research on unemployment in kenya

State of Youth Unemployment in Kenya

Subscribe to africa in focus, boaz munga and boaz munga senior policy analyst - kenya institute for public policy research and analysis (kippra) eldah onsomu eldah onsomu principal policy analyst - kenya institute for public policy research and analysis (kippra).

August 21, 2014

• 11 min read

Editor’s Note: This blog is part of a collection of posts discussing sub-Saharan Africa’s high youth unemployment rate and policies to combat it. In this series, scholars explore the complex challenges around youth unemployment facing policymakers in South Africa , Ghana, Kenya, Uganda and Nigeria.

Introduction and Incidence of Unemployment in Kenya

The unemployment problem is global and presents a particularly difficult labor market experience for youth. In Africa especially, unemployment and underemployment continue to be major obstacles to the full utilization of human resources despite relatively strong growth in the region over the last decade.

Youth in Kenya are experiencing much higher unemployment rates than the rest of the Kenyan population, as seen in Table 1. In 2005/06, youths aged 15-19 and 20-24 years had unemployment rates of 25 percent and 24 percent, respectively—about double the overall unemployment of 12.7 percent for the entire working-age group. Based on the 2009 census, the open unemployment rates declined for youth, but among youth aged 15-19 and 20-24 years these rates were about 15.8 percent and 13.1 percent, respectively—relative to a total unemployment rate of 8.6 percent. Interestingly, in recent years, the unemployment rates of females and males aged 15-19 and 20-24 years are quite comparable, though this trend is similar across all age groups in Kenya. For example, in 2009, male youth aged 20-24 years had an unemployment rate of 13.6 percent relative to the females’ rate of 12.6 percent.

There is a substantial variation in unemployment rates in urban and rural regions. In 2005/06 as well as 2009, the respective urban total unemployment rates of 19.9 percent and 11.0 percent were about twice as large as the rural rates. Like the national trends, within these regions, youth unemployment was much larger than that of the working-age population. In urban areas in 2009, for instance, the overall unemployment rate was about 11.0 percent relative to a youth (20-24 years) unemployment rate of 19.1 percent.

Unemployment Versus Related Labor Market Challenges

In a developing country such as Kenya, the estimated unemployment rates underestimate the enormity of the labor market challenge because a large number of individuals are inactive [1] rather than unemployed, and most of the individuals in employment are engaged in informal jobs. It is thus important to look at other related challenges, such as inactivity and informal employment, for a fuller appreciation of the labor market challenge facing youth (Boateng, 2000).

Figure 1 illustrates a broader representation of the challenges relating to youth employment. A key message emanating from Figure 1 is that unemployment, using the narrow or broad definition, is just one of the labor market challenges facing the Kenyan youth. The largest share of Kenyan youth—about 48.6 percent—was employed in 2009, and nearly 33 percent were full-time students. Even though a large share of youth is employed, most are engaged in informal activities. In 2009, about 84 percent of employed youth aged 15 to 24 years were in informal employment (which provides a rough estimate of individuals engaged in vulnerable jobs). Importantly, the proportion of inactive youths exceeds the proportion that is unemployed; about 10.2 percent were inactive (mainly “homemakers”) while an 8 percent share was unemployed.

Clearly then, besides addressing unemployment, policy interventions should focus on the issues of job quality and youth inactivity. In terms of policy interventions, the demarcation of the related challenges is vital, since what might work in reducing unemployment may not address poor quality jobs or inactivity. 

Educational Attainment and Labor Market Status of the Youth

A second key point this article seeks to convey relates to education. A majority of youth are still stuck at low levels of educational achievement. Specifically, 62 percent of youth aged 15-34 years have below secondary level education, 34 percent have secondary education, and only 1 percent have university education.

Educational attainment appears to have a strong influence on an individual’s labor market activity. Compared to employed individuals, the openly unemployed and inactive youths have a higher proportion of individuals who “never went to school.” In addition, about 90 percent of all employed individuals whose highest level of education is primary school are engaged in vulnerable jobs, compared to 61 percent and 21 percent for those with at least secondary and university qualifications, respectively. Other census-related data indicates that about 40 percent of Kenya’s youth either “never attended school” or “did not complete primary education.”

Despite the country’s free primary and secondary education policy that greatly subsidizes basic education, it is estimated that about 14 percent of the approximately 10.6 million children (aged between 5 and 14 years) left school or never attended school in 2009, and about 68 percent of secondary school-age youth (between 14-17) were not in school. These children are likely to become youths with little employable labor market skills over the next decade.

