Zoonotic diseases have varying public health burden and socio-economic impact across time and geographical settings making their prioritization for prevention and control important at the national level. We conducted systematic prioritization of zoonotic diseases and developed a ranked list of these diseases that would guide allocation of resources to enhance their surveillance, prevention, and control. A group of 36 medical, veterinary, and wildlife experts in zoonoses from government, research institutions and universities in Kenya prioritized 36 diseases using a semi-quantitative One Health Zoonotic Disease Prioritization tool developed by Centers for Disease Control and Prevention with slight adaptations. The tool comprises five steps: listing of zoonotic diseases to be prioritized, development of ranking criteria, weighting criteria by pairwise comparison through analytical hierarchical process, scoring each zoonotic disease based on the criteria, and aggregation of scores. In order of importance, the participants identified severity of illness in humans, epidemic/pandemic potential in humans, socio-economic burden, prevalence/incidence and availability of interventions (weighted scores assigned to each criteria were 0.23, 0.22, 0.21, 0.17 and 0.17 respectively), as the criteria to define the relative importance of the diseases. The top five priority diseases in descending order of ranking were anthrax, trypanosomiasis, rabies, brucellosis and Rift Valley fever. Although less prominently mentioned, neglected zoonotic diseases ranked highly compared to those with epidemic potential suggesting these endemic diseases cause substantial public health burden. The list of priority zoonotic disease is crucial for the targeted allocation of resources and informing disease prevention and control programs for zoonoses in Kenya.

Three months since the detection of the first COVID-19 case in Africa, almost all countries of the continent continued to report lower morbidity and mortality than the global trend, including Europe and North America. We reviewed the merits of various hypotheses advanced to explain this phenomenon, including low seeding rate, effective mitigation measures, population that is more youthful, favorable weather, and possible prior exposure to a cross-reactive virus. Having a youthful population and favorable weather appears compelling, particularly their combined effect; however, progression of the pandemic in the region and globally may dispel these in the coming months.

More than 75% of emerging infectious diseases are zoonotic in origin and a transdisciplinary, multi-sectoral One Health approach is a key strategy for their effective prevention and control. In 2004, US Centers for Disease Control and Prevention office in Kenya (CDC Kenya) established the Global Disease Detection Division of which one core component was to support, with other partners, the One Health approach to public health science. After catalytic events such as the global expansion of highly pathogenic H5N1 and the 2006 East African multi-country outbreaks of Rift Valley Fever, CDC Kenya supported key Kenya government institutions including the Ministry of Health and the Ministry of Agriculture, Livestock, and Fisheries to establish a framework for multi-sectoral collaboration at national and county level and a coordination office referred to as the Zoonotic Disease Unit (ZDU). The ZDU has provided Kenya with an institutional framework to highlight the public health importance of endemic and epidemic zoonoses including RVF, rabies, brucellosis, Middle East Respiratory Syndrome Coronavirus, anthrax and other emerging issues such as anti-microbial resistance through capacity building programs, surveillance, workforce development, research, coordinated investigation and outbreak response. This has led to improved outbreak response, and generated data (including discovery of new pathogens) that has informed disease control programs to reduce burden of and enhance preparedness for endemic and epidemic zoonotic diseases, thereby enhancing global health security. Since 2014, the Global Health Security Agenda implemented through CDC Kenya and other partners in the country has provided additional impetus to maintain this effort and Kenya’s achievement now serves as a model for other countries in the region. Significant gaps remain in implementation of the One Health approach at subnational administrative levels; there are sustainability concerns, competing priorities and funding deficiencies.

