How to Write About Coronavirus in a College Essay

Students can share how they navigated life during the coronavirus pandemic in a full-length essay or an optional supplement.

Writing About COVID-19 in College Essays

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Experts say students should be honest and not limit themselves to merely their experiences with the pandemic.

The global impact of COVID-19, the disease caused by the novel coronavirus, means colleges and prospective students alike are in for an admissions cycle like no other. Both face unprecedented challenges and questions as they grapple with their respective futures amid the ongoing fallout of the pandemic.

Colleges must examine applicants without the aid of standardized test scores for many – a factor that prompted many schools to go test-optional for now . Even grades, a significant component of a college application, may be hard to interpret with some high schools adopting pass-fail classes last spring due to the pandemic. Major college admissions factors are suddenly skewed.

"I can't help but think other (admissions) factors are going to matter more," says Ethan Sawyer, founder of the College Essay Guy, a website that offers free and paid essay-writing resources.

College essays and letters of recommendation , Sawyer says, are likely to carry more weight than ever in this admissions cycle. And many essays will likely focus on how the pandemic shaped students' lives throughout an often tumultuous 2020.

But before writing a college essay focused on the coronavirus, students should explore whether it's the best topic for them.

Writing About COVID-19 for a College Application

Much of daily life has been colored by the coronavirus. Virtual learning is the norm at many colleges and high schools, many extracurriculars have vanished and social lives have stalled for students complying with measures to stop the spread of COVID-19.

"For some young people, the pandemic took away what they envisioned as their senior year," says Robert Alexander, dean of admissions, financial aid and enrollment management at the University of Rochester in New York. "Maybe that's a spot on a varsity athletic team or the lead role in the fall play. And it's OK for them to mourn what should have been and what they feel like they lost, but more important is how are they making the most of the opportunities they do have?"

That question, Alexander says, is what colleges want answered if students choose to address COVID-19 in their college essay.

But the question of whether a student should write about the coronavirus is tricky. The answer depends largely on the student.

"In general, I don't think students should write about COVID-19 in their main personal statement for their application," Robin Miller, master college admissions counselor at IvyWise, a college counseling company, wrote in an email.

"Certainly, there may be exceptions to this based on a student's individual experience, but since the personal essay is the main place in the application where the student can really allow their voice to be heard and share insight into who they are as an individual, there are likely many other topics they can choose to write about that are more distinctive and unique than COVID-19," Miller says.

Opinions among admissions experts vary on whether to write about the likely popular topic of the pandemic.

"If your essay communicates something positive, unique, and compelling about you in an interesting and eloquent way, go for it," Carolyn Pippen, principal college admissions counselor at IvyWise, wrote in an email. She adds that students shouldn't be dissuaded from writing about a topic merely because it's common, noting that "topics are bound to repeat, no matter how hard we try to avoid it."

Above all, she urges honesty.

"If your experience within the context of the pandemic has been truly unique, then write about that experience, and the standing out will take care of itself," Pippen says. "If your experience has been generally the same as most other students in your context, then trying to find a unique angle can easily cross the line into exploiting a tragedy, or at least appearing as though you have."

But focusing entirely on the pandemic can limit a student to a single story and narrow who they are in an application, Sawyer says. "There are so many wonderful possibilities for what you can say about yourself outside of your experience within the pandemic."

He notes that passions, strengths, career interests and personal identity are among the multitude of essay topic options available to applicants and encourages them to probe their values to help determine the topic that matters most to them – and write about it.

That doesn't mean the pandemic experience has to be ignored if applicants feel the need to write about it.

Writing About Coronavirus in Main and Supplemental Essays

Students can choose to write a full-length college essay on the coronavirus or summarize their experience in a shorter form.

To help students explain how the pandemic affected them, The Common App has added an optional section to address this topic. Applicants have 250 words to describe their pandemic experience and the personal and academic impact of COVID-19.

"That's not a trick question, and there's no right or wrong answer," Alexander says. Colleges want to know, he adds, how students navigated the pandemic, how they prioritized their time, what responsibilities they took on and what they learned along the way.

If students can distill all of the above information into 250 words, there's likely no need to write about it in a full-length college essay, experts say. And applicants whose lives were not heavily altered by the pandemic may even choose to skip the optional COVID-19 question.

"This space is best used to discuss hardship and/or significant challenges that the student and/or the student's family experienced as a result of COVID-19 and how they have responded to those difficulties," Miller notes. Using the section to acknowledge a lack of impact, she adds, "could be perceived as trite and lacking insight, despite the good intentions of the applicant."

To guard against this lack of awareness, Sawyer encourages students to tap someone they trust to review their writing , whether it's the 250-word Common App response or the full-length essay.

Experts tend to agree that the short-form approach to this as an essay topic works better, but there are exceptions. And if a student does have a coronavirus story that he or she feels must be told, Alexander encourages the writer to be authentic in the essay.

"My advice for an essay about COVID-19 is the same as my advice about an essay for any topic – and that is, don't write what you think we want to read or hear," Alexander says. "Write what really changed you and that story that now is yours and yours alone to tell."

Sawyer urges students to ask themselves, "What's the sentence that only I can write?" He also encourages students to remember that the pandemic is only a chapter of their lives and not the whole book.

Miller, who cautions against writing a full-length essay on the coronavirus, says that if students choose to do so they should have a conversation with their high school counselor about whether that's the right move. And if students choose to proceed with COVID-19 as a topic, she says they need to be clear, detailed and insightful about what they learned and how they adapted along the way.

"Approaching the essay in this manner will provide important balance while demonstrating personal growth and vulnerability," Miller says.

Pippen encourages students to remember that they are in an unprecedented time for college admissions.

"It is important to keep in mind with all of these (admission) factors that no colleges have ever had to consider them this way in the selection process, if at all," Pippen says. "They have had very little time to calibrate their evaluations of different application components within their offices, let alone across institutions. This means that colleges will all be handling the admissions process a little bit differently, and their approaches may even evolve over the course of the admissions cycle."

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  • Patient Care & Health Information
  • Diseases & Conditions
  • Coronavirus disease 2019 (COVID-19)

COVID-19, also called coronavirus disease 2019, is an illness caused by a virus. The virus is called severe acute respiratory syndrome coronavirus 2, or more commonly, SARS-CoV-2. It started spreading at the end of 2019 and became a pandemic disease in 2020.

Coronavirus

  • Coronavirus

Coronaviruses are a family of viruses. These viruses cause illnesses such as the common cold, severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and coronavirus disease 2019 (COVID-19).

The virus that causes COVID-19 spreads most commonly through the air in tiny droplets of fluid between people in close contact. Many people with COVID-19 have no symptoms or mild illness. But for older adults and people with certain medical conditions, COVID-19 can lead to the need for care in the hospital or death.

Staying up to date on your COVID-19 vaccine helps prevent serious illness, the need for hospital care due to COVID-19 and death from COVID-19 . Other ways that may help prevent the spread of this coronavirus includes good indoor air flow, physical distancing, wearing a mask in the right setting and good hygiene.

Medicine can limit the seriousness of the viral infection. Most people recover without long-term effects, but some people have symptoms that continue for months.

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Typical COVID-19 symptoms often show up 2 to 14 days after contact with the virus.

Symptoms can include:

  • Shortness of breath.
  • Loss of taste or smell.
  • Extreme tiredness, called fatigue.
  • Digestive symptoms such as upset stomach, vomiting or loose stools, called diarrhea.
  • Pain, such as headaches and body or muscle aches.
  • Fever or chills.
  • Cold-like symptoms such as congestion, runny nose or sore throat.

People may only have a few symptoms or none. People who have no symptoms but test positive for COVID-19 are called asymptomatic. For example, many children who test positive don't have symptoms of COVID-19 illness. People who go on to have symptoms are considered presymptomatic. Both groups can still spread COVID-19 to others.

Some people may have symptoms that get worse about 7 to 14 days after symptoms start.

Most people with COVID-19 have mild to moderate symptoms. But COVID-19 can cause serious medical complications and lead to death. Older adults or people who already have medical conditions are at greater risk of serious illness.

COVID-19 may be a mild, moderate, severe or critical illness.

  • In broad terms, mild COVID-19 doesn't affect the ability of the lungs to get oxygen to the body.
  • In moderate COVID-19 illness, the lungs also work properly but there are signs that the infection is deep in the lungs.
  • Severe COVID-19 means that the lungs don't work correctly, and the person needs oxygen and other medical help in the hospital.
  • Critical COVID-19 illness means the lung and breathing system, called the respiratory system, has failed and there is damage throughout the body.

Rarely, people who catch the coronavirus can develop a group of symptoms linked to inflamed organs or tissues. The illness is called multisystem inflammatory syndrome. When children have this illness, it is called multisystem inflammatory syndrome in children, shortened to MIS -C. In adults, the name is MIS -A.

When to see a doctor

Contact a healthcare professional if you test positive for COVID-19 . If you have symptoms and need to test for COVID-19 , or you've been exposed to someone with COVID-19 , a healthcare professional can help.

People who are at high risk of serious illness may get medicine to block the spread of the COVID-19 virus in the body. Or your healthcare team may plan regular checks to monitor your health.

Get emergency help right away for any of these symptoms:

  • Can't catch your breath or have problems breathing.
  • Skin, lips or nail beds that are pale, gray or blue.
  • New confusion.
  • Trouble staying awake or waking up.
  • Chest pain or pressure that is constant.

This list doesn't include every emergency symptom. If you or a person you're taking care of has symptoms that worry you, get help. Let the healthcare team know about a positive test for COVID-19 or symptoms of the illness.

More Information

  • COVID-19 vs. flu: Similarities and differences
  • COVID-19, cold, allergies and the flu
  • Unusual symptoms of coronavirus

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COVID-19 is caused by infection with the severe acute respiratory syndrome coronavirus 2, also called SARS-CoV-2.

The coronavirus spreads mainly from person to person, even from someone who is infected but has no symptoms. When people with COVID-19 cough, sneeze, breathe, sing or talk, their breath may be infected with the COVID-19 virus.

The coronavirus carried by a person's breath can land directly on the face of a nearby person, after a sneeze or cough, for example. The droplets or particles the infected person breathes out could possibly be breathed in by other people if they are close together or in areas with low air flow. And a person may touch a surface that has respiratory droplets and then touch their face with hands that have the coronavirus on them.

It's possible to get COVID-19 more than once.

  • Over time, the body's defense against the COVID-19 virus can fade.
  • A person may be exposed to so much of the virus that it breaks through their immune defense.
  • As a virus infects a group of people, the virus copies itself. During this process, the genetic code can randomly change in each copy. The changes are called mutations. If the coronavirus that causes COVID-19 changes in ways that make previous infections or vaccination less effective at preventing infection, people can get sick again.

The virus that causes COVID-19 can infect some pets. Cats, dogs, hamsters and ferrets have caught this coronavirus and had symptoms. It's rare for a person to get COVID-19 from a pet.

Risk factors

The main risk factors for COVID-19 are:

  • If someone you live with has COVID-19 .
  • If you spend time in places with poor air flow and a higher number of people when the virus is spreading.
  • If you spend more than 30 minutes in close contact with someone who has COVID-19 .

Many factors affect your risk of catching the virus that causes COVID-19 . How long you are in contact, if the space has good air flow and your activities all affect the risk. Also, if you or others wear masks, if someone has COVID-19 symptoms and how close you are affects your risk. Close contact includes sitting and talking next to one another, for example, or sharing a car or bedroom.

It seems to be rare for people to catch the virus that causes COVID-19 from an infected surface. While the virus is shed in waste, called stool, COVID-19 infection from places such as a public bathroom is not common.

Serious COVID-19 illness risk factors

Some people are at a higher risk of serious COVID-19 illness than others. This includes people age 65 and older as well as babies younger than 6 months. Those age groups have the highest risk of needing hospital care for COVID-19 .

Not every risk factor for serious COVID-19 illness is known. People of all ages who have no other medical issues have needed hospital care for COVID-19 .

Known risk factors for serious illness include people who have not gotten a COVID-19 vaccine. Serious illness also is a higher risk for people who have:

  • Sickle cell disease or thalassemia.
  • Serious heart diseases and possibly high blood pressure.
  • Chronic kidney, liver or lung diseases.

People with dementia or Alzheimer's also are at higher risk, as are people with brain and nervous system conditions such as stroke. Smoking increases the risk of serious COVID-19 illness. And people with a body mass index in the overweight category or obese category may have a higher risk as well.

Other medical conditions that may raise the risk of serious illness from COVID-19 include:

  • Cancer or a history of cancer.
  • Type 1 or type 2 diabetes.
  • Weakened immune system from solid organ transplants or bone marrow transplants, some medicines, or HIV .

This list is not complete. Factors linked to a health issue may raise the risk of serious COVID-19 illness too. Examples are a medical condition where people live in a group home, or lack of access to medical care. Also, people with more than one health issue, or people of older age who also have health issues have a higher chance of severe illness.

