sequential decision-making problems, such as playing Go Robot [ 34 ]. The AI-based reinforcement framework consists of two main entities, a policymaker (or an actor) and a dynamic model of disease transmission (or the environment). The actor makes a decision based on the contact network structure and information regarding the dynamically changing epidemiological characteristics of the population (susceptible–exposed–infectious–recovered). Reinforcement learning utilizes the past–present–future states and reveals inherited or embedded information. These features can provide an innovative and alternative framework for understanding the transmission dynamics of infectious diseases.

6. Importance of One Health for Future Zoonotic Infectious Disease Epidemics or Pandemics

Over the last decade, two coronavirus diseases, Middle East respiratory syndrome coronavirus and SARS-CoV-2, have affected the global population. It has been well documented that these zoonotic infectious diseases are transmitted from animal populations (e.g., wildlife and livestock) to susceptible humans or vice versa by direct or indirect contact [ 35 ]. This contact is more frequent owing to humans’ forceful encroachment into natural spaces due to the drastic growth of the human population [ 36 ] and traveling [ 37 ]. Moreover, climate and landscape changes have reshaped the interconnectivity between animals and humans, which has induced either the competition for or the allocation of natural resources [ 38 ]. This type of change in interconnectivity consistently occurs between wild and farmed animals because livestock are highly dependent on humans for breeding and feeding. In countries such as South Korea, many domestic ducks have acquired avian influenza from wildfowl [ 39 , 40 ]. Proactive surveillance for avian influenza in both wild and farmed birds have been conducted by animal health authorities. Furthermore, early detection and the depopulation of infected poultry flocks and the serosurveillance of farm workers have been conducted to prevent the possible spread of viruses from animals to humans (i.e., spillover) [ 41 ]. Therefore, an integrated and holistic approach such as ‘One Health’ could improve public health decision-making policies for community-based mitigation and intervention strategies against these infectious diseases [ 37 ].

7. Conclusions

A critical strategic breakthrough of PHSMs from a One Health perspective is needed to mitigate or control future infectious disease epidemics and pandemics. Continuous improvements in community-based epidemiological modeling and applied computational methods are required to provide scientific evidence to improve public health decision-making policies.

Acknowledgments

We thank Achangwa Chiara and Suhyeon Jang at Onehealth Lab, Department of Preventive Medicine, Konyang University, for technical assistance.

Funding Statement

This work was supported by the National Research Foundation of Korea by the Ministry of Education (grant number NRF-2020R1I1A3066471), the Korean government (MSIT) (grant number 2020R1A2C3A01003550) and (MSIP) (grant number NRF-2021R1A2B5B01002611), and the Health and Medical Research Fund (project no. 20190712), AIR@InnoHK, administered by Innovation and Technology Commission.

Author Contributions

Conceptualization, S.R., J.Y.C., S.L., D.Y., Y.K., S.T.A. and B.C.C.; writing—original draft preparation, S.R., J.Y.C., S.L., D.Y. and S.T.A.; writing—review and editing, S.R., J.Y.C., S.L., D.Y. and S.T.A.; visualization, S.R.; supervision, S.R. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

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Authors Sukhyun Ryu, Sheikh Taslim Ali, and Byung Chul Chun are the editors of Viruses . This article was reviewed and handled by an independent editor and the authors were not involved in the editorial decision. The authors declare no conflict of interest.

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Study on health education methods based on rural residents' infectious disease-specific health literacy in Shandong, China

Affiliations.

• 1 College of Public Health, Shandong Second Medical University, Weifang, Shandong, China.
• 2 Dezhou Hospital of Traditional Chinese Medicine, Dezhou, Shandong, China.
• 3 Department of Histology and Embryology, Shandong Second Medical University, Weifang, Shandong, China.
• 4 Department of Epidemiology, Shandong Second Medical University, Weifang, Shandong, China.
• PMID: 39121244
• PMCID: PMC11315526
• DOI: 10.1097/MD.0000000000039292

Adequate infectious disease-specific health literacy (IDSHL) is of benefit to residents in dealing with infectious diseases. This study aimed to investigate the methods by which residents acquire knowledge about infectious disease prevention and control (IDPC knowledge) so as to find effective health education methods used to improve residents' IDSHL level. In 2022, a cross-sectional study was conducted in Shandong Province, China. Participants were recruited from rural areas by multistage sampling. The IDPC knowledge cognitive questionnaire, as a reliable and valid tool, was applied to data collection and to investigate the participants' IDPC knowledge. Chi-square analysis was utilized to analyze the differences in possession level of IDSHL between different subgroups. The relationship between demographic factors and methods to acquire IDPC knowledge was also examined by chi-square analysis. The possession rate of adequate IDSHL among the total 2283 participants was 31.80%. There was a significant association between IDSHL level and socio-demographic factors, including age (P < .001), sex (P = .02), education (P < .001), occupation (P < .001), annual family income (P < .001), whether to use smartphones (P < .001), whether to browse WeChat on smartphones (P < .001), and whether to browse apps on smartphones except WeChat (P < .001). Univariate analysis showed that whether to adopt specific methods, including television (P = .02), WeChat on smartphones (P < .001), propaganda of infectious disease prevention and control (P < .001), and doctor's advice (P < .001) to acquire IDPC knowledge had significant associations with IDSHL level. Age (P < .001), education (P < .05), occupation (P < .05), and annual family income (P < .01) were associated with methods to acquire IDPC knowledge. The rural residents' adequate IDSHL in Shandong Province, China, was not optimistic. The combination of traditional methods and Internet publicity platforms should take greater responsibility for IDSHL health education among rural populations.

Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.

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The authors have no conflicts of interest to disclose.

Adoption percentage of acquiring knowledge…

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Guest Essay

We Now Have a Chance to Stop the Most Deadly Infectious Disease — if We Act

By Atul Gawande

Dr. Gawande is the assistant administrator for global health at the United States Agency for International Development.

This year, I visited a sprawling homeless shelter in Delhi, India, where tuberculosis was rampant. I met a boy whose parents were day laborers. Soon after their arrival there, when the boy was 6, he and his older sister became sick. They weren’t diagnosed with TB until they were critically ill. After two years of treatment, the boy survived, but his sister died, he said. It had been too little, too late for her.

Humanity has had the tools to diagnose, treat and prevent TB for decades. Because of that, this airborne bacterial respiratory disease, once the cause of about 25 percent of all deaths in the United States, is no longer a widespread threat to public health in wealthy countries. But that’s far from true in lower-income countries. While international public health efforts have cut global TB case rates by a quarter and death rates by half since 2000, it is still the world’s No. 1 infectious-disease killer. TB claims more than one million lives annually.

There are new advances in screening, prevention and treatment, however, that now make significant progress possible — if we tap them. Success requires everyone pitching in.

In countries like India with high TB burdens, the government, the private sector and civil society organizations must commit to financing and delivering the new tools to stop TB — which India is now showing can be done. Manufacturers must lower costs. And high-income countries must do their part. The United States leads the world in providing innovation, expertise and support for countries combating the disease — both directly to local teams in high-risk settings, such as the shelter I visited, and through the Global Fund to Fight AIDS, Tuberculosis and Malaria. Last year, Congress provided additional support, enabling my team at USAID to forge new agreements with hard-hit countries, including the Philippines and Ethiopia. This is a good step, but stopping the TB scourge will require that Congress sustain these investments and that other industrialized nations do more to fill gaps.

TB is a disease that feeds on poverty and social breakdown — people weakened by hunger and depleted immune systems, living in overcrowded conditions or deprived of medical care are most vulnerable. While just one in 38,000 Americans has active TB, one in 500 people in India does. Among Delhi’s homeless population, one in every 12 people has the disease — a shocking rate. This means Delhi’s homeless face among the worst TB rates in a city with some of the worst TB rates in a country with the most TB cases in the world.

The strategy that quelled TB in the United States after World War II has worked consistently wherever it has been applied: Screen all vulnerable populations to find cases, treat the infected and stop transmission by providing those exposed with preventive treatment — even if they have no symptoms. Tubercular bacteria can hide in the body for months or years before blooming into full-blown disease.

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• Published: 12 April 2021

Vaccine development for emerging infectious diseases

• Jean-Louis Excler   ORCID: orcid.org/0000-0002-6462-5101 1 ,
• Melanie Saville 2 ,
• Seth Berkley 3 &
• Jerome H. Kim   ORCID: orcid.org/0000-0003-0461-6438 1  

Nature Medicine volume  27 ,  pages 591–600 ( 2021 ) Cite this article

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• Viral infection

Examination of the vaccine strategies and technical platforms used for the COVID-19 pandemic in the context of those used for previous emerging and reemerging infectious diseases and pandemics may offer some mutually beneficial lessons. The unprecedented scale and rapidity of dissemination of recent emerging infectious diseases pose new challenges for vaccine developers, regulators, health authorities and political constituencies. Vaccine manufacturing and distribution are complex and challenging. While speed is essential, clinical development to emergency use authorization and licensure, pharmacovigilance of vaccine safety and surveillance of virus variants are also critical. Access to vaccines and vaccination needs to be prioritized in low- and middle-income countries. The combination of these factors will weigh heavily on the ultimate success of efforts to bring the current and any future emerging infectious disease pandemics to a close.