A Review of Public Policies

Because unemployment has been viewed to be generally high in the recent past, it may be difficult to identify relatively successful public policies. But in one way or another, different policy interventions had their own successes and failures. Broad policy frameworks such as the Economic Recovery Strategy for Wealth and Employment Creation (ERSWEC) ( Government of Kenya, 2003 ) are credited for the upturn in economic growth beginning in 2003 (and averaging 5.44 percent in 2003-2007 compared to 1.72 percent in 1998-2002) and whose momentum continues to date (but was briefly interrupted by the post-election violence in 2007-2008). However, the economic growth rate was perhaps not large enough to reduce unemployment rates significantly. Employment creation grew at about half a million jobs per year, but most of the jobs created were in the informal sector . The economy thus failed to create good quality jobs for its ever-growing labor force.

Not-So-Successful Policies

The International Labor Organization (ILO) sent a Comprehensive Employment Mission to Kenya in 1972. The multi-disciplinary mission analyzed and gave recommendations on a report titled “Employment, incomes and equality,” in which it coined the phrase “informal sector.” The report considered the informal sector instrumental in creating employment and income generation (ILO, 1972). The ILO mission noted that the “informal sector activities were largely ignored, rarely supported … and sometimes actively discouraged by the Government” despite the “sector’s resilience.” Up until now, the informal sector in Kenya has grown and currently employs about 81 percent of workers. And for a long time, the government has generally lacked policy interventions addressing the issue of informality and small and medium enterprises.

Two notable interventions were the Sessional Paper No. 2 of 1992 on Small Enterprise and Jua Kali Development in Kenya, and Sessional Paper No. 2 of 2005 on Development of Micro and Small Enterprises for Wealth and Employment Creation for Poverty Reduction, which puts emphasis on the micro and small enterprise (MSE) sector (Gitonga, 2008). The Sessional papers concentrated on creating an enabling environment for these businesses, providing credit, and developing non-financial promotional programs.

Even so, gaps still remain. First, the policies failed to clearly demarcate the formal from the informal economy/sector, and thus failed to provide clear incentives for firms to formalize. Within policy circles, the terms MSEs, Jua Kali and “informal sector” are used interchangeably, yet not all MSEs are actually informal. In addition, the policy does not demarcate between survivalist and growth-oriented enterprises (Gitonga, 2008). Interventions are thus blind to the different needs of the heterogeneous establishments. Second, with respect to taxation and statutory requirements, formal MSEs tend to be treated in a similar manner to large firms, hence diminishing incentives for informal MSE firms to formalize their operations.

Another challenge is that access to formal credit by a majority of MSEs is relatively low . The majority of non-agricultural small enterprises (74 percent) rely on either their own savings or funds from family members for their initial capital. The study concludes that there is significant room to improve access to credit for better performance of the MSE sector.

Relatively Successful Policies

The Kenya Jua Kali Voucher Programme —an intervention aimed at making training systems work better for young people—was an example of a relatively successful unemployment policy . It was initiated in 1997 as a pilot scheme under the Micro and Small Enterprise Training and Technology Project and addressed training market failures by making information available, providing credit and other financial incentives, and reducing location-related barriers.

Eligible unemployed persons (mainly the disadvantaged youth) were given vouchers that they could use to pay for training at a provider of their choice. This design had two advantages: First, it ensured a better match between the participant and the training course; and second, it generated competition among training providers (mainly master craftsmen), hence improving the quality of training. About 37,606 vouchers were issued in firms with 50 or fewer workers in 1997–2001. Participants paid only 10 percent of the cost of the voucher, while the government subsidy covered the rest.

Evidence suggests that the scheme increased employment and assets of participants in comparison to a control group. However, it highlighted a number of implementation challenges that such schemes might face. First, programs like these are complex and costly to establish. Second, it is difficult to phase out the training subsidy, which in itself may be a source of distortion of the training market.

Such challenges can be overcome by having an exit strategy upfront before rolling out the scheme, and promote willingness of clients to pay for training. It is thought that the private sector may be a more successful channel through which the subsidy could be channeled.

Other ongoing interventions include the Youth Enterprise Development Fund , which provides loans and other support to youth enterprises, and the Uwezo Fund , which provides grants and interest-free loans to women and youth. While no impact evaluation has been done to assess the effects of these initiatives, it is hoped that they will contribute to addressing Kenya’s youth unemployment challenge.