Related information

  • COVID-19: Who's at higher risk of serious symptoms? - Related information COVID-19: Who's at higher risk of serious symptoms?

Complications

Complications of COVID-19 include long-term loss of taste and smell, skin rashes, and sores. The illness can cause trouble breathing or pneumonia. Medical issues a person already manages may get worse.

Complications of severe COVID-19 illness can include:

  • Acute respiratory distress syndrome, when the body's organs do not get enough oxygen.
  • Shock caused by the infection or heart problems.
  • Overreaction of the immune system, called the inflammatory response.
  • Blood clots.
  • Kidney injury.

Post-COVID-19 syndrome

After a COVID-19 infection, some people report that symptoms continue for months, or they develop new symptoms. This syndrome has often been called long COVID, or post- COVID-19 . You might hear it called long haul COVID-19 , post-COVID conditions or PASC. That's short for post-acute sequelae of SARS -CoV-2.

Other infections, such as the flu and polio, can lead to long-term illness. But the virus that causes COVID-19 has only been studied since it began to spread in 2019. So, research into the specific effects of long-term COVID-19 symptoms continues.

Researchers do think that post- COVID-19 syndrome can happen after an illness of any severity.

Getting a COVID-19 vaccine may help prevent post- COVID-19 syndrome.

  • Long-term effects of COVID-19

The Centers for Disease Control and Prevention (CDC) recommends a COVID-19 vaccine for everyone age 6 months and older. The COVID-19 vaccine can lower the risk of death or serious illness caused by COVID-19.

The COVID-19 vaccines available in the United States are:

2023-2024 Pfizer-BioNTech COVID-19 vaccine. This vaccine is available for people age 6 months and older.

Among people with a typical immune system:

  • Children age 6 months up to age 4 years are up to date after three doses of a Pfizer-BioNTech COVID-19 vaccine.
  • People age 5 and older are up to date after one Pfizer-BioNTech COVID-19 vaccine.
  • For people who have not had a 2023-2024 COVID-19 vaccination, the CDC recommends getting an additional shot of that updated vaccine.

2023-2024 Moderna COVID-19 vaccine. This vaccine is available for people age 6 months and older.

  • Children ages 6 months up to age 4 are up to date if they've had two doses of a Moderna COVID-19 vaccine.
  • People age 5 and older are up to date with one Moderna COVID-19 vaccine.

2023-2024 Novavax COVID-19 vaccine. This vaccine is available for people age 12 years and older.

  • People age 12 years and older are up to date if they've had two doses of a Novavax COVID-19 vaccine.

In general, people age 5 and older with typical immune systems can get any vaccine approved or authorized for their age. They usually don't need to get the same vaccine each time.

Some people should get all their vaccine doses from the same vaccine maker, including:

  • Children ages 6 months to 4 years.
  • People age 5 years and older with weakened immune systems.
  • People age 12 and older who have had one shot of the Novavax vaccine should get the second Novavax shot in the two-dose series.

Talk to your healthcare professional if you have any questions about the vaccines for you or your child. Your healthcare team can help you if:

  • The vaccine you or your child got earlier isn't available.
  • You don't know which vaccine you or your child received.
  • You or your child started a vaccine series but couldn't finish it due to side effects.

People with weakened immune systems

Your healthcare team may suggest added doses of COVID-19 vaccine if you have a moderately or seriously weakened immune system. The FDA has also authorized the monoclonal antibody pemivibart (Pemgarda) to prevent COVID-19 in some people with weakened immune systems.

Control the spread of infection

In addition to vaccination, there are other ways to stop the spread of the virus that causes COVID-19 .

If you are at a higher risk of serious illness, talk to your healthcare professional about how best to protect yourself. Know what to do if you get sick so you can quickly start treatment.

If you feel ill or have COVID-19 , stay home and away from others, including pets, if possible. Avoid sharing household items such as dishes or towels if you're sick.

In general, make it a habit to:

  • Test for COVID-19 . If you have symptoms of COVID-19 test for the infection. Or test five days after you came in contact with the virus.
  • Help from afar. Avoid close contact with anyone who is sick or has symptoms, if possible.
  • Wash your hands. Wash your hands well and often with soap and water for at least 20 seconds. Or use an alcohol-based hand sanitizer with at least 60% alcohol.
  • Cover your coughs and sneezes. Cough or sneeze into a tissue or your elbow. Then wash your hands.
  • Clean and disinfect high-touch surfaces. For example, clean doorknobs, light switches, electronics and counters regularly.

Try to spread out in crowded public areas, especially in places with poor airflow. This is important if you have a higher risk of serious illness.

The CDC recommends that people wear a mask in indoor public spaces if you're in an area with a high number of people with COVID-19 in the hospital. They suggest wearing the most protective mask possible that you'll wear regularly, that fits well and is comfortable.

  • COVID-19 vaccines: Get the facts - Related information COVID-19 vaccines: Get the facts
  • Comparing the differences between COVID-19 vaccines - Related information Comparing the differences between COVID-19 vaccines
  • Different types of COVID-19 vaccines: How they work - Related information Different types of COVID-19 vaccines: How they work
  • Debunking COVID-19 myths - Related information Debunking COVID-19 myths

Travel and COVID-19

Travel brings people together from areas where illnesses may be at higher levels. Masks can help slow the spread of respiratory diseases in general, including COVID-19 . Masks help the most in places with low air flow and where you are in close contact with other people. Also, masks can help if the places you travel to or through have a high level of illness.

Masking is especially important if you or a companion have a high risk of serious illness from COVID-19 .

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  • Goldman L, et al., eds. COVID-19: Epidemiology, clinical manifestations, diagnosis, community prevention, and prognosis. In: Goldman-Cecil Medicine. 27th ed. Elsevier; 2024. https://www.clinicalkey.com. Accessed Dec. 17, 2023.
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Understanding COVID-19

How To Protect Yourself During the Pandemic

Illustration of two men wearing masks while sitting on park benches six feet apart

COVID-19 has claimed millions of lives around the world. But we learn more about this disease every day. Scientists are developing tools that promise to slow and eventu­ally help us overcome the pandemic.

COVID-19 is caused by a new coronavirus called SARS-CoV-2. There are many types of coronaviruses. Some cause the common cold. Others have led to fatal disease outbreaks. These include severe acute respiratory syndrome (SARS) in 2003, Middle East respiratory syndrome (MERS) in 2012, and now COVID-19.

Coronaviruses are named for the crown-like spikes on their surface. (Corona means crown.) The viruses use the spikes to help get inside your body’s cells. Once inside, they replicate, or make copies of themselves.

Scientists have learned how to turn these spikes against the virus through vaccines and treatments. They’ve also learned what you can do to protect yourself from the virus.

Protecting Yourself

You’re most likely to get COVID-19 through close contact with someone who’s infected. Coughing, sneezing, talking, and breathing produce small droplets of liquid. These are called respiratory droplets. They travel through the air and can be inhaled by someone else.

“COVID-19 is spread mainly through exposure to respiratory droplets that tend to drop within six feet,” says Dr. Anthony Fauci, director of NIH’s National Institute of Allergy and Infectious Diseases. That’s why it’s important to stay at least six feet (about two arm lengths) away from people who don’t live with you.

“Surfaces can be contaminated. But it is likely that this is a less common cause of infection rather than person-to-person directly,” Fauci says.

You can protect yourself and others by wearing a mask. Choose one that has at least two layers of fabric. Make sure that the mask covers your mouth and nose and doesn’t leak air around the edges.

“There’s very little transmission in places where masks are worn,” says Dr. Ben Cowling at the University of Hong Kong who studies how viruses spread. Cowling found that infections were most often spread in settings where masks aren’t worn.

“Masks work. But even with mandatory masking, you still need social distancing as well,” he says. You can lower your risk by avoiding crowds. Crowds increase the risk of coming in contact with someone who has COVID-19.

What to Look For

Common symptoms of COVID-19 include fever, cough, headaches, fatigue, and muscle or body aches. People with COVID-19 may also lose their sense of smell or taste. Symptoms usually appear two to 14 days after being exposed to the virus.

But even people who don’t seem sick can still infect others. The CDC estimates that 50% of infections are spread by people with no symptoms. While some with this virus develop life-threatening illness, others have mild symptoms, and some never develop any.

Catching the virus is more dangerous for some groups of people. This includes older adults and people with certain medical conditions. These medical conditions include obesity, diabetes, heart and lung disease, and asthma. About 40% of Americans have at least one of these risk factors.

Getting Treatment

Better COVID-19 treatments mean that fewer people now get severely sick if they catch the virus. Scientists have been working to test available drugs against the virus. They’ve found at least two that can help people who are hospitalized with the virus.

A drug called remdesivir can reduce the time a patient spends in the hospital. A steroid called dexamethasone helps stop the immune system The system that protects your body from invading viruses, bacteria, and other microscopic threats. from reacting too strongly to the virus. That can damage body tissues and organs.

Antibody treatments are also available. Antibodies are proteins that your body makes to fight germs. Scientists have learned how to make them in the lab. Antibody treatments can block SARS-CoV-2 to prevent the illness from getting worse. They seem to have the most benefit when given early in the disease.

“Antibody treatments really do have the potential to help people, especially for treating individuals who are not yet hospitalized,” says Dr. Mark Heise, who studies the genetics of viruses at the University of North Carolina at Chapel Hill. Heise is working to develop mouse models to test treatments and vaccines.

Studies are now testing combinations of treatments. “Combining drugs that target both the virus and the person’s immune response may help treat COVID-19,” says Heise. Scientists are also looking for new drugs that better target the virus.

A Shot of Hope: Vaccines

It used to take a decade or more to develop a new vaccine. In this pandemic, scientists created COVID-19 vaccines in less than a year.

The first two vaccines approved for emergency use are from Moderna and Pfizer/BioNTech. Moderna’s vaccine was co-developed with NIH scientists. Both are a new type of vaccine called mRNA vaccines. mRNA carries the genetic information for your body to make proteins.

The vaccines direct the body’s cells to make a piece of the virus called the spike protein. These proteins can’t cause illness by themselves. But they teach your immune system to make antibodies against the protein. If you encounter the virus later, the antibodies provide protection against it.

The mRNA vaccines now available were shown to be more than 90% effective in large clinical trials. They can cause side effects—such as fatigue, muscle aches, joint pain, and headache. But both vaccines were found to be safe in the clinical trials.

“Get vaccinated. The vaccines are safe. They’re incredibly effective,” says Dr. Jason McLellan, an expert on coronaviruses at the University of Texas at Austin. McLellan’s research was critical in developing these vaccines. His team, along with NIH scientists, figured out how to lock the shape of the spike protein to make the most effective antibodies.

As the pandemic has gone on, new versions of the virus, or variants, have appeared. “We’re all very confident that vaccines will continue to work well against these variants,” McLellan says. “Vaccination also helps stop the development of new variants, because it provides fewer opportunities for the virus to change as it replicates.”

Many people will need to be vaccinated for the pandemic to end. Fauci estimates that 70% to 85% of the U.S. population will need to be vaccinated to get “herd immunity.” That’s the point where enough people are immune to the virus to prevent its spread. That’s important because it protects vulnerable people who can’t get vaccinated.

“It is my hope that all Americans will protect themselves by getting vaccinated when the vaccine becomes available to them,” Fauci says. “That is how our country will begin to heal and move forward.”

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Special Issue: COVID-19

This essay was published as part of a Special Issue on Misinformation and COVID-19, guest-edited by Dr. Meghan McGinty (Director of Emergency Management, NYC Health + Hospitals) and Nat Gyenes (Director, Meedan Digital Health Lab).

Peer Reviewed

The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media

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We investigate the relationship between media consumption, misinformation, and important attitudes and behaviours during the coronavirus disease 2019 (COVID-19) pandemic. We find that comparatively more misinformation circulates on Twitter, while news media tends to reinforce public health recommendations like social distancing. We find that exposure to social media is associated with misperceptions regarding basic facts about COVID-19 while the inverse is true for news media. These misperceptions are in turn associated with lower compliance with social distancing measures. We thus draw a clear link from misinformation circulating on social media, notably Twitter, to behaviours and attitudes that potentially magnify the scale and lethality of COVID-19.

Department of Political Science, McGill University, Canada

Munk School of Global Affairs and Public Policy, University of Toronto, Canada

Max Bell School of Public Policy, McGill University, Canada

School of Computer Science, McGill University, Canada

Department of Languages, Literatures, and Cultures, McGill University, Canada

Computer Science Program, McGill University, Canada

cause and effect of covid 19 essay brainly

Research Questions

  • How prevalent is misinformation surrounding COVID-19 on Twitter, and how does this compare to Canadian news media?
  • Does the type of media one is exposed to influence social distancing behaviours and beliefs about COVID-19?
  • Is there a link between COVID-19 misinformation and perceptions of the pandemic’s severity and compliance with social distancing recommendations?