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Newly emerging and reemerging infectious viral diseases have threatened humanity throughout history. Several interlaced and synergistic factors including demographic trends and high-density urbanization, modernization favoring high mobility of people by all modes of transportation, large gatherings, altered human behaviors, environmental changes with modification of ecosystems and inadequate global public health mechanisms have accelerated both the emergence and spread of animal viruses as existential human threats. In 1918, at the time of the ‘Spanish flu’, the world population was estimated at 1.8 billion. It is projected to reach 9.9 billion by 2050, an increase of more than 25% from the current 2020 population of 7.8 billion ( https://www.worldometers.info ). The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 (COVID-19) pandemic 1 , 2 , 3 engulfed the entire world in less than 6 months, with high mortality in the elderly and those with associated comorbidities. The pandemic has severely disrupted the world economy. Short of lockdowns, the only means of control have been limited to series of mitigation measures such as self-distancing, wearing masks, travel restrictions and avoiding gatherings, all imperfect and constraining. Now with more than 100 million people infected and more than 2 million deaths, it seems that the addition of vaccine(s) to existing countermeasures holds the best hope for pandemic control. Taken together, these reasons compel researchers and policymakers to be vigilant, reexamine the approach to surveillance and management of emerging infectious disease threats, and revisit global mechanisms for the control of pandemic disease 4 , 5 .

Emerging and reemerging infectious diseases

The appearance of new infectious diseases has been recognized for millennia, well before the discovery of causative infectious agents. Despite advances in development of countermeasures (diagnostics, therapeutics and vaccines), world travel and increased global interdependence have added layers of complexity to containing these infectious diseases. Emerging infectious diseases (EIDs) are threats to human health and global stability 6 , 7 . A review of emerging pandemic diseases throughout history offers a perspective on the emergence and characteristics of coronavirus epidemics, with emphasis on the SARS-CoV-2 pandemic 8 , 9 . As human societies grow in size and complexity, an endless variety of opportunities is created for infectious agents to emerge into the unfilled ecologic niches we continue to create. To illustrate this constant vulnerability of populations to emerging and reemerging pathogens and their respective risks to rapidly evolve into devastating outbreaks and pandemics, a partial list of emerging viral infectious diseases that occurred between 1900 and 2020 is shown in Table 1 .

Although nonemerging infectious diseases (not listed in Table 1 ), two other major mosquito-borne viral infections are yellow fever and dengue. Yellow fever, known for centuries and an Aedes mosquito-borne disease, is endemic in more than 40 countries across Africa and South America. Since 2016, several yellow fever outbreaks have occurred in Angola, Democratic Republic of Congo, Nigeria and Brazil to cite a few 10 , raising major concerns about the adequacy of yellow fever vaccine supply. Four live attenuated vaccines derived from the live attenuated yellow fever strain (17D) 11 and prequalified by the WHO (World Health Organization) are available 12 .

Dengue is an increasing global public health threat with the four dengue virus types (DENV1–4) now cocirculating in most dengue endemic areas. Population growth, an expansion of areas hospitable for Aedes mosquito species and the ease of travel have all contributed to a steady rise in dengue infections and disease. Dengue is common in more than 100 countries around the world. Each year, up to 400 million people acquire dengue. Approximately 100 million people get sick from infection, and 22,000 die from severe dengue. Most seriously affected by outbreaks are the Americas, South/Southeast Asia and the Western Pacific; Asia represents ~70% of the global burden of disease ( https://www.cdc.gov/dengue ). Several vaccines have been developed 13 . A single dengue vaccine, Sanofi Pasteur’s Dengvaxia based on the yellow fever 17D backbone, has been licensed in 20 countries, but uptake has been poor. A safety signal in dengue-seronegative vaccine recipients stimulated an international review of the vaccine performance profile, new WHO recommendations for use and controversy in the Philippines involving the government, regulatory agencies, Sanofi Pasteur, clinicians responsible for testing and administering the vaccine, and the parents of vaccinated children 14 .

Two bacterial diseases, old scourges of humanity, are endemic and responsible for recurrent outbreaks and are increasingly antimicrobial resistant. Cholera, caused by pathogenic strains of Vibrio cholerae , is currently in its seventh global pandemic since 1817; notably, the seventh pandemic started in 1961 15 . Global mortality due to cholera infection remains high, mainly due to delay in rehydrating patients. The global burden of cholera is estimated to be between 1.4 and 4.3 million cases with about 21,000–143,000 deaths per year, mostly in Asia and Africa. Tragic outbreaks have occurred in Yemen and Haiti. Adding to rehydration therapy, antibiotics have been used in the treatment of cholera to shorten the duration of diarrhea and to limit bacterial spread. Over the years, antimicrobial resistance developed in Asia and Africa to many useful antibiotics including chloramphenicol, furazolidone, trimethoprim-sulfamethoxazole, nalidixic acid, tetracycline and fluoroquinolones. Several vaccines have been developed and WHO prequalified; these vaccines constitute a Gavi-supported global stockpile for rapid deployment during outbreaks 16 .

Typhoid fever is a severe disease caused by the Gram-negative bacterium Salmonella enterica subsp. enterica serovar Typhi ( S . Typhi). Antimicrobial-resistant S . Typhi strains have become increasingly common. The first large-scale emergence and spread of a novel extensively drug-resistant (XDR) S . Typhi clone was first reported in Sindh, Pakistan 17 , 18 , and has subsequently been reported in India, Bangladesh, Nepal, the Philippines, Iraq and Guatemala 19 , 20 . The world is in a critical period as XDR S . Typhi has appeared in densely populated areas. The successful development of improved typhoid vaccines (conjugation of the Vi polysaccharide with a carrier protein) with increased immunogenicity and efficacy including in children less than 2 years of age will facilitate the control of typhoid, in particular in XDR areas by decreasing the incidence of typhoid fever cases needing antibiotic treatment 21 , 22 .

A model of vaccine development for emerging infectious diseases

The understanding of emerging infectious diseases has evolved over the past two decades. A look back at the SARS-CoV outbreak in 2002 shows that—despite a small number of deaths and infections—its high mortality and transmissibility caused significant global disruption (see Table 1 ). The epidemic ended as work on vaccines was initiated. Since then, the disease has not reappeared—wet markets were closed and transmission to humans from civets ceased. Consequently, work on vaccines against SARS-CoV ended and its funding was cut. Only a whole inactivated vaccine 23 and a DNA vaccine 24 were tested in phase 1 clinical trials.

Following a traditional research and development pipeline, it takes between 5 and 10 years to develop a vaccine for an infectious agent. This approach is not well suited for the needs imposed by the emergence of a new pathogen during an epidemic. Figure 1 shows a comparison of the epidemic curves and vaccine development timelines between the 2014 West African Ebola outbreak and COVID-19. The 2014 Ebola epidemic lasted more than 24 months with 11,325 deaths and was sufficiently prolonged to enable the development and testing of vaccines for Ebola, with efficacy being shown for one vaccine (of several) toward the end of the epidemic 25 , 26 . What makes the COVID-19 pandemic remarkable is that the whole research and development pipeline, from the first SARS-CoV-2 viral sequenced to interim analyses of vaccine efficacy trials, was accomplished in just under 300 days 27 . Amid increasing concerns about unmitigated transmission during the 2013–2016 Western African Ebola outbreak in mid-2014, WHO urged acceleration of the development and evaluation of candidate vaccines 25 . To ensure that manufacturers would take the Ebola vaccine to full development and deployment, Gavi, the Vaccine Alliance, publicly announced support of up to US$300 million for vaccine purchase and followed that announcement with an advance purchase agreement. Ironically, there had been Ebola vaccines previously developed and tested for biodefense purposes in nonhuman primates, but this previous work was neither ‘ready’ for clinical trials during the epidemic nor considered commercially attractive enough to finish development 28 .

a , The number of months from the onset of the epidemic is shown against the number of reported cases per day. Note that the COVID-19 (left) and Ebola (right) axes are scaled differently. b , Vaccine development timelines for COVID-19 versus Ebola in the context of particular events during the respective outbreaks. PHEIC, public health emergency of international concern.

From these perceived shortcomings in vaccine development during public health emergencies arose the Coalition for Epidemic Preparedness Innovations (CEPI), a not-for-profit organization dedicated to timely vaccine development capabilities in anticipation of epidemics 29 , 30 . CEPI initially focused on diseases chosen from a list of WHO priority pathogens for EIDs—Middle East respiratory syndrome (MERS), Lassa fever, Nipah, Rift Valley fever (RVF) and chikungunya. The goal of CEPI was to advance candidate vaccines through phase 2 and to prepare stockpiles of vaccine against eventual use/testing under epidemic circumstances. CEPI had also prepared for ‘disease X’ by investing in innovative rapid response platforms that could move from sequence to clinical trials in weeks rather than months or years, such as mRNA and DNA technology, platforms that were useful when COVID-19 was declared a global health emergency in January 2020, and a pandemic in March 2020 31 , 32 .

CEPI has been able to fund several vaccine development efforts, among them product development by Moderna, Inovio, Oxford–AstraZeneca and Novavax. Providing upfront funding helped these groups to advance vaccine candidates to clinical trials and develop scaled manufacturing processes in parallel, minimizing financial risk to vaccine developers. The launch of the larger US-funded Operation Warp Speed 33 further provided companies with funding—reducing risks associated with rapid vaccine development and securing initial commitments in vaccine doses.