Unemployment rates estimated in the last two national surveys and the 2009 Kenya Population Census suggest that open unemployment among youth aged 15-19 and 20-24 years is significantly larger than that of the entire working age group.

Although the government and other stakeholders tend to put more focus on unemployment, there should be sustained effort to address labor market related challenges that encompass remedies for “inactivity” and “poor quality jobs” as well. This is because inactivity and poor quality jobs actually affect a larger share of youth relative to those openly unemployed.

There is a case for an urgent enhancement of interventions that promote access to quality basic education for the youth for better labor market outcomes. This is because many youths are still stuck at low levels of educational achievement—and education appears to have a strong influence on an individual’s labor market activity. In addition, some policy interventions such as the MSE sector interventions have had their shortcomings. A key lesson for the government and other stakeholders is the need to effectively diagnose the challenges, and also monitor and evaluate policy interventions to inform subsequent interventions. 

Note:   Boaz Munga is a policy analyst in the Social Sector Division of the Kenya Institute for Public Policy Research and Analysis (KIPPRA). Eldah Onsomu is a policy analyst in the Social Sector Division of KIPPRA. KIPPRA is one of the Brookings Africa Growth Initiative’s six local think tank partners based in Africa. This blog reflects the views of the authors only and does not reflect the views of the Africa Growth Initiative.

[1] The inactive include: homemakers, those not working but who took “no action” in seeking work, the incapacitated and the retired. In some cases, full-time students are included. But in this analysis full-time students are excluded from the inactive category.

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Johanson, Richard and Arvil V. Adams (2004). Skills Development in Sub‐Saharan Africa. Regional and Sectoral Studies, World Bank, Washington, DC. Accessed: http://siteresources.worldbank.org/EDUCATION/Resources/278200-1126210664195/1636971-1126210694253/Skills_Development_Africa.pdf

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Ryan, T.C.I. (2002). Policy Timeline and Time Series Data for Kenya: An Analytical Data Compendium. Kenya Institute for Public Policy Research and Analysis (KIPPRA) Special Report No. 3. Nairobi: KIPPRA. Accessed: http://www.worldcat.org/title/policy-timeline-and-time-series-data-for-kenya-an-analytical-data-compendium/oclc/123376839

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EFFECTS OF INFLATION AND UNEMPLOYMENT ON ECONOMIC GROWTH IN KENYA

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A STUDY ON THE CAUSES OF UNEMPLOYMENT AMONG UNIVERSITY GRADUATES IN KENYA: A CASE OF GARISSA COUNTY, KENYA

Unemployment is a major problem in Kenya. It has made many young university graduates demoralized. Unemployment rate has risen so high that in every 10 young people, close to 4 are jobless with requisite qualifications. Successive governments have done little to arrest the situation. This research was done to understand the causes of unemployment in Kenya and the solutions that can be put in place to mitigate the problem. The effects of unemployment and the relationship between creation of opportunities and the growth of economy. The research found out that unemployment in Kenya is very high. This shows lack of confidence they have the system in place. The main effects of unemployment are crime, corruption, nepotism and favourism, high dependency and drug abuse. Being a job creator rather than a job seeker is the major solution of unemployment in Kenya. The research also found out that aligning the education curriculum in line with the demand of the market is paramount and should be hastened. In conclusion, unemployment has caused a lot of problems in Kenya. The research recommended a raft of measures to reduce the issue of unemployment in the country. Encourage the youth to be job creators and not job seekers only. Universities should play an important role in this case. Universities should develop courses that are relevant and demand driven. Duplication of courses with fewer demands should be minimized as this will flood graduates with similar courses that are not needed at all. Technical education should be enhanced and proper mechanisms put in place to sponsor and encourage students to take up these courses. Strict regulations should be enacted to fight corruption, nepotism and favourism. Kenya needs a practical and proactive solution for this monster.

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Federal Minimum Wage”, Industrial and Labour Relations Review, Vol. 46, pp 22-37.

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Republic of Kenya (1999). National Poverty Eradication Plan. Government Printer: Nairobi.

World Bank (2008). Kenya: Accelerating and Sustaining Inclusive Growth. Washington DC: World Bank. Accessed: http://s3.marsgroupkenya.org/media/documents/2011/02/13feaeaf037e1ce

d67c9039.pdf

Government of Kenya (2008). Sessional Paper No. 7 of 2005 on Employment Policy and Strategy for Kenya. Nairobi: Government Printer.