Essay Summary

  • We evaluate the presence of misinformation and public health recommendations regarding COVID-19 in a massive corpus of tweets as well as all articles published on nineteen Canadian news sites. Using these data, we show that preventative measures are more encouraged and covered on traditional news media, while misinformation appears more frequently on Twitter.
  • To evaluate the impact of this greater level of misinformation, we conducted a nationally representative survey that included questions about common misperceptions regarding COVID-19, risk perceptions, social distancing compliance, and exposure to traditional news and social media. We find that being exposed to news media is associated with fewer misperceptions and more social distancing compliance while conversely, social media exposure is associated with more misperceptions and less social distancing compliance.
  • Misperceptions regarding the virus are in turn associated with less compliance with social distancing measures, even when controlling for a broad range of other attitudes and characteristics.
  • Association between social media exposure and social distancing non-compliance is eliminated when accounting for effect of misperceptions, providing evidence that social media is associated with non-compliance through increasing misperceptions about the virus.

Implications

The COVID-19 pandemic has been accompanied by a so-called “infodemic”—a global spread of misinformation that poses a serious problem for public health. Infodemics are concerning because the spread of false or misleading information has the capacity to change transmission patterns (Kim et al., 2019) and consequently the scale and lethality of a pandemic. This information can be shared by any media, but there is reason to be particularly concerned about the role that social media, such as Facebook and Twitter, play in incidentally boosting misperceptions. These platforms are increasingly relied upon as primary sources of news (Mitchell et al., 2016) and misinformation has been heavily documented on them (Garrett, 2019; Vicario et al., 2016). Scholars have found medical and health misinformation on the platforms, including that related to vaccines (Radzikowski et al., 2016) and other virus epidemics such as Ebola (Fung et al., 2016) and Zika (Sharma et al., 2017). 

However, misinformation content typically makes up a low percentage of overall discussion of a topic (e.g. Fung et al., 2016) and mere exposure to misinformation does not guarantee belief in that misinformation. More research is thus needed to understand the extent and consequences of misinformation surrounding COVID-19 on social media. During the COVID-19 pandemic, Twitter, Facebook and other platforms have engaged in efforts to combat misinformation but they have continued to receive widespread criticism that misinformation is still appearing on prominent pages and groups (Kouzy et al., 2020; NewsGuard, 2020). The extent to which misinformation continues to circulate on these platforms and influence people’s attitudes and behaviours is still very much an open question.

Here, we draw on three data sets and a sequential mixed method approach to better understand the consequences of online misinformation for important behaviours and attitudes. First, we collected nearly 2.5 million tweets explicitly referring to COVID-19 in the Canadian context. Second, we collected just over 9 thousand articles from nineteen Canadian English-language news sites from the same time period. We coded both of these media sets for misinformation and public health recommendations. Third, we conducted a nationally representative survey that included questions related to media consumption habits, COVID-19 perceptions and misperceptions, and social distancing compliance. As our outcome variables are continuous, we use Ordinary Least Squares (OLS) regression to identify relationships between news and social media exposure, misperceptions, compliance with social distancing measures, and risk perceptions. We use these data to illustrate: 1) the relative prevalence of misinformation on Twitter; and 2) a powerful association between social media usage and misperceptions, on the one hand, and social distancing non-compliance on the other.

Misinformation and compliance with social distancing

We first compare the presence of misinformation on Twitter with that on news media and find, consistent with the other country cases (Chadwick & Vaccari, 2019; Vicario et al., 2016), comparatively higher levels of misinformation circulating on the social media platform. We also found that recommendations for safe practices during the pandemic (e.g. washing hands, social distancing) appeared much more frequently in the Canadian news media. These findings are in line with literature examining fake news which finds a large difference in information quality across media (Al-Rawi, 2019; Guess & Nyhan, 2018).

Spending time in a media environment that contains misinformation is likely to change attitudes and behaviours. Even if users are not nested in networks that propagate misinformation, they are likely to be incidentally exposed to information from a variety of perspectives (Feezell, 2018; Fletcher & Nielsen, 2018; Weeks et al., 2017). Even a highly curated social media feed is thus still likely to contain misinformation. As cumulative exposure to misinformation increases, users are likely to experience a reinforcement effect whereby familiarity leads to stronger belief (Dechêne et al., 2010).

To evaluate this empirically, we conducted a national survey that included questions on information consumption habits and a battery of COVID-19 misperceptions that could be the result of exposure to misinformation. We find that those who self-report exposure to the misinformation-rich social media environment do tend to have more misperceptions regarding COVID-19. These findings are consistent with others that link exposure to misinformation and misperceptions (Garrett et al., 2016; Jamieson & Albarracín, 2020). Social media users also self-report less compliance with social distancing.

Misperceptions are most meaningful when they impact behaviors in dangerous ways. During a pandemic, misperceptions can be fatal. In this case, we find that misperceptions are associated with reduced COVID-19 risk perceptions and with lower compliance with social distancing measures. We continue to find strong effects after controlling for socio-economic characteristics as well as scientific literacy. After accounting for the effect of misperceptions on social distancing non-compliance, social media usage no longer has a significant association with non-compliance, providing evidence that social media may lead to less social distancing compliance through its effect on COVID-19 misperceptions.

While some social media companies have made efforts to suppress misinformation on their platforms, there continues to be a high level of misinformation relative to news media. Highly polarized political environments and media ecosystems can lead to the spread of misinformation, such as in the United States during the COVID-19 pandemic (Allcott et al., 2020; Motta et al., 2020). But even in healthy media ecosystems with less partisan news (Owen et al., 2020), social media can continue to facilitate the spread of misinformation. There is a real danger that without concerted efforts to reduce the amount of misinformation shared on social media, the large-scale social efforts required to combat COVID-19 will be undermined. 

We contribute to a growing base of evidence that misinformation circulating on social media poses public health risks and join others in calling for social media companies to put greater focus on flattening the curve of misinformation (Donovan, 2020). These findings also provide governments with stronger evidence that the misinformation circulating on social media can be directly linked to misperceptions and public health risks. Such evidence is essential for them to chart an effective policy course. Finally, the methods and approach developed in this paper can be fruitfully applied to study other waves of misinformation and the research community can build upon the link clearly drawn between misinformation exposure, misperceptions, and downstream attitudes and behaviours.

We found use of social media platforms broadly contributes to misperceptions but were unable to precise the overall level of misinformation circulating on non-Twitter social media. Data access for researchers to platforms such as Facebook, YouTube, and Instagram is limited and virtually non-existent for SnapChat, WhatsApp, and WeChat. Cross-platform content comparisons are an important ingredient for a rich understand of the social media environment and these social media companies must better open their platforms to research in the public interest. 

Finding 1: Misinformation about COVID-19 is circulated more on Twitter as compared to traditional media.

We find large differences between the quality of information shared about COVID-19 on traditional news and Twitter. Figure 1 shows the percentage of COVID-19 related content that contains information linked to a particular theme. The plot reports the prevalence of information on both social and news media for: 1) three specific pieces of misinformation; 2) a general set of content that describes the pandemic itself as a conspiracy or a hoax; and 3) advice about hygiene and social distancing during the pandemic. We differentiate content that shared misinformation (red in the plot) from content that debunked misinformation (green in the plot). 

cause and effect of covid 19 essay brainly

There are large differences between the levels of misinformation on Twitter and news media. Misinformation was comparatively more common on Twitter across all four categories, while debunking was relatively more common in traditional news. Meanwhile, advice on hygiene and social distancing appeared much more frequently in news media. Note that higher percentages are to be expected for longer format news articles since we rely on keyword searches for identification. This makes the misinformation findings even starker – despite much higher average word counts, far fewer news articles propagate misinformation.

Finding 2: There is a strong association between social media exposure and misperceptions about COVID-19. The inverse is true for exposure to traditional news.

Among our survey respondents we find a corresponding strong association between social media exposure and misperceptions about COVID-19. These results are plotted in Figure 2, with controls included for both socioeconomic characteristics and demographics. Moving from no social media exposure to its maximum is expected to increase one’s misperceptions of COVID-19 by 0.22 on the 0-1 scale and decreased self-reported social distancing compliance by 0.12 on that same scale.

This result stands in stark contrast with the observed relationship between traditional news exposure and our outcome measures. Traditional news exposure is  positively  associated with correct perceptions regarding COVID-19. Moving from no news exposure to its highest level is expected to reduce misperceptions by 0.12 on the 0-1 scale and to increase social distancing compliance by 0.28 on that same scale. The effects are plotted in Figure 2. Social media usage appears to be correlated with COVID-19 misperceptions, suggesting these misperceptions are partially a result of misinformation on social media. The same cannot be said of traditional news exposure.

cause and effect of covid 19 essay brainly

Finding 3: Misperceptions about the pandemic are associated with lower levels of risk perceptions and social distancing compliance.

COVID-19 misperceptions are also powerfully associated with  lower  levels of social distancing compliance. Moving from the lowest level of COVID-19 misperceptions to its maximum is associated with a reduction of one’s social distancing by 0.39 on the 0-1 scale. The previously observed relationship between social media exposure and misperceptions disappears, suggestive of a mediated relationship. That is, social media exposure increases misperceptions, which in turn reduces social distancing compliance. Misperceptions is also weakly associated with lower COVID-19 risk perceptions. Estimates from our models using COVID-19 concern as the outcome can be found in the left panel of Figure 3, while social distancing can be found in the right panel.

Finally, we also see that the relationship between misinformation and both social distancing compliance and COVID-19 concern hold when including controls for science literacy and a number of fundamental predispositions that are likely associated with both misperceptions and following the advice of scientific experts, such as anti-intellectualism, pseudoscientific beliefs, and left-right ideology. These estimates can similarly be found in Figure 3.

cause and effect of covid 19 essay brainly

Canadian Twitter and news data were collected from March 26 th  to April 6 th , 2020. We collected all English-language tweets from a set of 620,000 users that have been determined to be likely Canadians. For inclusion, a given user must self-identify as Canadian-based, follow a large number of Canadian political elite accounts, or frequently use Canadian-specific hashtags. News media was collected from nineteen prominent Canadian news sites with active RSS feeds. These tweets and news articles were searched for “covid” or “coronavirus”, leaving a sample of 2.25 million tweets and 8,857 news articles.

Of the COVID-19 related content, we searched for terms associated with four instances of misinformation that circulated during the COVID-19 pandemic: that COVID-19 was no more serious than the flu, that vitamin C or other supplements will prevent contraction of the virus, that the initial animal-to-human transfer of the virus was the direct result of eating bats, or that COVID-19 was a hoax or conspiracy. Given that we used keyword searches to identify content, we manually reviewed a random sample of 500 tweets from each instance of misinformation. Each tweet was coded as one of four categories: propagating misinformation, combatting misinformation, content with the relevant keywords but unrelated to misinformation, or content that refers to the misinformation but does not offer comment. 

We then calculated the overall level of misinformation for that instance on Twitter by multiplying the overall volume of tweets by the proportion of hand-coded content where misinformation was identified. Each news article that included relevant keywords was similarly coded. The volume of the news mentioning these terms was sufficiently low that all news articles were hand coded. To identify health recommendations, we used a similar keyword search for terms associated with particular recommendations: 1) social distancing including staying at home, staying at least 6 feet or 2 meters away and avoiding gatherings; and 2) washing hands and not touching any part of your face. 1 Further details on the media collection strategy and hand-coding schema are available in the supporting materials.

For survey data, we used a sample of nearly 2,500 Canadian citizens 18 years or older drawn from a probability-based online national panel fielded from April 2-6, 2020. Quotas we set on age, gender, region, and language to ensure sample representativeness, and data was further weighted within region by gender and age based on the 2016 Canadian census.

We measure levels of COVID-19 misperceptions by asking respondents to rate the truthfulness of a series of nine false claims, such as the coronavirus being no worse than the seasonal flu or that it can be warded off with Vitamin C. Each was asked on a scale from definitely false (0) to definitely true (5). We use Cronbach’s Alpha as an indicator of scale reliability. Cronbach’s Alpha ranges from 0-1, with scores above 0.8 indicating the reliability is “good.” These items score 0.88, so we can safely construct a 0-1 scale of misperceptions from them. 

We evaluate COVID-19 risk perceptions with a pair of questions asking respondents how serious of a threat they believe the pandemic to be for themselves and for Canadians, respectively. Each question was asked on a scale from not at all (0) to very (4). We construct a continuous index with these items.

We quantify social distancing by asking respondents to indicate which of a series of behaviours they had undertaken in response to the pandemic, such as working from home or avoiding in-person contact with friends, family, and acquaintances. We use principal component analysis (PCA) to reduce the number of dimensions in these data while minimizing information loss. The analysis revealed 2 distinct dimensions in our questions. One dimension includes factors strongly determined by occupation, such as working from home and switching to online meetings. The other dimension contains more inclusive behaviours such as avoiding contact, travel, and crowded places. We generate predictions from the PCA for this latter dimension to use in our analyses. The factor loadings can be found in Table A1 of the supporting materials.