Vaccine platforms and vaccines for emerging infectious diseases

Vaccines are the cornerstone of the management of infectious disease outbreaks and are the surest means to defuse pandemic and epidemic risk. The faster a vaccine is deployed, the faster an outbreak can be controlled. As discussed in the previous section, the standard vaccine development cycle is not suited to the needs of explosive pandemics. New vaccine platform technologies however may shorten that cycle and make it possible for multiple vaccines to be more rapidly developed, tested and produced 34 . Table 2 provides examples of the most important technical vaccine platforms for vaccines developed or under development for emerging viral infectious diseases. Two COVID-19 vaccines were developed using mRNA technology (Pfizer–BioNTech 35 and Moderna 36 ), both showing safety and high efficacy, and now with US Food and Drug Administration (FDA) emergency use authorization (EUA) 37 , 38 and European Medicines Agency (EMA) conditional marketing authorization 39 , 40 . While innovative and encouraging for other EIDs, it is too early to assert that mRNA vaccines represent a universal vaccine approach that could be broadly applied to other EIDs (such as bacterial or enteric pathogens). While COVID-19 mRNA vaccines are a useful proof of concept, gathering lessons from their large-scale deployment and effectiveness studies still requires more work and time.

While several DNA vaccines are licensed for veterinary applications, and DNA vaccines have shown safety and immunogenicity in human clinical trials, no DNA vaccine has reached licensure for use in humans 41 . Recombinant proteins vary greatly in design for the same pathogen (for example, subunit, virus-like particles) and are often formulated with adjuvants but have longer development times. Virus-like particle-based vaccines used for hepatitis B and human papillomavirus are safe, highly immunogenic, efficacious and easy to manufacture in large quantity. The technology is also easily transferable. Whole inactivated pathogens (for example, SARS-CoV-2, polio, cholera) or live attenuated vaccines (for example, SARS-CoV-2, polio, chikungunya) are unique to each pathogen. Depending on the pathogen, these vaccines also may require biosafety level 3 manufacturing (at least for COVID-19 and polio), which may limit the possibility of technology transfer for increasing the global manufacturing capacity.

Other vaccines are based on recombinant vector platforms, subdivided into nonreplicating vectors (for example, adenovirus 5 (Ad5), Ad26, chimpanzee adenovirus-derived ChAdOx, highly attenuated vectors like modified vaccinia Ankara (MVA)) and live attenuated vectors such as the measles-based vector or the vesicular stomatitis virus (VSV) vector. Either each vector is designed with specific inserts for the pathogen targeted, or the same vector can be designed with different inserts for the same disease. The development of the Merck Ebola vaccine is an example. ERVEBO is a live attenuated, recombinant VSV-based, chimeric-vector vaccine, where the VSV envelope G protein was deleted and replaced by the envelope glycoprotein of Zaire ebolavirus . ERVEBO is safe and highly efficacious, now approved by the US FDA and the EMA, and WHO prequalified, making VSV an attractive ‘platform’ for COVID-19 and perhaps for other EID vaccines 26 although the −70 °C ultracold chain storage requirement still presents a challenge.

Other equally important considerations are speed of development, ease of manufacture and scale-up, ease of logistics (presentation, storage conditions and administration), technology transfer to other manufacturers to ensure worldwide supply, and cost of goods. Viral vectors such as Ad5, Ad26 and MVA have been used in HIV as well as in Ebola vaccines 42 . Finally, regulatory authorities do not approve platforms but vaccines. Each vaccine is different. However, with each use of a specific technology, regulatory agencies may, over time, become more comfortable with underlying technology and the overall safety and efficacy of the vaccine platform, allowing expedited review and approvals in the context of a pandemic 43 . With COVID-19, it meant that the regulatory authorities could permit expedited review of ‘platform’ technologies, such as RNA and DNA, that had been used (for other conditions) and had safety profiles in hundreds of people.

A heterologous prime–boost (HPB) vaccine approach has been extensively explored for HIV 44 and Ebola vaccines 42 . It is being investigated for COVID-19 vaccines with the Oxford–AstraZeneca AZD1222 and Gamaleya Sputnik V COVID-19 vaccines 45 or with the Pfizer–BioNTech vaccine ( https://www.comcovstudy.org.uk ). Other HPB combinations might be considered involving mRNA, DNA, viral vector-based and protein-based vaccines. This may offer the potential benefit of improving the immune response and avoiding mutlidose reactogenicity or anti-vector immune responses. Additionally, people previously vaccinated with the standard regimen (for example, single or two dose) could be offered a booster immunization with a different vaccine. This might mitigate current shortages in vaccines, particularly in low- and middle-income countries (LMICs). Such a matrix of HPB possibilities deserves further consideration by manufacturers, funders and regulators supported by clinical trial studies and assessment of implementation challenges.

Important improvements could speed up availability. Standardized labeling of vaccines so that they can be interchanged across countries and regions, date of production rather than expiration so that shelf life can be tracked, three-dimensional bar coding to allow critical information to be updated, standard indemnification and liability language that would allow agreement with all manufacturers, a no-fault compensation mechanism for serious adverse events related to vaccine administration, and regulatory harmonization are all critical and being worked on as part of the COVID-19 vaccine response and must be optimized for future outbreaks.

The pathway to EUA, licensure and beyond

Big pharmaceutical or biotechnology companies supported by organizations such as CEPI or efforts such as Operation Warp Speed have conducted efficacy trials in countries or regions with the highest SARS-CoV-2 incidence rates. The same groups have also committed funding for large-scale manufacturing at risk. With more than 60 vaccine candidates in clinical trials and another 170 in preclinical development (WHO COVID-19 vaccine landscape) 46 , it is uncertain whether vaccine candidates not in the first wave of testing/approvals will be able to progress to EUA and licensure based solely on results of randomized clinical efficacy trials with clinical endpoints. Regulators and ethics committees may decide that noninferiority clinical trials against comparator vaccines with proven clinical efficacy will be needed for further approvals. Would the demonstration of equivalence between immune responses generated by a new vaccine and those of a clinically proven efficacious vaccine (bridging studies) 47 be accepted by regulatory authorities and replace the need for noninferiority clinical endpoint studies? For that to occur there must be agreement on what are immune correlates of protection (ICP) to COVID-19, and these have yet to be identified. Moreover, it is not yet clear that ICP will translate equally between different vaccine platforms; for example, are immune responses generated by chimpanzee adenovirus the same as those generated by proteins or whole inactivated virus? As incidence rates of a disease decrease over time due to sustained mitigation measures and implementation of vaccination, larger sample sizes in multicountry trials, additional participant accrual time and complex logistics will likely be required for future approvals, compromising the speed of clinical development and increasing cost. Early deployment of scarce doses of still-investigational vaccines (under emergency use listing (EUL) or similar regulatory mechanisms) could bring additional public health benefits if accompanied by firm commitment to maintaining blinded follow-up of participants in ongoing or future placebo-controlled trials until a licensed vaccine is fully deployed in the population 48 .

Randomized controlled trials might underestimate the protective effect of vaccines at the population level. This would occur if the COVID-19 vaccine, in addition to conferring direct protection to individuals, reduces transmission of COVID-19 between individuals, providing protection to unvaccinated individuals and enhanced protection of vaccinated individuals in contact with vaccinated individuals. Vaccine-induced herd protection, which might be crucial to the public health value of a vaccine, will be missed when trials are individually randomized and analyses fail to take account of the geographical distribution of individuals in the population 49 . For these reasons, other clinical trial designs have been proposed once COVID-19 vaccines have achieved licensure via current phase 3 trials to assess how useful the vaccines will be in practice and addressing vaccine effectiveness, including the level of protection of both vaccinated and nonvaccinated individuals in targeted populations 50 .

In the particular context of the COVID-19 pandemic, whether regulatory authorities would require clinical endpoints in future efficacy trials or would consider ICP remains unclear. Clinical endpoints provide increased accuracy with regard to definitive clinical outcomes where outcome-related analyses using ICP are inferential. ICP will contribute to our understanding of viral pathogenesis and immunity, be useful for future approval of vaccines, and help in our understanding of waning of protective immunity following vaccination or infection. The paradox is that the higher the efficacy, the more difficult it will be to identify these correlates because there may not be enough infected vaccine recipients to compare with uninfected vaccine recipients. The analysis of ICP may be possible only in clinical trials showing a lower vaccine efficacy 50 . They would also not provide a rigorous evaluation of long-term safety and the potential for vaccine-associated enhanced respiratory disease 51 .

Pharmacovigilance and surveillance

In May 2020, the 42nd Global Advisory Committee on Vaccine Safety addressed pharmacovigilance preparedness for the launch of the future COVID-19 vaccines 52 . One of their recommendations was that infrastructure and capacity for surveillance of the safety of COVID-19 vaccines should be in place in all countries and engaged before a vaccine is introduced. The WHO’s COVID-19 vaccine safety surveillance manual develops the monitoring and reporting of adverse events following immunization and adverse events of special interest, data management systems and safety communication, and the need for postauthorization safety surveillance studies 53 . One critical element of this surveillance is the duration of the observation period. The implementation of this surveillance will require local, national, regional and global collaboration. While countries should include preparedness plans for COVID-19 vaccine safety in their overall plans for vaccine introduction, building on WHO guidance, it is imperative that the COVID-19 Vaccines Global Access (COVAX) initiative (coordinated by CEPI, Gavi, the Vaccine Alliance, and WHO) works with partners on capacity building and the practical aspects of implementation with technical and training support tailored to the settings.