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International Labour Organization (ILO) (1972). Employment, Incomes and Equality. A Strategy for Increasing Productive Employment in Kenya. Geneva: ILO.

Accessed: http://www.ilo.org/public/libdoc/ilo/1972/72B09_608_engl.pdf

Johanson, Richard and Arvil V. Adams (2004). Skills Development in Sub‐Saharan Africa. Regional and Sectoral Studies, World Bank, Washington, DC.

Accessed: http://siteresources.worldbank.org/EDUCATION/Resources/278200-

/1636971-1126210694253/Skills_Development_Africa.pdf

Kenya National Bureau of Statistics (KNBS) (2008). Labour Force Analytical Report – Based on the Kenya Integrated Household Budget Survey (2005/2006). Nairobi: Government Printer.

Ryan, T.C.I. (2002). Policy Timeline and Time Series Data for Kenya: An Analytical Data Compendium. Kenya Institute for Public Policy Research and Analysis (KIPPRA) Special Report No. 3. Nairobi: KIPPRA.

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Nigeria’s dichotomy: low unemployment, high poverty rates

Jonathan lain.

When analyzing poverty, only looking at unemployment rates will be insufficient and misleading. Instead, job quality – underemployment, people’s specific activities and occupations, and markers of formality – is fundamental for understanding the labor market and providing recommendations for policies.

In the case of a country like Nigeria, unemployment has proved a difficult statistic to interpret. Nigeria’s unemployment rate stood at 33.3 percent in Q4 of 2020. However, the National Bureau of Statistics (NBS) recently reported unemployment rates of 5.3 percent (Q4 2022) and 4.1 percent (Q1 2023), based on the new Nigeria Labour Force Survey (NLFS).

How can this make sense?

To begin, the definition of unemployment has changed to bring it more in line with the standards of the International Labour Organization (ILO). For the new NLFS, the “employed” covers anyone who worked one hour or more for pay or profit in the last seven days, even if they were temporarily absent. The “unemployed” are those individuals who are not employed but are (1) actively searching for paid work and (2) available to start paid work, either last week or within the next two weeks.

In Nigeria’s previous Unemployment Reports , the headline unemployment rate – like the 33.3 percent in Q4 2020 – included not only those who were not employed (and were searching and available) but also those working 1-19 hours per week. Thus, this headline number mixed unemployment and some proxy of time-based underemployment – although alongside this, NBS always reported unemployment according to the “international” definition as well. Additionally, temporary absences were not explicitly considered before, so the new approach correctly expands the count of employed people.

Another change in the definition moves subsistence agricultural workers from being counted as “employed” to being out of the labor force, as they produce goods for households rather than for the market. This way, they are treated in the same way as household members providing services for their household, like childcare, water fetching, cooking and so on. On top of these definitional and questionnaire changes, the new NLFS has made crucial improvements to sampling, fieldwork management, and data quality monitoring – this includes limiting the bias brought about by “proxy response”, whereby one household member responds to the questionnaire on behalf of another.

Equipped with these improvements, the new unemployment rate can be interpreted more clearly, as it avoids lumping together different concepts including unemployment, time-based under-employment, and a notion of sufficient livelihoods. It also allows international comparison. For example, Nigeria’s unemployment rate is of the same magnitude as in all of Western and Central Africa, where it stood at 4.7 percent in 2022.

Unemployment in Nigeria and in Western and Central Africa

Note: NLFS standard errors clustered by enumeration area and adjusted for state-level stratification of the sample. Source: NLFS, World Development Indicators, and NBS calculations.

The unemployment rate is also consistent with the situation pre-COVID. We built a bridge to previous data by harmonizing the working age, the treatment of temporary absences, and the treatment of subsistence agriculture, as well as applying the ILO definition of unemployment.

Before 2018, unemployment rates (using the “international” methodology) were always single digit, in line with the current estimates. It was only during the COVID-19 period that unemployment spiked in Nigeria.

Unemployment rate estimates for Nigeria, 2014-2023

Note: New international definition of unemployment classes those who are not working/employed even for one hour but who are searching and available as unemployed. Estimates from COVID-19 period shown in lighter shade. Source: NBS Unemployment Reports, 2018/19 NLSS, NLFS, and World Bank estimates.

But how meaningful is a single-digit unemployment rate in a country where around a third of the population lives in poverty? The unemployment rate is certainly helpful in understanding seasonal fluctuations and short-term shocks. Yet there is no guarantee that it is correlated with poverty  – the most direct measure of whether people have sufficient livelihoods.