 We gauge news and social media consumption by asking respondents to identify news outlets and social media platforms they have used over the past week for political news. The list of news outlets included 17 organizations such as mainstream sources like CBC and Global, and partisan outlets like Rebel Media and National Observer. The list of social media platforms included 10 options such as Facebook, Twitter, YouTube, and Instagram. We sum the total number of outlets/platforms respondents report using and take the log to adjust for extreme values. We measure offline political discussion with an index based on questions asking how often respondents have discussed politics with family, friends, and acquaintances over the past week. Descriptions of our primary variables can be found in Table A2 of the supporting materials. 

We evaluate our hypotheses using a standard design that evaluates the association between our explanatory and outcome variables controlling for other observable factors we measured. In practice, randomly assigning social media exposure is impractical, while randomly assigning misinformation is unethical. This approach allows us to describe these relationships, though we cannot make definite claims to causality.

We hypothesize that social media exposure is associated with misinformation on COVID-19. Figure 2 presents the coefficients of models predicting the effects of news exposure, social media exposure, and political discussion on COVID-19 misinformation, risk perceptions, and social distancing. Socio-economic and demographic control estimates are not displayed. Full estimation results can be found in the Table A3 of the supporting materials. 

We further hypothesize that COVID-19 misinformation is associated with lower COVID-19 risk perceptions and less social distancing compliance. Figure 3 presents the coefficients for models predicting the effects of misinformation, news exposure, and social media exposure on severity perceptions and social distancing. We show models with and without controls for science literacy and other predispositions. Full estimation results can be found in the Table A4 of the supporting materials.

Limitations and robustness

A study such as this comes with clear limitations. First, we have evaluated information coming from only a section of the overall media ecosystem and during a specific time-period. The level of misinformation differs across platforms and online news sites and a more granular investigation into these dynamics would be valuable. Our analysis suggests that similar dynamics exist across social media platforms, however. In the supplementary materials we show that associations between misperceptions and social media usage are even higher for other social media platforms, suggesting that our analysis of Twitter content may underrepresent the prevalence of misinformation on social media writ large. As noted above, existing limitations on data access make such cross-platform research difficult.

Second, our data is drawn from a single country and language case study and other countries may have different media environments and levels of misinformation circulating on social media. We anticipate the underlying dynamics found in this paper to hold across these contexts, however. Those who consume information from platforms where misinformation is more prevalent will have greater misperceptions and that these misperceptions will be linked to lower compliance with social distancing and lower risk perceptions. Third, an ecological problem is present wherein we do not link survey respondents directly to their social media consumption (and evaluation of the misinformation they are exposed to) and lack the ability to randomly assign social media exposure to make a strong causal argument. We cannot and do not make a causal argument here but argue instead that there is strong evidence for a misinformation to misperceptions to lower social distancing compliance link. 

  • / Fake News
  • / Mainstream Media
  • / Public Health
  • / Social Media

Cite this Essay

Bridgman, A., Merkley, E., Loewen, P. J., Owen, T., Ruths, D., Teichmann, L., & Zhilin, O. (2020). The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media. Harvard Kennedy School (HKS) Misinformation Review . https://doi.org/10.37016/mr-2020-028

Bibliography

Allcott, H., Boxell, L., Conway, J. C., Gentzkow, M., Thaler, M., & Yang, D. Y. (2020). Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic (Working Paper No. 26946; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26946

Al-Rawi, A. (2019). Gatekeeping Fake News Discourses on Mainstream Media Versus Social Media. Social Science Computer Review , 37 (6), 687–704. https://doi.org/10.1177/0894439318795849

Chadwick, A., & Vaccari, C. (2019). News sharing on UK social media: Misinformation, disinformation, and correction [Report]. Loughborough University. https://repository.lboro.ac.uk/articles/News_sharing_on_UK_social_media_misinformation_disinformation_and_correction/9471269

Dechêne, A., Stahl, C., Hansen, J., & Wänke, M. (2010). The Truth About the Truth: A Meta-Analytic Review of the Truth Effect. Personality and Social Psychology Review , 14 (2), 238–257. https://doi.org/10.1177/1088868309352251

Donovan, J. (2020). Social-media companies must flatten the curve of misinformation. Nature . https://doi.org/10.1038/d41586-020-01107-z

Feezell, J. T. (2018). Agenda Setting through Social Media: The Importance of Incidental News Exposure and Social Filtering in the Digital Era. Political Research Quarterly , 71 (2), 482–494. https://doi.org/10.1177/1065912917744895

Fletcher, R., & Nielsen, R. K. (2018). Are people incidentally exposed to news on social media? A comparative analysis. New Media & Society , 20 (7), 2450–2468. https://doi.org/10.1177/1461444817724170

Fung, I. C.-H., Fu, K.-W., Chan, C.-H., Chan, B. S. B., Cheung, C.-N., Abraham, T., & Tse, Z. T. H. (2016). Social Media’s Initial Reaction to Information and Misinformation on Ebola, August 2014: Facts and Rumors. Public Health Reports , 131 (3), 461–473. https://doi.org/10.1177/003335491613100312

Garrett, R. K. (2019). Social media’s contribution to political misperceptions in U.S. Presidential elections. PLoS ONE , 14 (3). https://doi.org/10.1371/journal.pone.0213500

Garrett, R. K., Weeks, B. E., & Neo, R. L. (2016). Driving a Wedge Between Evidence and Beliefs: How Online Ideological News Exposure Promotes Political Misperceptions. Journal of Computer-Mediated Communication , 21 (5), 331–348. https://doi.org/10.1111/jcc4.12164

Guess, A., & Nyhan, B. (2018). Selective Exposure to Misinformation: Evidence from the consumption of fake news during the 2016 U.S. presidential campaign. European Research Council , 49.

Jamieson, K. H., & Albarracín, D. (2020). The Relation between Media Consumption and Misinformation at the Outset of the SARS-CoV-2 Pandemic in the US. Harvard Kennedy School Misinformation Review , 2 . https://doi.org/10.37016/mr-2020-012

Kim, L., Fast, S. M., & Markuzon, N. (2019). Incorporating media data into a model of infectious disease transmission. PLOS ONE , 14 (2), e0197646. https://doi.org/10.1371/journal.pone.0197646

Kouzy, R., Abi Jaoude, J., Kraitem, A., El Alam, M. B., Karam, B., Adib, E., Zarka, J., Traboulsi, C., Akl, E. W., & Baddour, K. (2020). Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter. Cureus , 12 (3). https://doi.org/10.7759/cureus.7255

Mitchell, A., Gottfried, J., Barthel, M., & Shearer, E. (2016, July 7). The Modern News Consumer. Pew Research Center’s Journalism Project . https://www.journalism.org/2016/07/07/the-modern-news-consumer/

Motta, M., Stecula, D., & Farhart, C. E. (2020). How Right-Leaning Media Coverage of COVID-19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/a8r3p

NewsGuard. (2020). Superspreaders . https://www.newsguardtech.com/superspreaders/

Owen, T., Loewen, P., Ruths, D., Bridgman, A., Gorwa, R., MacLellan, S., Merkley, E., & Zhilin, O. (2020). Lessons in Resilience: Canada’s Digital Media Ecosystem and the 2019 Election . Public Policy Forum. https://ppforum.ca/articles/lessons-in-resilience-canadas-digital-media-ecosystem-and-the-2019-election/

Radzikowski, J., Stefanidis, A., Jacobsen, K. H., Croitoru, A., Crooks, A., & Delamater, P. L. (2016). The Measles Vaccination Narrative in Twitter: A Quantitative Analysis. JMIR Public Health and Surveillance , 2 (1), e1. https://doi.org/10.2196/publichealth.5059

Sharma, M., Yadav, K., Yadav, N., & Ferdinand, K. C. (2017). Zika virus pandemic—Analysis of Facebook as a social media health information platform. American Journal of Infection Control , 45 (3), 301–302. https://doi.org/10.1016/j.ajic.2016.08.022

Shin, J., Jian, L., Driscoll, K., & Bar, F. (2018). The diffusion of misinformation on social media: Temporal pattern, message, and source. Computers in Human Behavior , 83 , 278–287. https://doi.org/10.1016/j.chb.2018.02.008

Vicario, M. D., Bessi, A., Zollo, F., Petroni, F., Scala, A., Caldarelli, G., Stanley, H. E., & Quattrociocchi, W. (2016). The spreading of misinformation online. Proceedings of the National Academy of Sciences , 113 (3), 554–559. https://doi.org/10.1073/pnas.1517441113

Weeks, B. E., Lane, D. S., Kim, D. H., Lee, S. S., & Kwak, N. (2017). Incidental Exposure, Selective Exposure, and Political Information Sharing: Integrating Online Exposure Patterns and Expression on Social Media. Journal of Computer-Mediated Communication , 22 (6), 363–379. https://doi.org/10.1111/jcc4.12199

The project was funded through the Department of Canadian Heritage’s Digital Citizens Initiative.

Competing Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The research protocol was approved by the institutional review board at University of Toronto. Human subjects gave informed consent before participating and were debriefed at the end of the study.

This  is  an open access article distributed under the terms of the Creative  Commons  Attribution  License , which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

Data Availability

All materials needed to replicate this study are available via the Harvard Dataverse: https://doi.org/10.7910/DVN/5QS2XP .

EDITORIAL article

Editorial: coronavirus disease (covid-19): the impact and role of mass media during the pandemic.

\nPatrícia Arriaga

  • 1 Department of Social and Organizational Psychology, Iscte-University Institute of Lisbon, CIS-IUL, Lisbon, Portugal
  • 2 Department of Psychology and Social Work, Mid Sweden University, Östersund, Sweden
  • 3 Department of Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany

Editorial on the Research Topic Coronavirus Disease (COVID-19): The Impact and Role of Mass Media During the Pandemic

The outbreak of the coronavirus disease 2019 (COVID-19) has created a global health crisis that had a deep impact on the way we perceive our world and our everyday lives. Not only has the rate of contagion and patterns of transmission threatened our sense of agency, but the safety measures to contain the spread of the virus also required social and physical distancing, preventing us from finding solace in the company of others. Within this context, we launched our Research Topic on March 27th, 2020, and invited researchers to address the Impact and Role of Mass Media During the Pandemic on our lives at individual and social levels.

Despite all the hardships, disruption, and uncertainty brought by the pandemic, we received diverse and insightful manuscript proposals. Frontiers in Psychology published 15 articles, involving 61 authors from 8 countries, which were included in distinct specialized sections, including Health Psychology, Personality and Social Psychology, Emotion Science, and Organizational Psychology. Despite the diversity of this collective endeavor, the contributions fall into four areas of research: (1) the use of media in public health communication; (2) the diffusion of false information; (3) the compliance with the health recommendations; and (4) how media use relates to mental health and well-being.

A first line of research includes contributions examining the use of media in public health communication. Drawing on media messages used in previous health crises, such as Ebola and Zika, Hauer and Sood describe how health organizations use media. They offer a set of recommendations for COVID-19 related media messages, including the importance of message framing, interactive public forums with up-to-date information, and an honest communication about what is known and unknown about the pandemic and the virus. Following a content analysis approach, Parvin et al. studied the representations of COVID-19 in the opinion section of five Asian e-newspapers. The authors identified eight main issues (health and drugs, preparedness and awareness, social welfare and humanity, governance and institutions, the environment and wildlife, politics, innovation and technology, and the economy) and examined how e-newspapers from these countries attributed different weights to these issues and how this relates to the countries' cultural specificity. Raccanello et al. show how the internet can be a platform to disseminate a public campaign devised to inform adults about coping strategies that could help children and teenagers deal with the challenges of the pandemic. The authors examined the dissemination of the program through the analysis of website traffic, showing that in the 40 days following publication, the website reached 6,090 visits.

A second related line of research that drew the concern of researchers was the diffusion of false information about COVID-19 through the media. Lobato et al. examined the role of distinct individual differences (political orientation, social dominance orientation, traditionalism, conspiracy ideation, attitudes about science) on the willingness to share misinformation about COVID-19 over social media. The misinformation topics varied between the severity and spread of COVID-19, treatment and prevention, conspiracy theories, and miscellaneous unverifiable claims. Their results from 296 adult participants (Mage = 36.23; 117 women) suggest two different profiles. One indicating that those reporting more liberal positions and lower social dominance were less willing to share conspiracy misinformation. The other profile indicated that participants scoring high on social dominance and low in traditionalism were more willing to share both conspiracy and other miscellaneous claims, but less willing to share misinformation about the severity and spread of COVID-19. Their findings can have relevant contributions for the identification of specific individual profiles related to the widespread of distinct types of misinformation. Dhanani and Franz examined a sample of 1,141 adults (Mage = 44.66; 46.9% female, 74.7% White ethnic identity) living in the United States in March 2020. The authors examined how media consumption and information source were related to knowledge about COVID-19, the endorsement of misinformation about COVID-19, and prejudice toward Asian Americans. Higher levels of trust in informational sources such as public health organizations (e.g., Center for Disease Control) was associated with greater knowledge, lower endorsement of misinformation, and less prejudice toward Asian Americans. Media source was associated with distinct levels of knowledge, willingness to endorsement misinformation and prejudice toward American Asians, with social media use (e.g., Twitter, Facebook) being related with a lower knowledge about COVID-19, higher endorsement of misinformation, and stronger prejudice toward Asian Americans.