In view of the public health urgency and the extensive vaccination campaigns foreseen worldwide, the EMA and the national competent authorities in EU member states have prepared themselves for the expected high data volume by putting pharmacovigilance plans specific for COVID-19 vaccines in place. Good pharmacovigilance practices include detailed requirements and guidance on the principles of a risk management plan (RMP) and requirements for vaccines. In addition, core RMP requirements for COVID-19 vaccines have been developed to facilitate and harmonize the preparation of RMPs by companies and their evaluation by assessors. The RMP preparation addresses the planning of the postauthorization safety follow-up of COVID-19 vaccines by marketing authorization holders, while acknowledging uncertainties in the pandemic setting and recommending ways to prepare for pharmacovigilance activities 54 . Similarly, the US Advisory Committee on Immunization Practices (ACIP) initially convened the COVID-19 Vaccine Safety Technical Working Group in June 2020 to advise the ACIP COVID-19 Vaccine Workgroup and the full ACIP on the safety monitoring of COVID-19 vaccines under development and pharmacovigilance postapproval 55 .

Key lessons could be learnt from past situations where new vaccines were introduced in response to pandemic and epidemic emergencies. For the 2009 H1N1 influenza pandemic, few countries had a pandemic preparedness plan that comprehensively addressed vaccine deployment and monitoring of adverse events. The African Vaccine Regulatory Forum, a regional network of regulators and ethics committees, working closely with regulators from other parts of the world, participated in the review of clinical trial protocols and results, the joint monitoring of trials and the joint authorization and deployment of vaccines 56 . Such models can be used to guide pharmacovigilance for the deployment of COVID-19 vaccines, particularly in LMICs with limited resources. The introduction of the first licensed dengue vaccine, while not in the context of an international public health emergency, illustrated a number of lessons for the pharmacovigilance of newly introduced vaccines, particularly the vaccine-associated enhanced disease that was observed 13 , 14 . Due to the significant sequence homology between SARS-CoV-2 and SARS-CoV, antibody-dependent enhancement (ADE) and vaccine-associated enhanced respiratory disease (VAERD) were raised as potential safety issues 57 , 58 . VAERD and ADE have not been described in current reports of SARS-CoV-2 vaccine phase 3 trials. Similarly, VAERD has not been reported in animal challenge studies with SARS-CoV-2 vaccines that conferred protection 50 . With ADE the effect of waning antibody titers after vaccination (or after infection) and potential safety signals are unknown, which emphasizes the importance of follow-up monitoring 57 .

Pregnant women seem to be disproportionately affected during pandemics and emerging pathogen outbreaks 59 , 60 . The Pregnancy Research Ethics for Vaccines, Epidemics, and New Technologies (PREVENT) Working Group has published a roadmap to guide the inclusion of the interests of pregnant women in the development and deployment of vaccines against emerging pathogens 61 , 62 .

Equally important is the surveillance on SARS-CoV-2 circulating strains as well as of other coronaviruses (MERS, seasonal) 63 . SARS-CoV-2 is evolving, with new lineages being reported all over the world. Amongst previous lineages, D614G was shown to have faster growth in vitro and enhanced transmission in small animals, and has subsequently become globally dominant 64 , 65 , 66 . Other variants of concern have been described in the UK (B.1.1.7) 67 and in Brazil (B.1.1.28.1/P1) 68 with higher capacity for transmission and, potentially, lethality. N501Y (B.1.351) isolated in South Africa has an increased affinity for the human ACE2 receptor, which together with the repeated and independent evolution of 501Y-containing lineages 69 strongly argues for enhanced transmissibility. The B.1.351 variant has nine spike alterations; it rapidly emerged in South Africa during the second half of 2020 and has shown resistance to neutralizing antibodies elicited by infection and vaccination with previously circulating lineages. The AstraZeneca COVID-19 vaccine rollout in South Africa was recently halted after the analysis showed minimal efficacy against mild and moderate cases due to B.1.351, which accounts for 90% of the cases in this country 70 . The Novavax vaccine efficacy is 86% against the variant identified in the UK and 60% against the variant identified in South Africa 71 . The efficacy of a single dose of Johnson & Johnson’s Ad26 was 57% against moderate to severe COVID-19 infection in South Africa 72 .

For the many people who have already been infected with SARS-CoV-2 globally and are presumed to have accumulated some level of immunity, new variants such as B.1.351 pose a significant reinfection risk, although vaccine-induced cell-mediated immune responses might mitigate this risk. Scientists do not know how variant lineages will evolve under vaccine-induced immune pressure during the vaccination rollout or whether choices that alter the schedule or dose may impact virus evolution. Whether vaccines efficacious against current circulating strains including the variants identified in the UK and Brazil will keep their efficacy against emerging variants is unknown and deserves enhanced global COVID-19 surveillance in both humans and animals, similar to those developed for influenza. Global influenza surveillance has been conducted through WHO’s Global Influenza Surveillance and Response System since 1952. The Global Influenza Surveillance and Response System is a global mechanism of surveillance, preparedness and response for seasonal, pandemic and zoonotic influenza, a global platform for monitoring influenza epidemiology and disease, and a global alert system for novel influenza viruses and other respiratory pathogens 73 . The Global Initiative on Sharing Avian Influenza Database ( https://www.gisaid.org ) promotes the rapid sharing of data from all influenza viruses and the coronavirus causing COVID-19. These include genetic sequence and related clinical and epidemiological data associated with human viruses, and geographical as well as species-specific data associated with avian and other animal viruses. This molecular epidemiology surveillance should be expanded to all EIDs, particularly the deadliest and most transmissible, as recently described for Ebola 25 . As with influenza, preparations for SARS-CoV-2 vaccine variants should be proactive, with a view that platforms such as mRNA could generate new vaccine strains very rapidly. A clear regulatory pathway for strain change needs discussion with the regulators.

Approval process for licensure and EUA and the risk of speed

Vaccines are classically approved by the country’s national regulatory authority such as the US FDA or by a centralized procedure through the EMA. Once approved for licensure by a stringent or functional national regulatory authority in the country of manufacture, the manufacturing company can submit a dossier for WHO prequalification. However, for SARS-CoV-2 vaccines intended for COVAX, WHO prequalification is not required for initial use if they have received WHO EUL. COVAX is one of three pillars of the Access to COVID-19 Tools Accelerator, which was launched in April 2020 by the WHO, the EC (European Commission) and France. Vaccines receiving WHO EUL can be purchased by UNICEF (United Nations International Children’s Emergency Fund), the largest purchaser of vaccines for Gavi, the Vaccine Alliance. Countries participating in COVAX can access the vaccines through the COVAX Facility either as 1 of the 98 self-financing countries or, for the 92 LMICs, funded through the Gavi COVAX advance market commitment (AMC; https://www.gavi.org ).

In the current pandemic situation, the US FDA is using the EUA process to allow initial use of the vaccines from Pfizer, Moderna and Johnson & Johnson 74 . EMA is taking the approach of conditional approval 75 . The WHO emergency use assessment and listing (EUAL) procedure was developed in the wake of the Ebola virus disease outbreak in Africa to expedite the availability of vaccines. The EUAL was intended as guidance for national regulatory authorities in circumstances when the “community may be more willing to tolerate less certainty about the efficacy and safety of products, given the morbidity and/or mortality of the disease and the shortfall of treatment and/or prevention options” 76 . In early 2020, the WHO issued a revised EUL procedure to assess whether submitted data demonstrate a reasonable likelihood that a vaccine’s quality, safety and performance are acceptable and that the benefits outweigh the foreseeable risks and uncertainties in the context of a public health emergency of international concern 77 . It is intended that vaccines approved through EUAL would eventually go to full review and receive prequalification. WHO member states have the prerogative through their national regulatory authority to use the EUL procedure to authorize the use of unlicensed vaccines.

Some countries have used their national regulatory authorities to secure approval of nationally produced vaccines. The Russian government approved the Ad26 and Ad5 combination-based COVID-19 vaccine, Sputnik V, produced by the Gamaleya Research Institute, for use by individuals aged 60 years and above 78 , 79 . China’s National Medical Products Agency has given conditional approval to the whole inactivated virus BBIBP-CorV COVID-19 vaccine developed by the Beijing Institute of Biological Products, a Sinopharm subsidiary 80 . The authorization allows the general public’s use of the inoculation and comes after the company announced that its vaccine proved 79.3% effective in phase 3 trials 81 . Although the interim results are not yet published, they must have been reviewed and approved by the Chinese Center for Disease Control and Prevention and National Medical Products Agency. The United Arab Emirates was first to approve the Sinopharm vaccine for EUA in early December 2020 based on interim analysis results 82 . The Sinovac CoronaVac vaccine was recently granted conditional approval on the basis of interim efficacy results 83 . The CanSinoBIO COVID-19 vaccine achieved 65.7% efficacy in preventing symptomatic cases in clinical trials (unpublished). The vaccine also showed a 90.98% success rate in stopping severe disease in one of its interim analysis. The vaccine was granted EUA in Mexico and Pakistan 84 .