In fact, many poor countries have very low unemployment. And within Nigeria, poor and non-poor Nigerians were about equally likely to work in 2018/19. Unemployment was, if anything, higher among richer households.

Poverty and unemployment in Nigeria’s neighbors and other comparator countries

Note: Poverty rate calculated using the latest available data and the 2.15 USD 2017 PPP per person per day international poverty line. Unemployment rates shown are the ILO modeled estimates. Source: Poverty and Inequality Platform, ILOSTAT, and World Bank estimates.

How can poverty and unemployment move in different directions? When prices increase but wages remain low, households – and especially the poorest among them – have to find any means to increase household income.  They will find some work to do, for example, through small-scale agriculture, petty trading, or basic services – even if this work has very low productivity.

At the same time, richer households can afford to remain unemployed for longer  while searching for a better job. Most Nigerians cannot afford to spend long spells out of employment searching for jobs, especially given the sparse coverage of social protection . Without such support, “if you do not work, you cannot eat”, and unemployment can stay low, even when poverty is widespread.

Therefore, to understand the structural health of an economy and its labor market, we need to be more nuanced with the help of additional indicators. Poverty and wellbeing are determined much more by what you do rather than whether you are employed.   For example, wage jobs – being employed and paid by someone else – are better at keeping workers out of poverty. Such jobs, however, are rare in Nigeria: just 11.8 percent of employed Nigerians were primarily engaged in wage jobs in Q1 2023.

Some employed Nigerians are “underemployed”, meaning that they work less than 40 hours per week but declare themselves willing and available to work more. About 12.2 percent of employed Nigerians were underemployed in Q1 2023. Some Nigerians even search on the job, reflecting dissatisfaction with their current job or earnings. Around 7.2 percent of working-age Nigerians were employed, but searching for additional work in Q1 2023.

Policymakers should therefore not focus indiscriminately on creating any kind of job. This is the risk of blindly focusing on unemployment. The economy needs to generate productive jobs and meaningful work that can sustain households and lift them out of poverty. 

The NLFS collects a host of indicators on job quality that will provide vital insights into monitoring progress towards generating the types of jobs Nigeria needs to reduce poverty. By fully harnessing its rich, high-quality data – and not just looking at unemployment – the NLFS has the potential to provide vital policy guidance for many years to come.

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The upside of recessions

New research confirms it: The worse the economy gets, the longer we live. But why?

There's a reason governments spend so many taxpayer dollars digging their economies out of recessions. Families lose their homes. Children go malnourished. New grads spend years struggling to get their careers back on track, forgoing marriage and kids and homeownership. But a growing body of research suggests that recessions are good for at least one thing: longevity. Puzzlingly, it appears that economic downturns actually extend people's lives.

The latest evidence comes from " Lives vs. Livelihoods ," a new paper by four researchers led by the renowned health economist Amy Finkelstein. They found that during the Great Recession, from 2007 to 2009, age-adjusted mortality rates among Americans dropped 0.5% for every jump of 1 percentage point in an area's unemployment rate. The more joblessness, the longer people lived — especially adults over 64 and those without a college education.

"These mortality reductions appear immediately," the economists concluded, "and they persist for at least 10 years." The effects were so large that the recession effectively provided 4% of all 55-year-olds with an extra year of life. And in states that saw big jumps in unemployment, people were more likely to report being in excellent health. Recessions, it would seem, help us stay fitter, and live longer.

The question, of course, is why. The economists ruled out a lot of possible explanations. Laid-off workers weren't using their free time to exercise more, or cutting back on smoking or drinking because money was tight. Infectious diseases like influenza and pneumonia kept right on spreading, even though fewer people were going to work and dining out. Retirees didn't seem to be getting better care, even though rising unemployment rates made it easier for nursing homes to staff up. So what could the explanation be? How does higher unemployment lead to longer life?

The answer was pollution. Counties that experienced the biggest job losses in the Great Recession, the economists found, also saw the largest declines in air pollution, as measured by levels of the fine particulate matter PM2.5. It makes sense: During recessions, fewer people drive to work. Factories and offices slow down, and people cut back on their own energy use to save money. All that reduced activity leads to cleaner air. That would explain why workers without a college degree enjoyed the biggest drops in mortality: People with low-wage jobs tend to live in neighborhoods with more environmental toxins. It would also explain why the recession reduced mortality from heart disease, suicide, and car crashes — causes of death all linked to the physical and mental effects of PM2.5. Overall, the economists found, cleaner air was responsible for more than a third of the decline in mortality during the Great Recession.