A third line of research addressed the factors that could contribute to compliance with the health recommendations to avoid the spread of the disease. Vai et al. studied early pre-lockdown risk perceptions about COVID-19 and the trust in media sources among 2,223 Italians (Mage = 36.4, 69.2% female). They found that the perceived usefulness of the containment measures (e.g., social distancing) was related to threat perception and efficacy beliefs. Lower threat perception was associated with less perception of utility of the containment measures. Although most participants considered themselves and others capable of taking preventive measures, they saw the measures as generally ineffective. Participants acknowledged using the internet as their main source of information and considered health organizations' websites as the most trustworthy source. Albeit frequently used, social media was in general considered an unreliable source of information. Tomczyk et al. studied knowledge about preventive behaviors, risk perception, stigmatizing attitudes (support for discrimination and blame), and sociodemographic data (e.g., age, gender, country of origin, education level, region, persons per household) as predictors of compliance with the behavioral recommendations among 157 Germans, (age range: 18–77 years, 80% female). Low compliance was associated with male gender, younger age, and lower public stigma. Regarding stigmatizing attitudes, the authors only found a relation between support for discrimination (i.e., support for compulsory measures) and higher intention to comply with recommendations. Mahmood et al. studied the relation between social media use, risk perception, preventive behaviors, and self-efficacy in a sample of 310 Pakistani adults (54.2% female). The authors found social media use to be positively related to self-efficacy and perceived threat, which were both positively related to preventive behaviors (e.g., hand hygiene, social distancing). Information credibility was also related to compliance with health recommendations. Lep et al. examined the relationship between information source perceived credibility and trust, and participants' levels of self-protective behavior among 1,718 Slovenians (age range: 18–81 years, 81.7% female). The authors found that scientists, general practitioners (family doctors), and the National Institute of Public Health were perceived as the more credible source of information, while social media and government officials received the lowest ratings. Perceived information credibility was found to be associated with lower levels of negative emotional responses (e.g., nervousness, helplessness) and a higher level of observance of self-protective measures (e.g., hand washing). Siebenhaar et al. also studied the link between compliance, distress by information, and information avoidance. They examined the online survey responses of 1,059 adults living in Germany (Mage = 39.53, 79.4% female). Their results suggested that distress by information could lead to higher compliance with preventive measures. Distress by information was also associated with higher information avoidance, which in turn is related to less compliance. Gantiva et al. studied the effectiveness of different messages regarding the intentions toward self-care behaviors, perceived efficacy to motivate self-care behaviors in others, perceived risk, and perceived message strength, in a sample of 319 Colombians (age range: 18–60 years, 69.9% female). Their experiment included the manipulation of message framing (gain vs. loss) and message content (economy vs. health). Participants judged gain-frame health related messages to be stronger and more effective in changing self-behavior, whereas loss-framed health messages resulted in increased perceived risk. Rahn et al. offer a comparative view of compliance and risk perception, examining three hazard types: COVID-19 pandemic, violent acts, and severe weather. With a sample of 403 Germans (age range: 18–89 years, 72% female), they studied how age, gender, previous hazard experience and different components of risk appraisal (perceived severity, anticipated negative emotions, anticipatory worry, and risk perception) were related to the intention to comply with behavioral recommendations. They found that higher age predicted compliance with health recommendations to prevent COVID-19, anticipatory worry predicted compliance with warning messages regarding violent acts, and women complied more often with severe weather recommendations than men.

A fourth line of research examined media use, mental health and well-being during the COVID-19 pandemic. Gabbiadini et al. addressed the use of digital technology (e.g., voice/video calls, online games, watching movies in party mode) to stay connected with others during lockdown. Participants, 465 Italians (age range: 18–73 years, 348 female), reported more perceived social support associated with the use of these digital technologies, which in turn was associated with fewer feelings of loneliness, boredom, anger, and higher sense of belongingness. Muñiz-Velázquez et al. compared the media habits of 249 Spanish adults (Mage = 42.06, 53.8% female) before and during confinement. They compared the type of media consumed (e.g., watching TV series, listening to radio, watching news) and found the increased consumption of TV and social networking sites during confinement to be negatively associated with reported level of happiness. People who reported higher levels of well-being also reported watching less TV and less use of social networking sites. Majeed et al. , on the other hand, examined the relation between problematic social media use, fear of COVID-19, depression, and mindfulness. Their study, involving 267 Pakistani adults (90 female), suggested trait mindfulness had a buffer effect, reducing the impact of problematic media use and fear of COVID-19 on depression.

Taken together, these findings highlight how using different frames for mass media gives a more expansive view of its positive and negative roles, but also showcase the major concerns in the context of a pandemic crisis. As limitations we highlight the use of cross-sectional designs in most studies, not allowing to establish true inferences of causal relationships. The outcome of some studies may also be limited by the unbalanced number of female and male participants, by the non-probability sampling method used, and by the restricted time frame in which the research occurred. Nevertheless, we are confident that all the selected studies in our Research Topic bring important and enduring contributions to the understanding of how media, individual differences, and social factors intertwine to shape our lives, which can also be useful to guide public policies during these challenging times.

Author Contributions

PA: conceptualization, writing the original draft, funding acquisition, writing—review, and editing. FE: conceptualization, writing—review, and editing. MP: writing—review and editing. NP: conceptualization, writing the original draft, writing—review, and editing. All authors approved the submitted version.

PA and NP received partial support to work on this Research Topic through Fundação para a Ciência e Tecnologia (FCT) with reference to the project PTDC/CCI-INF/29234/2017. MP contribution was supported by the German Research Foundation (DFG, PA847/22-1 and PA847/25-1). The authors are independent of the funders.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We would like to express our gratitude to all the authors who proposed their work, all the researchers who reviewed the submissions to this Research Topic, and to Rob Richards for proofreading the Editorial manuscript.

Keywords: COVID-19, coronavirus disease, mass media, health communication, prevention, intervention, social behavioral changes

Citation: Arriaga P, Esteves F, Pavlova MA and Piçarra N (2021) Editorial: Coronavirus Disease (COVID-19): The Impact and Role of Mass Media During the Pandemic. Front. Psychol. 12:729238. doi: 10.3389/fpsyg.2021.729238

Received: 22 June 2021; Accepted: 30 July 2021; Published: 23 August 2021.

Edited and reviewed by: Eduard Brandstätter , Johannes Kepler University of Linz, Austria

Copyright © 2021 Arriaga, Esteves, Pavlova and Piçarra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Patrícia Arriaga, patricia.arriaga@iscte-iul.pt

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Persuasive Essay Guide

Persuasive Essay About Covid19

Caleb S.

How to Write a Persuasive Essay About Covid19 | Examples & Tips

11 min read

Persuasive Essay About Covid19

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Are you looking to write a persuasive essay about the Covid-19 pandemic?

Writing a compelling and informative essay about this global crisis can be challenging. It requires researching the latest information, understanding the facts, and presenting your argument persuasively.

But don’t worry! with some guidance from experts, you’ll be able to write an effective and persuasive essay about Covid-19.

In this blog post, we’ll outline the basics of writing a persuasive essay . We’ll provide clear examples, helpful tips, and essential information for crafting your own persuasive piece on Covid-19.

Read on to get started on your essay.

Arrow Down

  • 1. Steps to Write a Persuasive Essay About Covid-19
  • 2. Examples of Persuasive Essay About Covid19
  • 3. Examples of Persuasive Essay About Covid-19 Vaccine
  • 4. Examples of Persuasive Essay About Covid-19 Integration
  • 5. Examples of Argumentative Essay About Covid 19
  • 6. Examples of Persuasive Speeches About Covid-19
  • 7. Tips to Write a Persuasive Essay About Covid-19
  • 8. Common Topics for a Persuasive Essay on COVID-19 

Steps to Write a Persuasive Essay About Covid-19

Here are the steps to help you write a persuasive essay on this topic, along with an example essay:

Step 1: Choose a Specific Thesis Statement

Your thesis statement should clearly state your position on a specific aspect of COVID-19. It should be debatable and clear. For example:

Step 2: Research and Gather Information

Collect reliable and up-to-date information from reputable sources to support your thesis statement. This may include statistics, expert opinions, and scientific studies. For instance:

  • COVID-19 vaccination effectiveness data
  • Information on vaccine mandates in different countries
  • Expert statements from health organizations like the WHO or CDC

Step 3: Outline Your Essay

Create a clear and organized outline to structure your essay. A persuasive essay typically follows this structure:

  • Introduction
  • Background Information
  • Body Paragraphs (with supporting evidence)
  • Counterarguments (addressing opposing views)

Step 4: Write the Introduction

In the introduction, grab your reader's attention and present your thesis statement. For example:

Step 5: Provide Background Information

Offer context and background information to help your readers understand the issue better. For instance:

Step 6: Develop Body Paragraphs

Each body paragraph should present a single point or piece of evidence that supports your thesis statement. Use clear topic sentences, evidence, and analysis. Here's an example:

Step 7: Address Counterarguments

Acknowledge opposing viewpoints and refute them with strong counterarguments. This demonstrates that you've considered different perspectives. For example:

Step 8: Write the Conclusion

Summarize your main points and restate your thesis statement in the conclusion. End with a strong call to action or thought-provoking statement. For instance:

Step 9: Revise and Proofread

Edit your essay for clarity, coherence, grammar, and spelling errors. Ensure that your argument flows logically.

Step 10: Cite Your Sources

Include proper citations and a bibliography page to give credit to your sources.

Remember to adjust your approach and arguments based on your target audience and the specific angle you want to take in your persuasive essay about COVID-19.

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Examples of Persuasive Essay About Covid19

When writing a persuasive essay about the Covid-19 pandemic, it’s important to consider how you want to present your argument. To help you get started, here are some example essays for you to read:

Check out some more PDF examples below:

Persuasive Essay About Covid-19 Pandemic

Sample Of Persuasive Essay About Covid-19

Persuasive Essay About Covid-19 In The Philippines - Example

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Examples of Persuasive Essay About Covid-19 Vaccine

Covid19 vaccines are one of the ways to prevent the spread of Covid-19, but they have been a source of controversy. Different sides argue about the benefits or dangers of the new vaccines. Whatever your point of view is, writing a persuasive essay about it is a good way of organizing your thoughts and persuading others.

A persuasive essay about the Covid-19 vaccine could consider the benefits of getting vaccinated as well as the potential side effects.

Below are some examples of persuasive essays on getting vaccinated for Covid-19.

Covid19 Vaccine Persuasive Essay

Persuasive Essay on Covid Vaccines

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Examples of Persuasive Essay About Covid-19 Integration

Covid19 has drastically changed the way people interact in schools, markets, and workplaces. In short, it has affected all aspects of life. However, people have started to learn to live with Covid19.

Writing a persuasive essay about it shouldn't be stressful. Read the sample essay below to get idea for your own essay about Covid19 integration.

Persuasive Essay About Working From Home During Covid19

Searching for the topic of Online Education? Our persuasive essay about online education is a must-read.

Examples of Argumentative Essay About Covid 19

Covid-19 has been an ever-evolving issue, with new developments and discoveries being made on a daily basis.

Writing an argumentative essay about such an issue is both interesting and challenging. It allows you to evaluate different aspects of the pandemic, as well as consider potential solutions.

Here are some examples of argumentative essays on Covid19.

Argumentative Essay About Covid19 Sample

Argumentative Essay About Covid19 With Introduction Body and Conclusion

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Examples of Persuasive Speeches About Covid-19

Do you need to prepare a speech about Covid19 and need examples? We have them for you!

Persuasive speeches about Covid-19 can provide the audience with valuable insights on how to best handle the pandemic. They can be used to advocate for specific changes in policies or simply raise awareness about the virus.

Check out some examples of persuasive speeches on Covid-19:

Persuasive Speech About Covid-19 Example

Persuasive Speech About Vaccine For Covid-19

You can also read persuasive essay examples on other topics to master your persuasive techniques!

Tips to Write a Persuasive Essay About Covid-19

Writing a persuasive essay about COVID-19 requires a thoughtful approach to present your arguments effectively. 

Here are some tips to help you craft a compelling persuasive essay on this topic:

Choose a Specific Angle

Start by narrowing down your focus. COVID-19 is a broad topic, so selecting a specific aspect or issue related to it will make your essay more persuasive and manageable. For example, you could focus on vaccination, public health measures, the economic impact, or misinformation.

Provide Credible Sources 

Support your arguments with credible sources such as scientific studies, government reports, and reputable news outlets. Reliable sources enhance the credibility of your essay.