Brucellosis is a common bacterial zoonotic infection but data on the prevalence among humans and animals is limited in Kenya. A cross-sectional survey was conducted in three counties practicing different livestock production systems to simultaneously assess the seroprevalence of, and risk factors for brucellosis among humans and their livestock (cattle, sheep, camels, and goats). A two-stage cluster sampling method with random selection of sublocations and households was conducted. Blood samples were collected from humans and animals and tested for Brucella immunoglobulin G (IgG) antibodies. Human and animal individual seroprevalence was 16% and 8%, respectively. Household and herd seroprevalence ranged from 5% to 73% and 6% to 68%, respectively. There was a 6-fold odds of human seropositivity in households with a seropositive animal compared with those without. Risk factors for human seropositivity included regular ingestion of raw milk (adjusted odds ratio [aOR] = 3.5, 95% confidence interval [CI] = 2.8–4.4), exposure to goats (herding, milking, and feeding) (aOR = 3.1, 95% CI = 2.5–3.8), and handling of animal hides (aOR = 1.8, 95% CI = 1.5–2.2). Attaining at least high school education and above was a protective factor for human seropositivity (aOR = 0.3, 95% CI = 0.3–0.4). This linked study provides evidence of a strong association between human and animal seropositivity at the household level.

Background: Road traffic injuries (RTIs) contribute to a significant proportion of the burden of disease in Kenya. They also have a significant impact on the social and economic well-being of individuals, their families, and society. However, though estimates quantifying the burden of RTIs in Kenya do exist, most of these studies date back to the early 2000s—more than one decade ago. Objective: This article aims to present the current status of road safety in Kenya. Using data from the police and vital registration systems in Kenya, we present the current epidemiology of RTIs in the nation. We also sought to assess the status of 3 well-known risk factors for RTIs—speeding and the use of helmets and reflective clothing. Methods: Data for this study were collected in 2 steps. The first step involved the collection of secondary data from the Kenya traffic police as well as the National Vital Registration System to assess the current trends of RTIs in Kenya. Following this, observational studies were conducted in the Thika and Naivasha districts in Kenya to assess the current status of speeding among all vehicles and the use of helmets and reflective clothing among motorcyclists. Results: The overall RTI rate in Kenya was 59.96 per 100,000 population in 2009, with vehicle passengers being the most affected. Notably, injuries to motorcyclists increased at an annual rate of approximately 29 percent (95% confidence interval [CI]: 27–32; P < .001). The mean age of death due to road traffic crashes was 35 years. Fatalities due to RTIs increased at an annual rate of 7 percent (95% CI: 6–8; P < .001) for the period 2004 to 2009. Observational studies revealed that 69.45 percent of vehicles in Thika and 34.32 percent of vehicles in Naivasha were speeding. Helmets were used by less than one third of motorcycle drivers in both study districts, with prevalence rates ranging between 3 and 4 percent among passengers. Conclusions: This study highlights the significant burden of RTIs in Kenya. A renewed focus on addressing this burden is necessary. Focusing on increasing helmet and reflective clothing use and enforcement of speed limits has the potential to prevent a large number of road traffic crashes, injuries, and fatalities. However, it is difficult to demonstrate the magnitude of the injury problem to policymakers with minimal or inaccurate data, and this study illustrates the need for national continuous, systematic, and sustainable data collection efforts, echoing similar calls for action throughout the injury literature.

The lower than expected COVID-19 morbidity and mortality in Africa has been attributed to multiple factors, including weak surveillance. This study estimated the burden of SARS-CoV-2 infections eight months into the epidemic in Nairobi, Kenya. A population-based, cross-sectional survey was conducted using multi-stage random sampling to select households within Nairobi in November 2020. Sera from consenting household members were tested for antibodies to SARS-CoV-2. Seroprevalence was estimated after adjusting for population structure and test performance. Infection fatality ratios (IFRs) were calculated by comparing study estimates with reported cases and deaths. Among 1,164 individuals, the adjusted seroprevalence was 34.7% (95% CI 31.8-37.6). Half of the enrolled households had at least one positive participant. Seropositivity increased in more densely populated areas (spearman's r=0.63; p=0.009). Individuals aged 20-59 years had at least two-fold higher seropositivity than those aged 0-9 years. The IFR was 40 per 100,000 infections, with individuals ≥60 years old having higher IFRs. Over one-third of Nairobi residents had been exposed to SARS-CoV-2 by November 2020, indicating extensive transmission. However, the IFR was >10-fold lower than that reported in Europe and the USA, supporting the perceived lower morbidity and mortality in sub-Saharan Africa.