An economy firing on all cylinders creates more jobs — but it also generates all sorts of unseen but harmful side effects.

The new paper, along with other research into recessions, provides an important reminder that economic growth isn't — and shouldn't be — the only measure of our collective well-being. If recessions save lives, that comes with a corollary: Boom times cost lives. An economy firing on all cylinders creates more jobs — but it also generates all sorts of unseen but harmful side effects. "Our findings suggest important trade-offs between economic activity and mortality," the authors conclude. That's economist-speak for two very bad choices: Would you prefer wealth that kills you, or poverty that keeps you alive?

It's that dilemma that has given rise to what's known as the degrowth movement — the idea that the gross domestic product doesn't provide us with an accurate read on human progress. Sure, economic growth provides jobs. But it doesn't tell us anything about the health of our children or the safety of our neighborhoods or the sustainability of our planet. What's the point of having all this money, the degrowthers ask, if it's making us worse off?

I'm sympathetic to that line of reasoning — up to a point. But I don't think that actually shrinking the economy, as some degrowthers advocate, is a good idea. Lower growth inevitably leads to higher unemployment, and that's not a trade-off we should be willing to accept. I grew up in Japan, a country degrowthers often point to as a model for slower growth. It's true that Japan is politically stable, clean, and safe even though its economy has stalled for 30 years. But there's something about long-term economic stagnation that saps a country's hope. Nothing changes — in politics, in culture, in society — even when everyone knows it's bad. Without realizing it, I had settled into this national inertia, the belief that nothing could be done. It was only in 2012, when I moved to San Francisco, that I started to feel real agency over the direction of my life. Everyone around me believed they could change the world, and the sense of optimism was contagious.

The degrowth movement presents us with a false choice. The solution to bad growth isn't less growth. It's better growth. With stronger regulation and smarter innovation, I'm confident we can find ways to create jobs without destroying the environment and shortening our lives. If the new research tells us anything, it's that we still have a long way to go in striking a healthy balance between economic growth and social welfare. We shouldn't have to choose between working and living.

Aki Ito is a chief correspondent at Business Insider.

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BREAKING NEWS: Alexandria says plan to bring Capitals, Wizards to Northern Virginia is dead

Maryland unemployment, still among the nation’s lowest, ticks up for third straight month

Jeff Clabaugh | [email protected]

March 25, 2024, 4:40 AM

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After claiming the title of lowest state unemployment rate in the country last year, Maryland’s unemployment rate rose for the third consecutive month in February.

Virginia’s unemployment rate held steady last month.

The Labor Department’s Bureau of Labor Statistics reports Maryland’s seasonally-adjusted unemployment rate in February was 2.4%, up from 2.3% in January and 2.2% in December.

Virginia’s unemployment rate was 3.0%, unchanged from December and January. It was about the same as a year earlier.

North Dakota had the lowest state unemployment rate in February, at 2.0%, followed by South Dakota, at 2.1%. California now has the highest unemployment rate among states, at 5.3%, displacing Nevada, which now has the second-highest state unemployment rate, at 5.2% in February.

Nationally, the unemployment rate in February rose 0.3% to 3.9%.

Maryland had about 24,000 more jobs at the end of February. Virginia ended the month with a year-over-year payroll gain of 38,000 jobs.

The Bureau of Labor Statistics posts monthly unemployment and civilian payroll changes by state online .

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© 2024 WTOP. All Rights Reserved. This website is not intended for users located within the European Economic Area.

Jeff Clabaugh has spent 20 years covering the Washington region's economy and financial markets for WTOP as part of a partnership with the Washington Business Journal, and officially joined the WTOP newsroom staff in January 2016.

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ICAP-Trained Surveillance Team Identifies Human Rift Valley Fever Case in Marsabit, Kenya

Mar 26, 2024 | News , Stories from the Field

ICAP surveillance staff Sammie Munene and Mohamed Ali prepare samples from suspected cases in Marsabit to be transported to Kenya’s National Public Health Lab.

An ICAP-supported disease surveillance team in Kenya successfully identified and reported a new human case of Rift Valley fever (RVF) in northern Kenya, leading the country’s Ministry of Health to declare an outbreak on January 24, 2024. RVF is an acute hemorrhagic fever caused by a vector-borne virus carried by mosquitoes. It usually affects the region’s livestock, including cattle, camels, and goats, but can less commonly be transmitted to humans.