Use Persuasive Language

Employ persuasive techniques, such as ethos (establishing credibility), pathos (appealing to emotions), and logos (using logic and evidence). Use vivid examples and anecdotes to make your points relatable.

Organize Your Essay

Structure your essay involves creating a persuasive essay outline and establishing a logical flow from one point to the next. Each paragraph should focus on a single point, and transitions between paragraphs should be smooth and logical.

Emphasize Benefits

Highlight the benefits of your proposed actions or viewpoints. Explain how your suggestions can improve public health, safety, or well-being. Make it clear why your audience should support your position.

Use Visuals -H3

Incorporate graphs, charts, and statistics when applicable. Visual aids can reinforce your arguments and make complex data more accessible to your readers.

Call to Action

End your essay with a strong call to action. Encourage your readers to take a specific step or consider your viewpoint. Make it clear what you want them to do or think after reading your essay.

Revise and Edit

Proofread your essay for grammar, spelling, and clarity. Make sure your arguments are well-structured and that your writing flows smoothly.

Seek Feedback 

Have someone else read your essay to get feedback. They may offer valuable insights and help you identify areas where your persuasive techniques can be improved.

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Common Topics for a Persuasive Essay on COVID-19 

Here are some persuasive essay topics on COVID-19:

  • The Importance of Vaccination Mandates for COVID-19 Control
  • Balancing Public Health and Personal Freedom During a Pandemic
  • The Economic Impact of Lockdowns vs. Public Health Benefits
  • The Role of Misinformation in Fueling Vaccine Hesitancy
  • Remote Learning vs. In-Person Education: What's Best for Students?
  • The Ethics of Vaccine Distribution: Prioritizing Vulnerable Populations
  • The Mental Health Crisis Amidst the COVID-19 Pandemic
  • The Long-Term Effects of COVID-19 on Healthcare Systems
  • Global Cooperation vs. Vaccine Nationalism in Fighting the Pandemic
  • The Future of Telemedicine: Expanding Healthcare Access Post-COVID-19

In search of more inspiring topics for your next persuasive essay? Our persuasive essay topics blog has plenty of ideas!

To sum it up,

You have read good sample essays and got some helpful tips. You now have the tools you needed to write a persuasive essay about Covid-19. So don't let the doubts stop you, start writing!

If you need professional writing help, don't worry! We've got that for you as well.

MyPerfectWords.com is a professional persuasive essay writing service that can help you craft an excellent persuasive essay on Covid-19. Our experienced essay writer will create a well-structured, insightful paper in no time!

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Frequently Asked Questions

Are there any ethical considerations when writing a persuasive essay about covid-19.

FAQ Icon

Yes, there are ethical considerations when writing a persuasive essay about COVID-19. It's essential to ensure the information is accurate, not contribute to misinformation, and be sensitive to the pandemic's impact on individuals and communities. Additionally, respecting diverse viewpoints and emphasizing public health benefits can promote ethical communication.

What impact does COVID-19 have on society?

The impact of COVID-19 on society is far-reaching. It has led to job and economic losses, an increase in stress and mental health disorders, and changes in education systems. It has also had a negative effect on social interactions, as people have been asked to limit their contact with others.

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cause and effect of covid 19 essay brainly

The world is grappling with an invisible, deadly enemy, trying to understand how to live with the threat posed by a virus . For some writers, the only way forward is to put pen to paper, trying to conceptualize and document what it feels like to continue living as countries are under lockdown and regular life seems to have ground to a halt.

So as the coronavirus pandemic has stretched around the world, it’s sparked a crop of diary entries and essays that describe how life has changed. Novelists, critics, artists, and journalists have put words to the feelings many are experiencing. The result is a first draft of how we’ll someday remember this time, filled with uncertainty and pain and fear as well as small moments of hope and humanity.

At the New York Review of Books, Ali Bhutto writes that in Karachi, Pakistan, the government-imposed curfew due to the virus is “eerily reminiscent of past military clampdowns”:

Beneath the quiet calm lies a sense that society has been unhinged and that the usual rules no longer apply. Small groups of pedestrians look on from the shadows, like an audience watching a spectacle slowly unfolding. People pause on street corners and in the shade of trees, under the watchful gaze of the paramilitary forces and the police.

His essay concludes with the sobering note that “in the minds of many, Covid-19 is just another life-threatening hazard in a city that stumbles from one crisis to another.”

Writing from Chattanooga, novelist Jamie Quatro documents the mixed ways her neighbors have been responding to the threat, and the frustration of conflicting direction, or no direction at all, from local, state, and federal leaders:

Whiplash, trying to keep up with who’s ordering what. We’re already experiencing enough chaos without this back-and-forth. Why didn’t the federal government issue a nationwide shelter-in-place at the get-go, the way other countries did? What happens when one state’s shelter-in-place ends, while others continue? Do states still under quarantine close their borders? We are still one nation, not fifty individual countries. Right?

Award-winning photojournalist Alessio Mamo, quarantined with his partner Marta in Sicily after she tested positive for the virus, accompanies his photographs in the Guardian of their confinement with a reflection on being confined :

The doctors asked me to take a second test, but again I tested negative. Perhaps I’m immune? The days dragged on in my apartment, in black and white, like my photos. Sometimes we tried to smile, imagining that I was asymptomatic, because I was the virus. Our smiles seemed to bring good news. My mother left hospital, but I won’t be able to see her for weeks. Marta started breathing well again, and so did I. I would have liked to photograph my country in the midst of this emergency, the battles that the doctors wage on the frontline, the hospitals pushed to their limits, Italy on its knees fighting an invisible enemy. That enemy, a day in March, knocked on my door instead.

In the New York Times Magazine, deputy editor Jessica Lustig writes with devastating clarity about her family’s life in Brooklyn while her husband battled the virus, weeks before most people began taking the threat seriously:

At the door of the clinic, we stand looking out at two older women chatting outside the doorway, oblivious. Do I wave them away? Call out that they should get far away, go home, wash their hands, stay inside? Instead we just stand there, awkwardly, until they move on. Only then do we step outside to begin the long three-block walk home. I point out the early magnolia, the forsythia. T says he is cold. The untrimmed hairs on his neck, under his beard, are white. The few people walking past us on the sidewalk don’t know that we are visitors from the future. A vision, a premonition, a walking visitation. This will be them: Either T, in the mask, or — if they’re lucky — me, tending to him.

Essayist Leslie Jamison writes in the New York Review of Books about being shut away alone in her New York City apartment with her 2-year-old daughter since she became sick:

The virus. Its sinewy, intimate name. What does it feel like in my body today? Shivering under blankets. A hot itch behind the eyes. Three sweatshirts in the middle of the day. My daughter trying to pull another blanket over my body with her tiny arms. An ache in the muscles that somehow makes it hard to lie still. This loss of taste has become a kind of sensory quarantine. It’s as if the quarantine keeps inching closer and closer to my insides. First I lost the touch of other bodies; then I lost the air; now I’ve lost the taste of bananas. Nothing about any of these losses is particularly unique. I’ve made a schedule so I won’t go insane with the toddler. Five days ago, I wrote Walk/Adventure! on it, next to a cut-out illustration of a tiger—as if we’d see tigers on our walks. It was good to keep possibility alive.

At Literary Hub, novelist Heidi Pitlor writes about the elastic nature of time during her family’s quarantine in Massachusetts:

During a shutdown, the things that mark our days—commuting to work, sending our kids to school, having a drink with friends—vanish and time takes on a flat, seamless quality. Without some self-imposed structure, it’s easy to feel a little untethered. A friend recently posted on Facebook: “For those who have lost track, today is Blursday the fortyteenth of Maprilay.” ... Giving shape to time is especially important now, when the future is so shapeless. We do not know whether the virus will continue to rage for weeks or months or, lord help us, on and off for years. We do not know when we will feel safe again. And so many of us, minus those who are gifted at compartmentalization or denial, remain largely captive to fear. We may stay this way if we do not create at least the illusion of movement in our lives, our long days spent with ourselves or partners or families.

Novelist Lauren Groff writes at the New York Review of Books about trying to escape the prison of her fears while sequestered at home in Gainesville, Florida:

Some people have imaginations sparked only by what they can see; I blame this blinkered empiricism for the parks overwhelmed with people, the bars, until a few nights ago, thickly thronged. My imagination is the opposite. I fear everything invisible to me. From the enclosure of my house, I am afraid of the suffering that isn’t present before me, the people running out of money and food or drowning in the fluid in their lungs, the deaths of health-care workers now growing ill while performing their duties. I fear the federal government, which the right wing has so—intentionally—weakened that not only is it insufficient to help its people, it is actively standing in help’s way. I fear we won’t sufficiently punish the right. I fear leaving the house and spreading the disease. I fear what this time of fear is doing to my children, their imaginations, and their souls.

At ArtForum , Berlin-based critic and writer Kristian Vistrup Madsen reflects on martinis, melancholia, and Finnish artist Jaakko Pallasvuo’s 2018 graphic novel Retreat , in which three young people exile themselves in the woods:

In melancholia, the shape of what is ending, and its temporality, is sprawling and incomprehensible. The ambivalence makes it hard to bear. The world of Retreat is rendered in lush pink and purple watercolors, which dissolve into wild and messy abstractions. In apocalypse, the divisions established in genesis bleed back out. My own Corona-retreat is similarly soft, color-field like, each day a blurred succession of quarantinis, YouTube–yoga, and televized press conferences. As restrictions mount, so does abstraction. For now, I’m still rooting for love to save the world.

At the Paris Review , Matt Levin writes about reading Virginia Woolf’s novel The Waves during quarantine:

A retreat, a quarantine, a sickness—they simultaneously distort and clarify, curtail and expand. It is an ideal state in which to read literature with a reputation for difficulty and inaccessibility, those hermetic books shorn of the handholds of conventional plot or characterization or description. A novel like Virginia Woolf’s The Waves is perfect for the state of interiority induced by quarantine—a story of three men and three women, meeting after the death of a mutual friend, told entirely in the overlapping internal monologues of the six, interspersed only with sections of pure, achingly beautiful descriptions of the natural world, a day’s procession and recession of light and waves. The novel is, in my mind’s eye, a perfectly spherical object. It is translucent and shimmering and infinitely fragile, prone to shatter at the slightest disturbance. It is not a book that can be read in snatches on the subway—it demands total absorption. Though it revels in a stark emotional nakedness, the book remains aloof, remote in its own deep self-absorption.

In an essay for the Financial Times, novelist Arundhati Roy writes with anger about Indian Prime Minister Narendra Modi’s anemic response to the threat, but also offers a glimmer of hope for the future:

Historically, pandemics have forced humans to break with the past and imagine their world anew. This one is no different. It is a portal, a gateway between one world and the next. We can choose to walk through it, dragging the carcasses of our prejudice and hatred, our avarice, our data banks and dead ideas, our dead rivers and smoky skies behind us. Or we can walk through lightly, with little luggage, ready to imagine another world. And ready to fight for it.

From Boston, Nora Caplan-Bricker writes in The Point about the strange contraction of space under quarantine, in which a friend in Beirut is as close as the one around the corner in the same city:

It’s a nice illusion—nice to feel like we’re in it together, even if my real world has shrunk to one person, my husband, who sits with his laptop in the other room. It’s nice in the same way as reading those essays that reframe social distancing as solidarity. “We must begin to see the negative space as clearly as the positive, to know what we don’t do is also brilliant and full of love,” the poet Anne Boyer wrote on March 10th, the day that Massachusetts declared a state of emergency. If you squint, you could almost make sense of this quarantine as an effort to flatten, along with the curve, the distinctions we make between our bonds with others. Right now, I care for my neighbor in the same way I demonstrate love for my mother: in all instances, I stay away. And in moments this month, I have loved strangers with an intensity that is new to me. On March 14th, the Saturday night after the end of life as we knew it, I went out with my dog and found the street silent: no lines for restaurants, no children on bicycles, no couples strolling with little cups of ice cream. It had taken the combined will of thousands of people to deliver such a sudden and complete emptiness. I felt so grateful, and so bereft.

And on his own website, musician and artist David Byrne writes about rediscovering the value of working for collective good , saying that “what is happening now is an opportunity to learn how to change our behavior”:

In emergencies, citizens can suddenly cooperate and collaborate. Change can happen. We’re going to need to work together as the effects of climate change ramp up. In order for capitalism to survive in any form, we will have to be a little more socialist. Here is an opportunity for us to see things differently — to see that we really are all connected — and adjust our behavior accordingly. Are we willing to do this? Is this moment an opportunity to see how truly interdependent we all are? To live in a world that is different and better than the one we live in now? We might be too far down the road to test every asymptomatic person, but a change in our mindsets, in how we view our neighbors, could lay the groundwork for the collective action we’ll need to deal with other global crises. The time to see how connected we all are is now.