Manufacturing—how to make more, faster

Production and distribution of hundreds of millions of doses of COVID-19 vaccine within a year of identification of the pandemic pathogen is unprecedented, and while the principles are straightforward, the manufacturing equation is complex and prone to delay. The technical platform utilized to make a vaccine (mRNA, whole inactivated virus, vector, protein with or without adjuvant), the dosage (low, mid, high), the schedule of vaccination (single or two dose) and the manufacturer capability, capacity and reputation are all important considerations for regulators and the WHO. The initial phase of manufacturing scale-up will be a key regulator of vaccine access initially. This could potentially be impacted by vaccine nationalism and the announced bilateral agreements between manufacturers and high-income countries. Companies such as Sinopharm, the Serum Institute of India or Bharat have a huge capacity for production but must supply the gigantic markets of China and India. Delays in the production of several western 85 and Chinese COVID-19 vaccines 86 have already been reported.

The Developing Countries Vaccine Manufacturers Network (DCVMN) was established in 2000 with the mission to increase the availability and affordability of quality vaccines to protect against known and emerging infectious diseases 87 . About 70% of the global EPI vaccine supplies and about 75% procured by UN (United Nations) agencies are produced by DCVMN members 88 . Several technology transfers to DCVMN members have occurred over the past decades to significantly contribute to global health. Following an initial collaboration on the oral cholera vaccine between Sweden and VABIOTECH in Vietnam, the International Vaccine Institute improved the vaccine and then transferred the technology back to VABIOTECH and to several DCVMN members, including Shantha Biotechnics (Shanchol), India; EuBiologics (Euvichol), Republic of Korea; and Incepta (Cholvax), Bangladesh. Shanchol, Euvichol and Euvichol Plus are WHO prequalified and the major contributors to the Gavi-supported global stockpile 16 while Cholvax is marketed in Bangladesh.

For COVID-19 vaccines, several companies have licensed or contracted vaccine production to other manufacturers—AstraZeneca and Novavax with the Serum Institute (India) and SK Bioscience (Korea); Moderna with Lonza (Switzerland), Johnson & Johnson with Biological E (India); and Chinese Sinovac with Butantan (Brazil) and BioFarma (Indonesia). Hopefully the license and contract manufacturing arrangements will allow the production of sufficient doses of vaccines to provide equitable access to at-risk populations globally 89 .

Under the pressures of the pandemic, and with the need for accelerated development of COVID-19 vaccines, optimization of more practical aspects of vaccine implementation, supply and dosing was secondary to the need for rapid proof of concept. COVID-19 mRNA vaccines and the VSV-EBO Ebola vaccine from Merck have a similar requirement for ultracold chain storage. While that might be overcome by relatively simple technology, the scalability of these technologies for universal vaccination is unknown. Additional development is needed to establish the stability of vaccines at higher temperatures (Pfizer mRNA). There is evidence to suggest the presence of some protection against COVID-19 after the first dose; this is critical information not only for COVID-19 but also to frame thinking around other EID vaccines.

Leave no one behind, or the unequal access to vaccines and treatments

The 2030 Agenda for Sustainable Development has the vision to leave no one behind, particularly low-income countries. COVID-19 has seen exceptionalism at either extreme. On the one hand, COVAX aims to provide at least 2 billion doses of WHO-approved vaccine to participating countries by the end of 2021—roughly 20% of each country’s vaccination needs. A total of 92 LMICs will receive vaccine largely through an AMC arranged by Gavi 90 . It now appears that the USA will join COVAX, which recently announced that it had secured agreements for sufficient doses to meet the 2021 target 50 .

Critically, vaccinating people in LMICs will require additional vaccine purchases, at a cost estimated in billions of dollars. In purely economic terms, it appears that such an investment could have substantial benefit for the global economy 91 . On the other hand, COVAX is on track to achieve its goals and poised to start delivering vaccines, and yet no AMC countries had yet been vaccinated when tens of millions of people were already being vaccinated in high-income countries. Among high-income countries, billions of doses have been preordered, several times more than justified by their populations. Can COVAX achieve its target of providing 2 billion doses by 2021, or will manufacturing bottlenecks lead to delay that will allow the coronavirus to continue to circulate in poorer countries and prolong the pandemic? If unable to access COVID-19 vaccines in a timely manner, the 2030 Agenda for Sustainable Development, especially Sustainable Development Goal 3 focusing on health, will be difficult to achieve, and low-income countries will be under extraordinary pressure as the COVID-19 pandemic forces them further into poverty and deeper inequality.

UN Secretary-General António Guterres has again stressed that COVID-19 vaccines must be a global public good, available to everyone, everywhere. “Vaccinationalism is self-defeating and would delay a global recovery” 92 . Modeling studies suggest that if high-income countries take the first 2 billion doses of available COVID-19 vaccines without regard to equity, global COVID-19 deaths will double 93 . Ensuring that all countries have rapid, fair and equitable access to COVID-19 vaccines is the promise of COVAX.

Final remarks

The lessons of the COVID-19 pandemic need to be compiled and applied to the development of future vaccines against emerging infectious diseases and novel pandemic pathogens. The permanent threat of emerging pathogens calls for vigilance, surveillance and preparedness for vaccine development and deployment, all crosscutting activities to be conducted flawlessly between epidemiologists, scientists, developers, human and veterinary health authorities, regulators and funders. Global health stakeholders have learned something about developing vaccines efficiently: they still have much to learn about making and using them with due regard to equity and access.

Zhu, N. et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 382 , 727–733 (2020).

CAS   PubMed   PubMed Central   Google Scholar  

Huang, C. et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395 , 497–506 (2020).

Wang, D. et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 323 , 1061–1069 (2020).

Friedler, A. Sociocultural, behavioural and political factors shaping the COVID-19 pandemic: the need for a biocultural approach to understanding pandemics and (re)emerging pathogens. Glob. Public Health 16 , 17–35 (2021).

Article   PubMed   Google Scholar  

Gully, P. R. Pandemics, regional outbreaks, and sudden-onset disasters. Healthc. Manage. Forum 33 , 164–169 (2020).

Morens, D. M. & Fauci, A. S. Emerging infectious diseases: threats to human health and global stability. PLoS Pathog. 9 , e1003467 (2013).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Marston, H. D., Folkers, G. K., Morens, D. M. & Fauci, A. S. Emerging viral diseases: confronting threats with new technologies. Sci. Transl. Med. 6 , 253ps210 (2014).

Article   Google Scholar  

Morens, D. M. & Fauci, A. S. Emerging pandemic diseases: how we got to COVID-19. Cell 182 , 1077–1092 (2020).

Morens, D. M., Daszak, P. & Taubenberger, J. K. Escaping Pandora’s box—another novel coronavirus. N. Engl. J. Med. 382 , 1293–1295 (2020).

Article   CAS   PubMed   Google Scholar  

Sacchetto, L., Drumond, B. P., Han, B. A., Nogueira, M. L. & Vasilakis, N. Re-emergence of yellow fever in the neotropics—quo vadis? Emerg. Top. Life Sci. 4 , 399–410 (2020).

PubMed   Google Scholar  

World Health Organization. Yellow fever. https://www.who.int/biologicals/vaccines/yellow_fever/en/ (2015).

Juan-Giner, A. et al. Immunogenicity and safety of fractional doses of yellow fever vaccines: a randomised, double-blind, non-inferiority trial. Lancet 397 , 119–127 (2021).

Prompetchara, E., Ketloy, C., Thomas, S. J. & Ruxrungtham, K. Dengue vaccine: global development update. Asian Pac. J. Allergy Immunol. 38 , 178–185 (2020).

PubMed   CAS   Google Scholar  

Thomas, S. J. & Yoon, I. K. A review of Dengvaxia ® : development to deployment. Hum. Vaccin. Immunother. 15 , 2295–2314 (2019).

Article   PubMed   PubMed Central   Google Scholar  

Hu, D. et al. Origins of the current seventh cholera pandemic. Proc. Natl Acad. Sci. USA 113 , E7730–E7739 (2016).

Shaikh, H., Lynch, J., Kim, J. & Excler, J. L. Current and future cholera vaccines. Vaccine 38 , A118–A126 (2020).

Klemm, E. J. et al. Emergence of an extensively drug-resistant Salmonella enterica serovar Typhi clone harboring a promiscuous plasmid encoding resistance to fluoroquinolones and third-generation cephalosporins. mBio 9 , e00105–18 (2018).

Yousafzai, M. T. et al. Ceftriaxone-resistant Salmonella Typhi outbreak in Hyderabad City of Sindh, Pakistan: high time for the introduction of typhoid conjugate vaccine. Clin. Infect. Dis. 68 , S16–S21 (2019).

Qamar, F. N. et al. Antimicrobial resistance in typhoidal salmonella: surveillance for enteric fever in Asia project, 2016–2019. Clin. Infect. Dis. 71 , S276–S284 (2020).