In his announcement about the outbreak, the Ministry of Health’s acting director general, Dr. Patrick Amoth, MBChB, MMed, linked it to the aftermath of the El Niño rains, which spurred an increase in mosquito populations and the overall transmission of vector-borne diseases.

“The importance of early detection, reporting, and response to disease outbreaks cannot be overstated,” said Doris Naitore, program director for ICAP in Kenya. “Emerging and endemic diseases of public health concern can potentially inflict significant harm on the population. These diseases can spread rapidly, cause high mortality, influence economic activities, and potentially overwhelm the health care system.”

With financial and technical support from the Centers for Disease Control and Prevention (CDC), ICAP has been collaborating with the Ministry of Health since 2021 to scale up integrated health facility-based surveillance – the routine monitoring of infectious diseases in patients – at hospitals and clinics across the country for 33 priority diseases that are viewed as public health concerns in Kenya, including Rift Valley fever. Surveillance is operational in 11 health facilities, with plans to expand to 20 more in the next two years.

Each participating health facility has an ICAP trained surveillance team consisting of a surveillance officer, a lab technician who draws the blood, and a data clerk. It was the surveillance team in Marsabit County who swiftly identified a new human case of Rift Valley fever in Turbi, North Horr Sub-County, after recognizing certain telltale symptoms in a patient.

“Since October 2021, we have vigilantly monitored cases of acute febrile illness,” explained Mohamed Ali, the surveillance officer for the Marsabit team. “We are happy that these efforts have borne fruits as we picked up the very first case of RVF…which subsequently led to the declaration of an outbreak.”

The surveillance team also played a crucial role by ensuring the prompt and safe transportation of blood samples from suspected cases to the National Public Health Laboratories in Nairobi for testing. This was particularly challenging given the remote location of Marsabit. Since the surveillance program’s implementation, the entire process of testing and identifying suspected infections has shrunk to two weeks when, in the past, it could take months.

A multidisciplinary team that included health officials from the Ministry of Health, the CDC, and ICAP were then deployed to investigate and respond to the outbreak.

“This collaborative program is driven by a commitment to safeguarding the local community’s wellbeing, enabling them to continue their livelihoods and protect their livestock,” ICAP’s Naitore said. “This initiative highlights the significance of vigilant health surveillance systems and demonstrates the powerful impact of partnership and collaboration in advancing public health objectives.”

A major global health organization that has been improving public health in countries around the world for two decades, ICAP works to transform the health of populations through innovation, science, and global collaboration. Based at Columbia Mailman School of Public Health, ICAP has projects in more than 40 countries, working side-by-side with ministries of health and local governmental, non-governmental, academic, and community partners to confront some of the world’s greatest health challenges. Through evidence-informed programs, meaningful research, tailored technical assistance, effective training and education programs, and rigorous surveillance to measure and evaluate the impact of public health interventions, ICAP aims to realize a global vision of healthy people, empowered communities, and thriving societies. Online at icap.columbia.edu

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ICAP is at the forefront of research generating new knowledge to improve access to and quality of health services, strengthen delivery mechanisms, and evaluate public health interventions. Leveraging years of experience and a committed cadre of accomplished experts, ICAP designs, implements, monitors, and evaluates a range of innovative implementation science, epidemiological, and clinical research studies. To ensure sustainability of this pragmatic research, ICAP provides training and mentorship in the countries where it works.

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With a Clinic on Wheels, ICAP Moves Research on Opioids and HIV Into the Passing Lane

In summer 2021, a state-of-the-art mobile clinic began making rounds in the streets of Harlem and the Bronx, drawing attention with its bright graphics. But beneath the colorful exterior is a serious proposition – to address the intertwined public health crises of opioid addiction, HIV, and hepatitis C among people who inject drugs.

Drug overdose is the leading cause of accidental death in the United States, with nearly 108,000 fatalities in 2021, the highest number of overdose deaths recorded in any 12-month period. Factors such as lack of access to health care, poverty, mental health disorders, use of multiple illicit substances, stigma and discrimination combine to increase the risk of HIV transmission and acquisition and other health issues among people who inject drugs.