The portrait these writers paint of a world under quarantine is multifaceted. Our worlds have contracted to the confines of our homes, and yet in some ways we’re more connected than ever to one another. We feel fear and boredom, anger and gratitude, frustration and strange peace. Uncertainty drives us to find metaphors and images that will let us wrap our minds around what is happening.

Yet there’s no single “what” that is happening. Everyone is contending with the pandemic and its effects from different places and in different ways. Reading others’ experiences — even the most frightening ones — can help alleviate the loneliness and dread, a little, and remind us that what we’re going through is both unique and shared by all.

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  • Published: 12 January 2021

Summary of the COVID-19 epidemic and estimating the effects of emergency responses in China

  • Junwen Tao   ORCID: orcid.org/0000-0002-2017-1726 1   na1 ,
  • Yue Ma   ORCID: orcid.org/0000-0002-1980-7520 1   na1 ,
  • Caiying Luo 1 ,
  • Jiaqi Huang 1 ,
  • Tao Zhang 1 &
  • Fei Yin 1  

Scientific Reports volume  11 , Article number:  717 ( 2021 ) Cite this article

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Coronavirus disease-2019 (COVID-19) pandemic has affected millions of people since December 2019. Summarizing the development of COVID-19 and assessing the effects of control measures are very critical to China and other countries. A logistic growth curve model was employed to compare the development of COVID-19 before and after the emergency response took effect. We found that the number of confirmed cases peaked 9–14 days after the first detection of an imported case, but there was a peak lag in the province where the outbreak was concentrated. Results of the growth curves indicated that the fitted cumulative confirmed cases were close to the actual observed cases, and the R 2 of all models was above 0.95. The average growth rate decreased by 44.42% nationally and by 32.5% outside Hubei Province. The average growth rate in the 12 high-risk areas decreased by 29.9%. The average growth rate of cumulative confirmed cases decreased by approximately 50% after the emergency response. Areas with frequent population migration have a high risk of outbreak. The emergency response taken by the Chinese government was able to effectively control the COVID-19 outbreak. Our study provides references for other countries and regions to control the COVID-19 outbreak.

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Introduction.

On December 31, 2019, China notified the World Health Organization (WHO) of unknown pneumonia cases in Wuhan, Hubei province 1 . This pneumonia came with persistent fever, cough, and dyspnea 2 and was then named Coronavirus Disease 2019 (COVID-19). The disease spread rapidly from Hubei province to other provinces in China within 2 weeks 3 , 4 . By November 14, 2020, a total of 92,409 confirmed cases and 4749 deaths had been reported in China, of which less than seventeen percent of the cases and less than four percent of the deaths occurred outside Hubei province. Since 13 January 2020, first Thailand 5 , then more than 200 countries, including Japan, Korea 6 , the United States 7 , and the United Kingdom 8 , have reported imported COVID-19 cases. Due to the speed and scale of transmission, the WHO described COVID-19 as a pandemic on 12 March 2020, officially declaring that COVID-19 entered the global epidemic phase.

Beginning 15 January 2020, the Chinese government launched an emergency response at all levels. On the one hand, in the epicenter of the outbreak, Hubei province implemented traffic control. On the other hand, the whole nation was required to wear masks and to avoid going out and having close contact with other people to reduce the exposure to susceptible people. As the earliest occurrence area, Hubei province has been through the process of case accumulation—outbreak detection—isolation and control. The rest of China has been through a complete process of case imports—detected transmission—isolation and control. Besides, as winter comes, the second wave of COVID-19 becomes one of the most important concerns of China and other countries. Those who have managed to take the COVID-19 epidemic under control are now threatened by the risk from imported cases while those who failed to flatten the epidemic curves are accumulating active cases continuously. Therefore, summarizing the COVID-19 development in Hubei province and other regions of China can help us to explore the epidemic characteristics of COVID-19 and provide a reference for other countries to assess the stages of the COVID-19 epidemic.

The course of COVID-19 includes incubation, disease, and recovery or death 2 , 9 . This course is characterized at the population level, as the number of cumulative confirmed cases experience a period of delay before exponential growth, then present a period of maximum increasing density, and finally enter a stable stage. The entire process presents an s-shaped development trend. A logistic growth curve model 10 is often used to describe such ecological processes 11 , 12 . Both the average growth rate and the maximum value of the growth curve have clear epidemiological significance and are of great reference value in the field of public health. Therefore, this study used the logistic growth curve model to evaluate the effects of emergency responses before and after implementation in two situations. One is in the epicenter, Hubei Province, in which numerical local transmissions have already occurred when the COVID-19 cases were firstly reported. The other is the regions with large immigration from the epicenter, mainly threatened by the importing risk. In addition, this study would extract historical data to simulate a short-term dynamic prediction and discussed the application of the growth curve model in the assessment of COVID-19 to provide a reference for China and other countries.

General characteristics of COVID-19 in China

Wuhan, Hubei province shut down outward traffic beginning 23 January 2020, followed by the rest of Hubei province. To find high-risk areas caused by imported cases, we drew a heatmap of the migration out of Hubei on 22 January 2020 (Fig.  1 a), which indicated that people mainly migrated to Henan, Hunan, Chongqing, Jiangxi, Guangdong, Anhui, Sichuan, Jiangsu, Zhejiang, Beijing, and Shanghai. A heatmap of the cumulative confirmed cases in Chinese provinces from 22 January to 4 March 2020 highlights similar provinces (Fig.  1 b). Hubei province was the location of the concentrated COVID-19 outbreak, followed by its neighbors (Henan, Anhui, Jiangxi, Hunan, and Chongqing) and some economically developed and densely populated provinces (Guangdong, Zhejiang, Jiangsu, Shandong, Sichuan, Shanghai, and Beijing). Thus, Sichuan, Guangdong, Beijing, Shandong, Chongqing, Zhejiang, Jiangxi, Anhui, Jiangsu, Hunan, Shanghai, and Henan were selected as high-risk areas with imported cases for further analysis. In addition, since over 80% of confirmed cases were reported in Hubei province (Table 1 : 81,047 cases were reported in China, in which 67,990 cases were reported in Hubei province), the epidemic characteristics in the rest part of China may be masked by that in Hubei province. Therefore, we also analyzed the national data excluding Hubei province to present the epidemic development in other provinces.

figure 1

( a ) Percentage of the migration population moving from Hubei province to other provinces on 22 January 2020. ( b ) The cumulative confirmed COVID-19 cases in Chinese provinces from 22 January to 4 March 2020.

According to the time series of the confirmed COVID-19 cases (except outliers) in China and 12 high-risk provinces, we summarized the peak confirmed cases, the corresponding peak date, and the cumulative number of confirmed cases (Table 1 ). Figure  2 shows the time series of confirmed COVID-19 cases in the identified provinces. The confirmed COVID-19 cases in Hubei province and nationwide showed a rapid increase before February 4, followed by a decline, and gradually stabilized after February 18, 2020. In high-risk provinces with imported cases, the peak of confirmed cases was around 30 January 2020 in Sichuan, Guangdong, Zhejiang, and Shanghai, and around 2 February 2020 in Beijing, Chongqing, Jiangxi, Anhui, Jiangsu, Hunan, and Henan.

figure 2

The time series of confirmed COVID-19 cases in China, Hubei province, and 12 high-risk provinces from 22 January to 4 March 2020.

Two outliers occurred in China and Hubei province on February 12 and 13, as the National Health Commission of the PRC revised the definition of COVID-19 confirmed cases in Hubei province on February 12, adding “clinical case” to “confirmed case,” and left the other provinces unchanged 13 . Another outlier was found in Shandong Province on February 20, corresponding to an outbreak at a prison with 200 confirmed cases 14 . The overall trend of confirmed cases in the other provinces increased first and then decreased.

Impact evaluation of emergency response

We fitted the growth curves at two different periods to assess the impact of the emergency response implemented in each province. Figure  3 shows the growth curves of each area. The coefficients of the logistic growth curve models in two periods are referred to the Supplementary Tables S2 and S3 . The fitted cumulative confirmed cases were close to the actual observed cases, and the R 2 of all models was above 0.95.

figure 3

The logistic growth curves of China, Hubei province, and 12 high-risk provinces before and after the emergency responses. Black points representing observed values, red lines representing fitted growth curves, and black dash lines representing two different periods’ cut-off points.

The average growth rates of the two periods in China, Hubei province, and 12 high-risk provinces are presented in Table 2 and Fig.  4 . The average growth rate decreased by 44.4% nationally and by 32.5% outside Hubei province. The average growth rate in each province decreased significantly after the emergency response. The average growth rate in the 12 high-risk areas decreased by 29.9%, which was lower than that outside Hubei province. Before the emergency response, the provinces with the highest average growth rates were ranked from highest to lowest as follows: Hunan, Hubei, Zhejiang, Shandong, Jiangxi, Jiangsu, Guangdong, Sichuan, Anhui, Henan, Chongqing, Beijing, and Shanghai. Hubei, Shandong, Zhejiang, Jiangxi, and Hunan had growth rates higher than the national average. After the emergency response, the average growth rate of each province from highest to lowest was Zhejiang, Hunan, Anhui, Shanghai, Jiangxi, Jiangsu, Hunan, Guangdong, Hubei, Chongqing, Beijing, Sichuan, and Shandong. The growth rates of Guangdong, Zhejiang, Jiangxi, Anhui, Jiangsu, Hunan, Shanghai, and Henan were higher than the national average.

figure 4

The comparison of the average growth rates before and after the emergency responses in China, Hubei province, and 12 high-risk provinces.

Prediction capacity evaluation of logistic growth curve models

We used cumulative confirmed case data, from January 22 to February 4, 2020, to simulate a short-term dynamic prediction. Table 3 shows the MAE and MAPE of the logistic growth curve model in each province. Figure  5 shows the 1-step dynamic prediction of the logistic growth curve model in China, Hubei province, and 12 high-risk provinces. The 1-step dynamic prediction outperformed the rest, with a MAPE of 1.16–5.45% in different areas. Except for the models for China, Hubei, and Shandong provinces, which were affected by the three outliers mentioned above, the models showed predictions close to the observations.

figure 5

The 1-step dynamic prediction of the logistic growth curve model in China, Hubei province, and 12 high-risk provinces. Black points representing observed values and orange lines representing fitted growth curves.

COVID-19 has currently become one of the biggest threats to the human world 15 , 16 . As the country reported the COVID-19 outbreak firstly, China issued national emergency responses 17 , 18 , including cross-regional traffic control and suspending the operations of restaurants, entertainment, and cultural tourism areas, and has taken the epidemic under control in early March. This study used the logistic growth curve models to summarize the COVID-19 epidemic in the epicenter, Hubei province, and other 12 high-risk provinces in China before and after the emergency responses. Results showed the areas with larger migration from Hubei province, have suffered more severe epidemics of the COVID-19. Prompt emergency responses after the detection of imported cases greatly reduced the growth rate of the local epidemic. Also, in the early stage without adequate information for more detailed dynamic prediction models, the logistic growth curve model has good prediction accuracy in the short-term forecast.

Before the shutdown of the traffic leaving Wuhan, Hubei province, people from Hubei province mainly migrated to Henan, Hunan, Chongqing, Jiangxi, Guangdong, Anhui, Sichuan, Jiangsu, Zhejiang, Beijing, and Shanghai, which was consistent with provinces later had high incidences of COVID-19. It indicated that the people migration was related to the spread of the COVID-19 epidemic. This finding can be supported by other studies 19 , 20 . As a respiratory infectious disease, the number of transmission sources and susceptible population density directly affects the COVID-19 spread 21 . Blocking migration from severe outbreak areas would be of great importance to prevent the disease from spreading to other areas, especially during the early stages. Tian et al. found that the confirmed cases reported in lockdown cities decreased by 37% than those cities without lockdown in China 22 . In addition, Flaxman et al. estimated the effects of non-pharmaceutical interventions on COVID-19 in 11 European countries and found that lockdown had a large effect on controlling the epidemic 23 .

The peak outbreak occurred from February 1 to February 4, 2020, which could be related to the population migration and the incubation of COVID-19. As January 25 was the traditional Chinese New Year, most people were returning to their hometowns to reunite with their families. Therefore, the densified migration in the week before the traditional Chinese New Year led to the rapid spread of COVID-19. With the estimated 3–7 days incubation, each province experienced 9–14 days from the first detection of imported cases to the peak of confirmed cases, which was consistent with the sum of the migration peak and the incubation period. Therefore, 9–14 days after the detection of imported cases is the critical period for preventing further transmission. In this period, screening tests and the quarantine of COVID-19 patients should be carried out to find the infection source and protect susceptible populations. Notably, in the region with the most severe outbreak, Hubei province, the peak of confirmed cases was delayed, which is consistent with the findings of Sun et al. 24 . They found that delays between suspected infection and seeking care at a hospital were longer in Hubei province than in other provinces. This phenomenon may be attributed to the long accumulation of confirmed cases and inadequate testing capacity, suggested that more health resources are needed in such an area.