Marchello, C. S., Carr, S. D. & Crump, J. A. A systematic review on antimicrobial resistance among Salmonella Typhi worldwide. Am. J. Trop. Med. Hyg. 103 , 2518–2527 (2020).

Andrews, J. R. et al. Typhoid conjugate vaccines: a new tool in the fight against antimicrobial resistance. Lancet Infect. Dis. 19 , e26–e30 (2019).

D’Souza, M. P. & Frahm, N. Adenovirus 5 serotype vector-specific immunity and HIV-1 infection: a tale of T cells and antibodies. AIDS 24 , 803–809 (2010).

Lin, J. T. et al. Safety and immunogenicity from a phase I trial of inactivated severe acute respiratory syndrome coronavirus vaccine. Antivir. Ther. 12 , 1107–1113 (2007).

Martin, J. E. et al. A SARS DNA vaccine induces neutralizing antibody and cellular immune responses in healthy adults in a Phase I clinical trial. Vaccine 26 , 6338–6343 (2008).

Jacob, S. T. et al. Ebola virus disease. Nat. Rev. Dis. Primers 6 , 13 (2020).

Wolf, J. et al. Applying lessons from the Ebola vaccine experience for SARS-CoV-2 and other epidemic pathogens. NPJ Vaccines 5 , 51 (2020).

Ball, P. The lightning-fast quest for COVID vaccines—and what it means for other diseases. Nature 589 , 16–18 (2021).

Feldmann, H., Feldmann, F. & Marzi, A. Ebola: lessons on vaccine development. Annu. Rev. Microbiol. 72 , 423–446 (2018).

Gouglas, D., Christodoulou, M., Plotkin, S. A. & Hatchett, R. CEPI: driving progress toward epidemic preparedness and response. Epidemiol. Rev. 41 , 28–33 (2019).

Rottingen, J. A. et al. New vaccines against epidemic infectious diseases. N. Engl. J. Med. 376 , 610–613 (2017).

Sandbrink, J. B. & Shattock, R. J. RNA vaccines: a suitable platform for tackling emerging pandemics? Front. Immunol. 11 , 608460 (2020).

Jackson, N. A. C., Kester, K. E., Casimiro, D., Gurunathan, S. & DeRosa, F. The promise of mRNA vaccines: a biotech and industrial perspective. NPJ Vaccines 5 , 11 (2020).

US Department of Health and Human Health Services. Explaining Operation Warp Speed. https://health.mo.gov/living/healthcondiseases/communicable/novel-coronavirus-lpha/pdf/fact-sheet-operation-warp-speed.pdf 2020).

van Riel, D. & de Wit, E. Next-generation vaccine platforms for COVID-19. Nat. Mater. 19 , 810–812 (2020).

Article   PubMed   CAS   Google Scholar  

Polack, F. P. et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine. N. Engl. J. Med. 383 , 2603–2615 (2020).

Baden, L. R. et al. Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccine. N. Engl. J. Med. 384 , 403–416 (2021).

US Food and Drug Administration. FDA takes key action in fight against COVID-19 by issuing emergency use authorization for first COVID-19 vaccine. https://www.fda.gov/news-events/press-announcements/fda-takes-key-action-fight-against-covid-19-issuing-emergency-use-authorization-first-covid-19 (2020).

US Food and Drug Administration. FDA takes additional action in fight against COVID-19 by issuing emergency use authorization for second COVID-19 vaccine. https://www.fda.gov/news-events/press-announcements/fda-takes-additional-action-fight-against-covid-19-issuing-emergency-use-authorization-second-covid (2020).

European Medicines Agency. EMA recommends first COVID-19 vaccine for authorisation in the EU. https://www.ema.europa.eu/en/news/ema-recommends-first-covid-19-vaccine-authorisation-eu (2020).

European Medicines Agency. EMA recommends COVID-19 Vaccine Moderna for authorisation in the EU. https://www.ema.europa.eu/en/news/ema-recommends-covid-19-vaccine-moderna-authorisation-eu (2021).

Liu, M. A. A Comparison of plasmid DNA and mRNA as vaccine technologies. Vaccines 7 , 37 (2019).

Article   CAS   PubMed Central   Google Scholar  

Pollard, A. J. et al. Safety and immunogenicity of a two-dose heterologous Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen in adults in Europe (EBOVAC2): a randomised, observer-blind, participant-blind, placebo-controlled, phase 2 trial. Lancet Infect. Dis . https://doi.org/10.1016/S1473-3099(20)30476-X (2020).

Adalja, A. A., Watson, M., Cicero, A. & Inglesby, T. Vaccine platform technologies: a potent tool for emerging infectious disease vaccine development. Health Secur. 18 , 59–60 (2020).

Excler, J. L. & Kim, J. H. Novel prime-boost vaccine strategies against HIV-1. Expert Rev. Vaccines 18 , 765–779 (2019).

European Pharmaceutical Review. AstraZeneca to test combination of AZD1222 and Sputnik V vaccines. https://www.europeanpharmaceuticalreview.com/news/136683/astrazeneca-to-test-combination-of-azd1222-and-sputnik-v-vaccines/ (2020).

World Health Organization. Draft landscape and tracker of COVID-19 candidate vaccines. https://www.who.int/publications/m/item/draft-landscape-of-covid-19-candidate-vaccines (2021).

Fritzell, B. Bridging studies. Dev. Biol. Stand. 95 , 181–188 (1998).

CAS   PubMed   Google Scholar  

WHO Ad Hoc Expert Group on the Next Steps for Covid-19 Vaccine Evaluation. Placebo-controlled trials of Covid-19 vaccines—why we still need them. N. Engl. J. Med . 384 , e2 (2021).

Clemens, J., Brenner, R., Rao, M., Tafari, N. & Lowe, C. Evaluating new vaccines for developing countries. Efficacy or effectiveness? JAMA 275 , 390–397 (1996).

Kim, J. H., Marks, F. & Clemens, J. D. Looking beyond COVID-19 vaccine phase 3 trials. Nat. Med. 27 , 205–211 (2021).

Follmann, D. et al. Assessing durability of vaccine effect following blinded crossover in COVID-19 vaccine efficacy trials. Preprint at https://www.medrxiv.org/content/10.1101/2020.12.14.20248137v1 (2020).

World Health Organization. Global Advisory Committee on Vaccine Safety, 27–28 May 2020. https://www.who.int/vaccine_safety/committee/reports/May_2020/en/ (2020).

World Health Organization. COVID-19 vaccines: safety surveillance manual. https://apps.who.int/iris/handle/10665/338400 (2020).

European Medicines Agency. Pharmacovigilance plan of the EU Regulatory Network for COVID-19 Vaccines. https://www.ema.europa.eu/en/documents/other/pharmacovigilance-plan-eu-regulatory-network-covid-19-vaccines_en.pdf (2020).

Lee, G. M., Romero, J. R. & Bell, B. P. Postapproval vaccine safety surveillance for COVID-19 vaccines in the US. JAMA 324 , 1937–1938 (2020).

Kieny, M. P. & Rago, L. Regulatory policy for research and development of vaccines for public health emergencies. Expert Rev. Vaccines 15 , 1075–1077 (2016).

Lambert, P. H. et al. Consensus summary report for CEPI/BC March 12–13, 2020 meeting: assessment of risk of disease enhancement with COVID-19 vaccines. Vaccine 38 , 4783–4791 (2020).

Zellweger, R. M., Wartel, T. A., Marks, F., Song, M. & Kim, J. H. Vaccination against SARS-CoV-2 and disease enhancement - knowns and unknowns. Expert Rev. Vaccines 19 , 691–698 (2020).

Creanga, A. A. et al. Severity of 2009 pandemic influenza A (H1N1) virus infection in pregnant women. Obstet. Gynecol. 115 , 717–726 (2010).

Menendez, C., Lucas, A., Munguambe, K. & Langer, A. Ebola crisis: the unequal impact on women and children’s health. Lancet Glob. Health 3 , e130 (2015).

The PREVENT Working Group. Pregnant women and vaccines against emerging epidemic threats: ethics guidance on preparedness, research and response. http://vax.pregnancyethics.org/prevent-guidance (2018).

Krubiner, C. B. et al. Pregnant women and vaccines against emerging epidemic threats: ethics guidance for preparedness, research, and response. Vaccine 39 , 85–120 (2021).

Edridge, A. W. D. et al. Seasonal coronavirus protective immunity is short-lasting. Nat. Med. 26 , 1691–1693 (2020).

Plante, J. A. et al. Spike mutation D614G alters SARS-CoV-2 fitness. Nature https://doi.org/10.1038/s41586-020-2895-3 (2020).

Korber, B. et al. Tracking changes in SARS-CoV-2 spike: evidence that D614G increases infectivity of the COVID-19 virus. Cell 182 , 812–827 (2020).

Hou, Y. J. et al. SARS-CoV-2 D614G variant exhibits efficient replication ex vivo and transmission in vivo. Science 370 , 1464–1468 (2020).

Volz, E. et al. Evaluating the effects of SARS-CoV-2 spike mutation D614G on transmissibility and pathogenicity. Cell 184 , 64–75.e11 (2021).

Faria, N. R. Genomic characterisation of an emergent SARS-CoV-2 lineage in Manaus: preliminary findings. Virological https://virological.org/t/586 (2020).