The mobile clinic is at the center of ICAP’s participation in the nationwide INTEGRA study (HPTN 094), which aims to determine whether using mobile health units to deliver integrated health services for people with opioid use disorder can improve addiction, HIV, hepatitis C and substance use outcomes compared to standard of care. At locations frequented by people who inject drugs, ICAP study team members engaged with individuals, provided them with information regarding the study, enrolled participants and followed up with them throughout their study participation.

Participants in the study are randomized to receive integrated care on the “van” – as the study team calls it – or to receive the services of a health care navigator who will assist the participant in finding care in the community.

“The integrated care model means they will be able to receive their buprenorphine [a medication to treat opioid use disorder] prescription from the van,” said Rashaunna Redd, NP, site clinician for ICAP’s Bronx Prevention Center, which conducts the study. “And they will also be tested for HIV, STIs, and hepatitis, and screened for routine primary care problems such as diabetes and blood pressure issues.”

After six months, all participants transition to care in the community. Follow-up after the study extends to 12 months.

“Our goal is to make it as close to one stop as a possible. Although we recognize that some people will have serious medical conditions that require them to see specialists – and we will help them with that,” said Ellen Morrison, MD, site lead at ICAP’s Bronx Prevention Center.

Since the study began, initial findings revealed a high prevalence of mental health disorders such as anxiety, depression, and post-traumatic stress disorder among participants.

“This finding is particularly important because recreational drug use may be used as a form of self-medication,” said Alan Padilla, BA, community educator at ICAP’s Bronx Prevention Center. “Our team is actively promoting the need to address these underlying factors to fully provide addiction services.”

As the van proclaims in bright lettering, ICAP is driving health forward . Mobile health units, along with this study, are providing the engine necessary to reach that mission.

Funder: U.S. National Institute of Allergy and Infectious Diseases (NIAID) with funding from the U.S. National Institute on Drug Abuse (NIDA)

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Charting LGBTQ+ Health Challenges in New York City During COVID-19

As COVID-19 swept the globe, its ruthless trajectory exacerbated the challenges and inequities already faced by the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community, including employment and housing discrimination, inequitable health care, and more. To gain insight into the burden and impact of COVID-19 on this community, and assess vaccine uptake, ICAP conducted a study that reached more than 1,000 LGBTQ+ New Yorkers aged 18 to 68 years.

While LGBTQ+ individuals in NYC reported a similar burden of COVID-19 and vaccine uptake compared to the general population of the city, the study revealed this community is more likely to experience increased financial and emotional challenges due to the pandemic, particularly among the most stigmatized, such as gender minorities and among those with multiple minority identities. For example, 81 percent of LGBTQ+ individuals reported experiencing financial hardship as a result of the pandemic. This important evidence base will inform strategies to reach unvaccinated individuals and assist policymakers in developing further programs to support those most negatively impacted by the pandemic.

Funder: Rockefeller Foundation

Project: Experiences of LGBTQ+ Populations in New York City During the COVID-19 Pandemic (The LEXICON Study)

COVID-19 and Older Adults in New York City: A Landmark Study

In New York City, older adults had seven times the mortality rate from COVID-19 compared to all other ages, but there was little known about the mental health and social ramifications of the pandemic on this population – especially those who were still living at home and not in nursing homes.

To gain a better understanding of the effects of the pandemic on this vulnerable group, ICAP launched the SARS-CoV-2 Impact on Lives and Views of Elderly Residents (SILVER) study, aimed at understanding the physical, emotional, and economic effects of the COVID-19 pandemic on older adults living at home. A total of 676 participants 70 years and older were enrolled – overall, 18 percent of older adults screened for depression and 17 percent for anxiety, with a greater percent of Latinx older adults reporting loneliness than other races and ethnicities. Almost one-third of older New Yorkers reported financial challenges and almost one in ten reported not having enough to eat.

With new funding, ICAP launched a second SILVER study seeking to learn more about the impact of the pandemic on participants’ ongoing health and wellbeing. The second round of data collection expanded topic areas, pursuing further details about participants’ access to resources such as telehealth, housing, internet, social support, and use of city services. Attitudes toward the COVID-19 vaccine, booster doses, and the influenza vaccine were also evaluated. In addition to following up with the first SILVER study participants, the second study included new participants, specifically Asian New Yorkers, to better represent the diversity of New York City. The ultimate goal of the study was to provide policymakers in New York City and other communities with more accurate information on how to best serve and assist older adults during times of crisis.

Funder: New York Community Trust

Project: SARS-CoV-2 Impact on Lives and Views of Elderly Residents (SILVER) Study