The logistic growth curves of cumulative COVID-19 cases before and after the implementation of emergency response in each study province showed an approximate 50% reduction in the average growth rate after the emergency response, similar to the result of Lai’s study. Lai et al. predicted the confirmed cases would have been 67-fold higher by 29 February 2020 without the emergency response in China 25 . As all the emergency responses were launched within 1 week after the first confirmed case, the reduction in the average growth rate suggested that rapid growth of the epidemic can be slowed by a timely emergency response after the early detection of imported cases within the critical period of 9–14 days.

The average growth rate in Zhejiang, Jiangsu, Anhui, Jiangxi, Hunan, Shanghai, and Henan provinces remained higher than the national average growth rate after the implementation of the emergency response. Among them, the economically developed provinces, and labor-exporting provinces with frequent population migration, such as Zhejiang, Hunan, and Anhui provinces, had the highest growth rates, indicating a high outbreak risk. Therefore, the control measures should be particularly strengthened to prevent COVID-19 outbreaks in these regions. Although the emergency response reduced the average growth rate, in the outbreak center, Hubei province, the peak in confirmed cases was delayed. This suggests that if the outbreak was not detected in time, the critical control period might pass, which would lead to a lag in the implementation of prevention and control measures in response to the outbreak. Therefore, for concentrated COVID-19 outbreak areas, the growth of the epidemic would not be easily controlled within the standard critical period of 9–14 days. The lagged peak of confirmed cases should be fully considered, and the duration of control measures should be extended for further development of the epidemic. And a study in the UK suggested that to avoid a rebound, the control measures should be maintained until a vaccine is available, which might be about 18 months 26 .

In the 1-step dynamic prediction of the cumulative confirmed COVID-19 cases in the early stage of the epidemic, the MAPE between the predicted and actual cumulative cases was 1.16–5.45%. Despite the increase due to the change in diagnostic criteria on February 13 in Hubei province, the values predicted by the logistic growth curve model were very close to the actual observed values. Thus, the logistic growth curve model can be used to assess the short-term development of COVID-19 and aid in the short-term adjustment of prevention and control measures, especially in the early stage of the epidemic.

There are several limitations to this study. As based on the existing surveillance data, the detection capacity of COVID-19 varies between different regions, which may lead to an underestimated occurrence at the early stage, and the outbreak reflected by the surveillance data may be delayed. Each region should consider local detection capacity when formulating prevention and control measures.

In conclusion, areas with frequent migration have a high risk of COVID-19 outbreak, so the prevention and control measures should be strengthened. Timely detection of imported cases and blocking migration from the epidemic areas are important for controlling the spread of COVID-19. The 9–14 days after the first detection of imported cases could be the critical period for epidemic prevention and control. In areas where the epidemic is severe, we need to consider the peak lag and extend prevention measures. The emergency responses launched in China efficiently reduced the spread and further development of the epidemic, which provides a reference for other countries and regions, especially facing a new wave coming with the winter. The logistic growth curve model can accurately evaluate and predict the short-term development of the COVID-19 epidemic.

Data sources

Confirmed COVID-19 case data were obtained from the Chinese Center for Disease Control and Prevention 27 . All cases were confirmed by laboratory and clinical diagnosis and met the definition of confirmed cases according to the National Health Commission of China 28 . Baidu is the most widely used search engine in China, and we extracted population migration data from the Baidu Qianxi to find areas with early imported cases 29 . Considering that in the early stages of the COVID-19 outbreak, the situation reports may have underreported cases while the national new daily case has been reduced to the level around one hundred to the beginning of the March and kept at a low level in further, we used confirmed cases from 22 January to 4 March 2020 to ensure the reliability of the data.

Statistical analysis

This study used heatmaps to conduct a spatiotemporal distribution analysis of cumulative confirmed COVID-19 cases and population migration in China on a provincial level. The heatmaps were constructed with the cumulative confirmed cases and population migration data via the “rgdal” and “ggplot2” packages in R 3.6.3. We selected Hubei province as the concentrated outbreak area for analysis, and other provinces with early reported cases as representative provinces facing the risk of an outbreak.

The logistic growth curve is a statistical model used to simulate the growth of cells, animals, plants, or populations. In a finite population, the logistic growth curve presents s-shaped. The parameters of this model have clear epidemiological significance and are of great reference value in the field of public health. Therefore, this study used the logistic growth curve model to summarize the characteristics of the COVID-19 epidemic and to evaluate the effects of emergency responses in China. The formula for the model is as follows:

where N t represents the cumulative confirmed COVID-19 cases at time t, N 0 represents the cumulative confirmed cases at the initial time, K represents the maximum cumulative confirmed cases within the analysis period, and r is the average growth rate of the cumulative confirmed cases. The “SummarizeGrowth()” function was used to fit the growth curve model via the “growthcurver” package in R 3.6.3.

To evaluate the effects of the emergency response implemented in each province, we fitted the logistic growth curve models at two different periods, using an average incubation period of 7 days 24 , 28 after the emergency response implemented date as the cut-off point (for details of the time period, see Supplementary Table S1 ). The first time period was used to assess the situation before the emergency response. The second time period, from the end of period one to 4 March 2020, was used to assess the situation after the emergency response had taken effect. The coefficient of determination ( R 2 ) was used to evaluate the goodness of fit. The average growth rates of periods one and two in each province were compared to evaluate the effects of the emergency response.

To simulate the short-term trend of the epidemic, we used the logistic growth curve model for dynamic prediction from 22 January to 4 March 2020 30 . The step lengths of the dynamic predictions were set as 1, 3, and 7 days, referred to as the 1, 3, or 7 out-of-sample prediction. In the 1 out-of-sample prediction, the cumulative confirmed cases from January 22 to February 4 were selected as the training set, and 1 day after, February 5, was selected as the test set. Then, the model was updated with actual observations from February 5, and the cumulative confirmed cases on February 6 were predicted by the updated model until all the predicted cumulative confirmed cases from February 5 to March 4 were obtained. The average absolute error (MAE) and average absolute percentage error (MAPE) were then calculated for each dynamic prediction with different step lengths to evaluate the short-term trend of the epidemic.

All statistical analyses were performed in R 3.6.3 using packages such as “growthcurver”, “rgdal” and “ggplot2”.

Data availability

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 81872713 and 81803332) and Sichuan Science & Technology Program (Grant Nos. 2019YFS0471, 2020YFS0015, 2020YFS0091 and 21ZDYF1793).

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These authors contributed equally: Junwen Tao and Yue Ma.

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West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China

Junwen Tao, Yue Ma, Caiying Luo, Jiaqi Huang, Tao Zhang & Fei Yin

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F.Y. and Y.M. designed the study, collected data, and contributed to data analysis. J. T. contributed to the literature search, data analysis, data interpretation, figures, and writing. C.L., J.H., and T.Z. contributed to data interpretation. All authors contributed to writing the manuscript and revising the final version.

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Correspondence to Fei Yin .

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Tao, J., Ma, Y., Luo, C. et al. Summary of the COVID-19 epidemic and estimating the effects of emergency responses in China. Sci Rep 11 , 717 (2021). https://doi.org/10.1038/s41598-020-80201-8

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Effects of COVID-19 pandemic in daily life

Dear Editor,

COVID-19 (Coronavirus) has affected day to day life and is slowing down the global economy. This pandemic has affected thousands of peoples, who are either sick or are being killed due to the spread of this disease. The most common symptoms of this viral infection are fever, cold, cough, bone pain and breathing problems, and ultimately leading to pneumonia. This, being a new viral disease affecting humans for the first time, vaccines are not yet available. Thus, the emphasis is on taking extensive precautions such as extensive hygiene protocol (e.g., regularly washing of hands, avoidance of face to face interaction etc.), social distancing, and wearing of masks, and so on. This virus is spreading exponentially region wise. Countries are banning gatherings of people to the spread and break the exponential curve. 1 , 2 Many countries are locking their population and enforcing strict quarantine to control the spread of the havoc of this highly communicable disease.

COVID-19 has rapidly affected our day to day life, businesses, disrupted the world trade and movements. Identification of the disease at an early stage is vital to control the spread of the virus because it very rapidly spreads from person to person. Most of the countries have slowed down their manufacturing of the products. 3 , 4 The various industries and sectors are affected by the cause of this disease; these include the pharmaceuticals industry, solar power sector, tourism, Information and electronics industry. This virus creates significant knock-on effects on the daily life of citizens, as well as about the global economy.

Presently the impacts of COVID-19 in daily life are extensive and have far reaching consequences. These can be divided into various categories:

  • • Challenges in the diagnosis, quarantine and treatment of suspected or confirmed cases
  • • High burden of the functioning of the existing medical system
  • • Patients with other disease and health problems are getting neglected
  • • Overload on doctors and other healthcare professionals, who are at a very high risk
  • • Overloading of medical shops
  • • Requirement for high protection
  • • Disruption of medical supply chain
  • • Slowing of the manufacturing of essential goods
  • • Disrupt the supply chain of products
  • • Losses in national and international business
  • • Poor cash flow in the market
  • • Significant slowing down in the revenue growth
  • • Service sector is not being able to provide their proper service
  • • Cancellation or postponement of large-scale sports and tournaments
  • • Avoiding the national and international travelling and cancellation of services
  • • Disruption of celebration of cultural, religious and festive events
  • • Undue stress among the population
  • • Social distancing with our peers and family members
  • • Closure of the hotels, restaurants and religious places
  • • Closure of places for entertainment such as movie and play theatres, sports clubs, gymnasiums, swimming pools, and so on.
  • • Postponement of examinations

This COVID-19 has affected the sources of supply and effects the global economy. There are restrictions of travelling from one country to another country. During travelling, numbers of cases are identified positive when tested, especially when they are taking international visits. 5 All governments, health organisations and other authorities are continuously focussing on identifying the cases affected by the COVID-19. Healthcare professional face lot of difficulties in maintaining the quality of healthcare in these days.

Declaration of competing interest

None declared.

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    Other infections, such as the flu and polio, can lead to long-term illness. But the virus that causes COVID-19 has only been studied since it began to spread in 2019. So, research into the specific effects of long-term COVID-19 symptoms continues. Researchers do think that post-COVID-19 syndrome can happen after an illness of any severity.

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    Reading time: 3 min (864 words) The COVID-19 pandemic has led to a dramatic loss of human life worldwide and presents an unprecedented challenge to public health, food systems and the world of work. The economic and social disruption caused by the pandemic is devastating: tens of millions of people are at risk of falling into extreme poverty ...

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    Outlook. Many health experts believe that the new strain of coronavirus likely originated in bats or pangolins. The first transmission to humans was in Wuhan, China. Since then, the virus has ...

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    The transition to an online education during the coronavirus disease 2019 (COVID-19) pandemic may bring about adverse educational changes and adverse health consequences for children and young adult learners in grade school, middle school, high school, college, and professional schools. The effects may differ by age, maturity, and socioeconomic ...

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    A novel coronavirus (CoV) named '2019-nCoV' or '2019 novel coronavirus' or 'COVID-19' by the World Health Organization (WHO) is in charge of the current outbreak of pneumonia that began at the beginning of December 2019 near in Wuhan City, Hubei Province, China [1-4]. COVID-19 is a pathogenic virus. From the phylogenetic analysis ...

  8. Understanding COVID-19

    COVID-19 has claimed millions of lives around the world. But we learn more about this disease every day. Scientists are developing tools that promise to slow and eventu­ally help us overcome the pandemic. COVID-19 is caused by a new coronavirus called SARS-CoV-2. There are many types of coronaviruses. Some cause the common cold.

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    COVID-19 is caused by the SARS-CoV-2 virus. COVID-19 can cause mild to severe respiratory illness, including death. The best preventive measures include getting vaccinated, wearing a mask during times of high transmission, staying 6 feet apart, washing hands often and avoiding sick people. Contents Overview Symptoms and Causes Diagnosis and ...

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    COVID-19: Emergence, Spread, Possible Treatments, and Global Burden. The Coronavirus (CoV) is a large family of viruses known to cause illnesses ranging from the common cold to acute respiratory tract infection. The severity of the infection may be visible as pneumonia, acute respiratory syndrome, and even death.

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    COVID-19 is a social action, and it can also be considered a great social problem on the basis of Richard Puller's definition. When looked at generally, COVID-19 is a disease spreading through close human contacts in day-to-day social relationships. ... This may cause some effects in supply chain networks in Sri Lanka as well as South Asian ...

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    Answer: The coronavirus disease (COVID-19) is caused by a virus, NOT by bacteria. The virus that causes COVID-19 is in a family of viruses called Coronaviridae. Antibiotics do not work against viruses. Some people who become ill with COVID-19 can also develop a bacterial infection as a complication. In this case, antibiotics may be recommended ...

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    We investigate the relationship between media consumption, misinformation, and important attitudes and behaviours during the coronavirus disease 2019 (COVID-19) pandemic. We find that comparatively more misinformation circulates on Twitter, while news media tends to reinforce public health recommendations like social distancing. We find that exposure to social media is associated with ...

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