Wibmer, C. K. et al. SARS-CoV-2 501Y.V2 escapes neutralization by South African COVID-19 donor plasma. Preprint at bioRxiv https://doi.org/10.1101/2021.01.18.427166 (2021).

BBC. Covid: South Africa halts AstraZeneca vaccine rollout over new variant. https://www.bbc.com/news/world-africa-55975052 (2021).

Mahase, E. Covid-19: Novavax vaccine efficacy is 86% against UK variant and 60% against South African variant. BMJ 372 , n296 (2021).

Johnson & Johnson. Johnson & Johnson announces single-shot Janssen COVID-19 vaccine candidate met primary endpoints in interim analysis of its phase 3 ENSEMBLE trial. https://www.jnj.com/johnson-johnson-announces-single-shot-janssen-covid-19-vaccine-candidate-met-primary-endpoints-in-interim-analysis-of-its-phase-3-ensemble-trial (2021).

World Health Organization. Global Influenza Surveillance and Response System (GISRS). https://www.who.int/influenza/gisrs_laboratory/en/

US Food and Drug Administration. Emergency use authorization. https://www.fda.gov/emergency-preparedness-and-response/mcm-legal-regulatory-and-policy-framework/emergency-use-authorization (2021).

European Medicines Agency. Conditional marketing authorization. https://www.ema.europa.eu/en/human-regulatory/marketing-authorisation/conditional-marketing-authorisation (2020).

Smith, M. J., Ujewe, S., Katz, R. & Upshur, R. E. G. Emergency use authorisation for COVID-19 vaccines: lessons from Ebola. Lancet 396 , 1707–1709 (2020).

World Health Organization. Emergency use listing procedure. https://www.who.int/publications/m/item/emergency-use-listing-procedure (2020).

Pharmaceutical Technology. Russia approves Sputnik V Covid-19 vaccine for senior citizens. https://www.pharmaceutical-technology.com/news/russia-sputnik-senior-citizens/ (2021).

Logunov, D. Y. et al. Safety and efficacy of an rAd26 and rAd5 vector-based heterologous prime-boost COVID-19 vaccine: an interim analysis of a randomised controlled phase 3 trial in Russia. Lancet https://doi.org/10.1016/S0140-6736(21)00234-8 (2021).

Xinhuanet. China approves first self-developed COVID-19 vaccine. http://www.xinhuanet.com/english/2020-12/31/c_139632402.htm (2020).

Sinopharm. China grants conditional market approval for Sinopharm CNBG’s COVID-19 vaccine. http://www.sinopharm.com/en/s/1395-4173-38862.html (2021).

CNBC. Dubai is offering the Pfizer vaccine to residents for free in addition to China’s Sinopharm shot. https://www.cnbc.com/2020/12/23/dubai-offering-pfizer-sinopharm-covid-vaccines-to-residents-for-free.html (2020).

Reuters. China approves Sinovac Biotech COVID-19 vaccine for general public use. https://www.reuters.com/article/us-health-coronavirus-vaccine-sinovac-idUSKBN2A60AY (2021).

Reuters. Pakistan approves Chinese CanSinoBIO COVID vaccine for emergency use. https://www.reuters.com/article/us-health-coronavirus-pakistan-vaccine/pakistan-approves-chinese-cansinobio-covid-vaccine-for-emergency-use-idUSKBN2AC1FG (2021).

Euronews. Coronavirus: 15m people in the UK have now had their first COVID jab—what about wider Europe? https://www.euronews.com/2021/02/14/coronavirus-15m-people-in-the-uk-have-now-had-their-first-covid-jab-what-about-wider-europ (2021).

Deng, C. & Malsin, J. China’s Covid-19 vaccine makers struggle to meet demand. The Wall Street Journal https://www.wsj.com/articles/chinas-covid-19-vaccine-makers-struggle-to-meet-demand-11612958560 (10 February 2021).

Pagliusi, S. et al. Developing countries vaccine manufacturers network: doing good by making high-quality vaccines affordable for all. Vaccine 31 , B176–B183 (2013).

Jadhav, S., Gautam, M. & Gairola, S. Role of vaccine manufacturers in developing countries towards global healthcare by providing quality vaccines at affordable prices. Clin. Microbiol. Infect. 20 , 37–44 (2014).

Kim, J. H. SARS-CoV-2 vaccine development, access, and equity. J. Exp. Med. 217 , e20201288 (2020).

Nhamo, G., Chikodzi, D., Kunene, H. P. & Mashula, N. COVID-19 vaccines and treatments nationalism: challenges for low-income countries and the attainment of the SDGs. Glob. Public Health 16 , 319–339 (2020).

World Bank. Global economy to expand by 4% in 2021; vaccine deployment and investment key to sustaining the recovery. https://www.worldbank.org/en/news/press-release/2021/01/05/global-economy-to-expand-by-4-percent-in-2021-vaccine-deployment-and-investment-key-to-sustaining-the-recovery (2021).

UN News. WHO chief warns against ‘catastrophic moral failure’ in COVID-19 vaccine access. https://news.un.org/en/story/2021/01/1082362 (18 January 2021).

Chinazzi, M. et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science 368 , 395–400 (2020).

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J.-L.E., M.S., S.B. and J.H.K. equally contributed to the synopsis of the manuscript. J.-L.E. and J.H.K. wrote the text and tables of the manuscript. J.H.K. provided the figure. M.S. and S.B. edited the manuscript.

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J.-L.E. is a consultant for vaccine safety for the Brighton Collaboration, Johnson & Johnson and the US Military HIV Research Program. J.H.K. is a consultant to SK Bioscience. M.S. has a financial interest in Sanofi (shares). S.B. does not have any financial or nonfinancial conflicts of interest.

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Excler, JL., Saville, M., Berkley, S. et al. Vaccine development for emerging infectious diseases. Nat Med 27 , 591–600 (2021). https://doi.org/10.1038/s41591-021-01301-0

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Human populations that hunt, butcher, and sell bushmeat (bushmeat activities) are at increased risk for zoonotic pathogen spillover. Despite associations with global epidemics of severe illnesses, such as Ebola and mpox, quantitative assessments of bushmeat activities are lacking. However, such assessments could help prioritize pandemic prevention and preparedness efforts. We used geospatial models that combined published data on bushmeat activities and ecologic and demographic drivers to map the distribution of bushmeat activities in rural regions globally. The resulting map had high predictive capacity for bushmeat activities (true skill statistic = 0.94). The model showed that mammal species richness and deforestation were principal drivers of the geographic distribution of bushmeat activities and that countries in West and Central Africa had the highest proportion of land area associated with bushmeat activities. These findings could help prioritize future surveillance of bushmeat activities and forecast emerging zoonoses at a global scale.

During April–July 2022, outbreaks of severe acute hepatitis of unknown etiology (SAHUE) were reported in 35 countries. Five percent of cases required liver transplantation, and 22 patients died. Viral metagenomic studies of clinical samples from SAHUE cases showed a correlation with human adenovirus F type 41 (HAdV-F41) and adeno-associated virus type 2 (AAV2). To explore the association between those DNA viruses and SAHUE in children in Ireland, we quantified HAdV-F41 and AAV2 in samples collected from a wastewater treatment plant serving 40% of Ireland’s population. We noted a high correlation between HAdV-F41 and AAV2 circulation in the community and SAHUE clinical cases. Next-generation sequencing of the adenovirus hexon in wastewater demonstrated HAdV-F41 was the predominant HAdV type circulating. Our environmental analysis showed increased HAdV-F41 and AAV2 prevalence in the community during the SAHUE outbreak. Our findings highlight how wastewater sampling could aid in surveillance for respiratory adenovirus species.

SARS-CoV-2 infections among vaccinated nursing home residents increased after the Omicron variant emerged. Data on booster dose effectiveness in this population are limited. During July 2021–March 2022, nursing home outbreaks in 11 US jurisdictions involving > 3 infections within 14 days among residents who had received at least the primary COVID-19 vaccine(s) were monitored. Among 2,188 nursing homes, 1,247 outbreaks were reported in the periods of Delta (n = 356, 29%), mixed Delta/Omicron (n = 354, 28%), and Omicron (n = 536, 43%) predominance. During the Omicron-predominant period, the risk for infection within 14 days of an outbreak start was lower among boosted residents than among residents who had received the primary vaccine series alone (risk ratio [RR] 0.25, 95% CI 0.19–0.33). Once infected, boosted residents were at lower risk for all-cause hospitalization (RR 0.48, 95% CI 0.40–0.49) and death (RR 0.45, 95% CI 0.34–0.59) than primary vaccine–only residents.

We assessed effectiveness of the BNT162b2 vaccine against infection with the B.1.1.529 (Omicron) variant (mostly BA.1 subvariant), among children 5–11 years of age in Israel. Using a matched case–control design, we matched SARS-CoV-2–positive children (cases) and SARS-CoV-2–negative children (controls) by age, sex, population group, socioeconomic status, and epidemiologic week. Vaccine effectiveness estimates after the second vaccine dose were 58.1% for days 8–14, 53.9% for days 15–21, 46.7% for days 22–28, 44.8% for days 29–35, and 39.5% for days 36–42. Sensitivity analyses by age group and period demonstrated similar results. Vaccine effectiveness against Omicron infection among children 5–11 years of age was lower than vaccine efficacy and vaccine effectiveness against non-Omicron variants, and effectiveness declined early and rapidly.

Mpox was diagnosed in 2 women returning to Vietnam from the United Arab Emirates. The monkeypox viruses belonged to an emerging sublineage, A.2.1, distinct from B.1, which is responsible for the ongoing multicountry outbreak. Women could contribute to mpox transmission, and enhanced genomic surveillance is needed to clarify pathogen evolution.

We assessed susceptibility of dogs to SARS-COV-2 Delta and Omicron variants by experimentally inoculating beagle dogs. Moreover, we investigated transmissibility of the variants from infected to naive dogs. The dogs were susceptible to infection without clinical signs and transmitted both strains to other dogs through direct contact.

We report the spillover of highly pathogenic avian influenza A(H5N1) into marine mammals in the northeastern United States, coincident with H5N1 in sympatric wild birds. Our data indicate monitoring both wild coastal birds and marine mammals will be critical to determine pandemic potential of influenza A viruses.

Since April 2022, waves of SARS-CoV-2 Omicron variant cases have surfaced in Taiwan and spread throughout the island. Using high-throughput sequencing of the SARS-CoV-2 genome, we analyzed 2,405 PCR-positive swab samples from 2,339 persons and identified the Omicron BA.2.3.7 variant as a major lineage within recent community outbreaks in Taiwan.

We identified Yezo virus infection in a febrile patient who had a tick bite in northeastern China, where 0.5% of Ixodes persulcatus ticks were positive for viral RNA. Clinicians should be aware of this potential health threat and include this emerging virus in the differential diagnosis for tick-bitten patients in this region.

We describe the influence of seasonal meteorologic variations and rainfall events on Anopheles stephensi mosquito populations during a 40-month surveillance study at a US military base in Djibouti. Focusing surveillance and risk mitigation for An. stephensi mosquitoes when climatic conditions are optimal presents an opportunity for malaria prevention and control in eastern Africa.

Tularemia was diagnosed for a 33-year-old pregnant woman in Serbia after a swollen neck lymph node was detected at gestation week 18. Gentamicin was administered parenterally (120 mg/d for 7 d); the pregnancy continued with no complications and a healthy newborn was delivered. Treatment of tularemia optimizes maternal and infant outcomes.

Using histopathology and phylogenetic analysis of the internal transcribed spacer 2 gene, we found > 2 distinct trematode species that caused ocular trematode infections in children in Sri Lanka. Collaborations between clinicians and parasitologists and community awareness of water-related contamination hazards will promote diagnosis, control, and prevention of ocular trematode infections.

We compared serial intervals and incubation periods for SARS-CoV-2 Omicron BA.1 and BA.2 subvariants and Delta variants in Singapore. Median incubation period was 3 days for BA.1 versus 4 days for Delta. Serial interval was 2 days for BA.1 and 3 days for BA.2 but 4 days for Delta.

Using data from 12 US health departments, we estimated mean serial interval for monkeypox virus infection to be 8.5 (95% credible interval 7.3–9.9) days for symptom onset, based on 57 case pairs. Mean estimated incubation period was 5.6 (95% credible interval 4.3–7.8) days for symptom onset, based on 35 case pairs.

We performed a follow-up of a previously reported SARS-CoV-2 prevalence study (April‒May 2020) in Verona, Italy. Through May 2022, only <1.1% of the city population had never been infected or vaccinated; 8.8% was the officially reported percentage. Limiting protection measures and vaccination boosters to elderly and frail persons seems justified.

During 2019–2020, a chikungunya outbreak occurred in Djibouti City, Djibouti, while dengue virus and malaria parasites were cocirculating. We used blotting paper to detect arbovirus emergence and confirm that it is a robust method for detecting and monitoring arbovirus outbreaks remotely.

Causes of blackwater fever, a complication of malaria treatment, are not completely clear, and immune mechanisms might be involved. Clinical management is not standardized. We describe an episode of blackwater fever in a nonimmune 12-year-old girl in Italy who was treated with steroids, resulting in a rapid clinical resolution.

We report the isolation of Helicobacter ailurogastricus , a Helicobacter species that infects cats and dogs, from a person with multiple refractory gastric ulcers. In addition to H. suis , which infects pigs, Helicobacter species that infect cats and dogs should be considered as potential gastric pathogens in humans.

In August 2021, a large-scale mortality event affected harbor porpoises ( Phocoena phocoena ) in the Netherlands. Pathology and ancillary testing of 22 animals indicated that the most likely cause of death was Erysipelothrix rhusiopathiae infection. This zoonotic agent poses a health hazard for cetaceans and possibly for persons handling cetacean carcasses.

We describe a 4-year-old male patient in Ohio, USA, who had encephalitis caused by Powassan virus lineage 2. Virus was detected by using metagenomic next-generation sequencing and confirmed with IgM and plaque reduction neutralization assays. Clinicians should recognize changing epidemiology of tickborne viruses to enhance encephalitis diagnosis and management.

Hamadryas baboons ( Papio hamadryas ) may transmit zoonotic vector-borne pathogens to visitors and workers frequenting zoological parks. We molecularly screened 33 baboons for vector-borne pathogens. Three (9.1%) of 33 animals tested positive for Rickettsia conorii subspecies israelensis . Clinicians should be aware of potential health risks from spatial overlapping between baboons and humans.

Thelazia callipaeda is a zoonotic vector-borne nematode that infects and causes eye disease among a wide range of domestic and wild mammals, including humans. We describe an unusual case of reinfection by this nematode in Serbia and call for a focus on preventive measures in endemic areas.

We describe a case of mpox characterized by a circularly distributed facial rash but no identified risk factors. Fomite transmission of monkeypox virus from contaminated linen at a massage spa was suspected. Clinicians should consider mpox in patients with consistent clinical syndromes, even in the absence of epidemiologic risk factors.

We retrospectively screened oropharyngeal and rectal swab samples originally collected in California, USA, for Chlamydia trachomatis and Neisseria gonorrhoeae testing for the presence of monkeypox virus DNA. Among 206 patients screened, 17 (8%) had samples with detectable viral DNA. Monkeypox virus testing from mucosal sites should be considered for at-risk patients.

We describe an unusual outbreak of respiratory infections caused by human metapneumovirus in children during the sixth wave of COVID-19 in Spain, associated with the Omicron variant. Patients in this outbreak were older than usual and showed more hypoxia and pneumonia, longer length of stay, and greater need for intensive care.

We found highly pathogenic avian influenza A(H5N1) virus clade 2.3.4.4b associated with meningoencephalitis in a stranded harbor porpoise ( Phocoena phocoena ). The virus was closely related to strains responsible for a concurrent avian influenza outbreak in wild birds. This case highlights the potential risk for virus spillover to mammalian hosts.

We reconstructed the SARS-CoV-2 epidemic caused by Omicron variant in Puerto Rico by sampling genomes collected during October 2021–May 2022. Our study revealed that Omicron BA.1 emerged and replaced Delta as the predominant variant in December 2021. Increased transmission rates and a dynamic landscape of Omicron sublineage infections followed.

The global spread of monkeypox virus has raised concerns over the establishment of novel enzootic reservoirs in expanded geographic regions. We demonstrate that although deer mice are permissive to experimental infection with clade I and II monkeypox viruses, the infection is short-lived and has limited capability for active transmission.

A 26-year-old patient in France who worked as a butcher sought care initially for erythema multiforme. Clinical examination revealed a nodule with a crusty center, which upon investigation appeared to be an orf nodule. Diagnosis was confirmed by PCR. The patient was not isolated and had a favorable outcome after basic wound care.

To assess dynamics of SARS-CoV-2 in Greater Accra Region, Ghana, we analyzed SARS-CoV-2 genomic sequences from persons in the community and returning from international travel. The Accra Metropolitan District was a major origin of virus spread to other districts and should be a primary focus for interventions against future infectious disease outbreaks.

We sequenced 54 respiratory syncytial virus (RSV) genomes collected during 2021–22 and 2022–23 outbreaks in Washington, USA, to determine the origin of increased RSV cases. Detected RSV strains have been spreading for >10 years, suggesting a role for diminished population immunity from low RSV exposure during the COVID-19 pandemic.

Substantial investments into laboratories, notably sophisticated equipment, have been made over time to detect emerging diseases close to their source. Diagnostic capacity has expanded as a result, but challenges have emerged. The Equipment Management and Sustainability Survey was sent to the Veterinary Services of 182 countries in mid-2019. We measured the status of forty types of laboratory equipment used in veterinary diagnostic laboratories. Of the 68,455 items reported from 227 laboratories in 136 countries, 22% (14,894/68,455) were improperly maintained, and 46% (29,957/65,490) were improperly calibrated. Notable differences were observed across World Bank income levels and regions, raising concerns about equipment reliability and the results they produce. Our results will advise partners and donors on how best to support low-resource veterinary laboratories to improve sustainability and fulfill their mandate toward pandemic prevention and preparedness, as well as encourage equipment manufacturers to spur innovation and develop more sustainable products that meet end-users’ needs.

Crimean-Congo Hemorrhagic Fever Virus for Clinicians-An Overview — (Length: 26:14)

Length: 26:14

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