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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.

Coxiella burnetii , the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

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.

Unravelling the mechanisms of Rift Valley fever virus (RVFV) maintenance in endemic areas during interepidemic periods is critical for enhancing early detection and response. Unfortunately, data on key epidemiological parameters, such as incidence rates, which are crucial for risk assessments and designing targeted interventions, are almost nonexistent. We conducted a longitudinal study of 1,938 pastoral livestock and 814 livestock keepers in an endemic region of northern Kenya from March 2022 to May 2023 to estimate the incidence rate of RVFV exposure and determine risk factors for infection. We assessed exposure to RVFV in humans and livestock using an anti-RVF immunoglobulin enzyme-linked immunosorbent assay. RVFV incidence was calculated in livestock and humans as the number of new seroconversions over the total animal and person time at risk, respectively. An interval-censored regression model was employed to compute the baseline hazard and identify risk factors. We observed 113 new livestock infections over 805 animal-years at risk, translating to an annual livestock incidence rate of 0.14 per animal-year (95% CI: 0.12–0.17). Multivariable analysis found species, acaricide use, and period of sampling were significant factors that influence RVFV incidence in livestock. In humans, 15 RVFV seroconversions were observed over 629 person-years at risk, yielding an incidence rate of 24 per 1000 person-years (95% CI: 13–39). Age and sex were not significant predictors of RVFV human exposure. Seroconversion in livestock and humans suggests that low-level transmission between vertebrate hosts and vectors could be the primary mechanism for RVF viral persistence in endemic areas. Our findings highlight the need for routine serosurveillance and continuous public health education on RVF infection and prevention during interepidemic periods.

Nearly a century after the first reports of Rift Valley fever (RVF) were documented in Kenya, questions on the transmission dynamics of the disease remain. Specifically, data on viral maintenance in the quiescent years between epidemics is limited. We implemented a cross-sectional study in northern Kenya to determine the seroprevalence, risk factors, and ecological predictors of RVF in humans and livestock during an interepidemic period. Six hundred seventy-six human and 1,864 livestock samples were screened for anti-RVF Immunoglobulin G (IgG). Out of the 1,864 livestock samples tested for IgG, a subset of 1,103 samples was randomly selected for additional testing to detect the presence of anti-RVFV Immunoglobulin M (IgM). The anti-RVF virus (RVFV) IgG seropositivity in livestock and humans was 21.7% and 28.4%, respectively. RVFV IgM was detected in 0.4% of the livestock samples. Participation in the slaughter of livestock and age were positively associated with RVFV exposure in humans, while age was a significant factor in livestock. We detected significant interaction between rainfall and elevation's influence on livestock seropositivity, while in humans, elevation was negatively associated with RVF virus exposure. The linear increase of human and livestock exposure with age suggests an endemic transmission cycle, further corroborated by the detection of IgM antibodies in livestock.

Tracking livestock abortion patterns over time and across factors such as species and agroecological zones (AEZs) could inform policies to mitigate disease emergence, zoonoses risk, and reproductive losses. We conducted a year-long population-based active surveillance of livestock abortion between 2019 and 2020, in administrative areas covering 52% of Kenya’s landmass and home to 50% of Kenya’s livestock. Surveillance sites were randomly selected to represent all AEZs in the country. Local animal health practitioners electronically transmitted weekly abortion reports from each ward, the smallest administrative unit, to a central server, using a simple short messaging service (SMS). Data were analyzed descriptively by administrative unit, species, and AEZ to reveal spatiotemporal patterns and relationships with rainfall and temperature. Of 23,766 abortions reported in all livestock species, sheep and goats contributed 77%, with goats alone contributing 53%. Seventy-seven per cent (n = 18,280) of these abortions occurred in arid and semi-arid lands (ASALs) that primarily practice pastoralism production systems. While spatiotemporal clustering of cases was observed in May-July 2019 in the ASALs, there was a substantial seasonal fluctuation across AEZs. Kenya experiences high livestock abortion rates, most of which go unreported. We recommend further research to document the national true burden of abortions. In ASALs, studies linking pathogen, climate, and environmental surveillance are needed to assign livestock abortions to infectious or non-infectious aetiologies and conducting human acute febrile illnesses surveillance to detect any links with the abortions.

Coxiella burnetii, the causative agent of Q fever, is a globally distributed pathogen with significant zoonotic and economic impacts, particularly in regions where humans and livestock interact closely. Although endemic in many countries, including Kenya, comprehensive epidemiological data on the pathogen are limited. To address this gap, we conducted a linked human and livestock populations study in Garbatulla, Isiolo County to assess seroprevalence and identify potential predictors of C. burnetii exposure. We used a cross-sectional design with multistage sampling. Blood and serum samples were collected from 2,157 livestock and 683 humans that were recruited from 242 households. Additional data on herd/household and subject characteristics were collected using a structured questionnaire. Indirect enzyme-linked immunosorbent assay (ELISA) was used to test the serum samples for antibodies against C. burnetii. Univariable and multivariable analyses identified potential predictors of exposure in both livestock and humans. The overall seroprevalence of C. burnetii was 47.9% (95% CI: 45.7%-50.1%) in livestock and 44.7% (95% CI: 40.9%-48.5%) in humans. In livestock, significant variation in seroprevalence was found by species (p < 0.001). Goats were found to have significantly higher odds of being exposed to C. burnetii compared to cattle, sheep and camels. Both weaners and young animals had significantly lower odds of exposure compared to adults. In humans, the odds of C. burnetii exposure were lower among females compared to males. Herds seropositivity was also an important predictor of humans exposure to C. burnetii. This study provides evidence of high seroprevalence of C. burnetii in both livestock and humans, highlighting the need for active surveillance programs targeting both populations. These programs should focus on identifying active shedding and implementing targeted control measures to mitigate the public health risks associated with C. burnetii.

To improve early detection of emerging infectious diseases in sub-Saharan Africa (SSA), many of them zoonotic, numerous electronic animal disease-reporting systems have been piloted but not implemented because of cost, lack of user friendliness, and data insecurity. In Kenya, we developed and rolled out an open-source mobile phone-based domestic and wild animal disease reporting system and collected data over two years to investigate its robustness and ability to track disease trends. The Kenya Animal Biosurveillance System (KABS) application was built on the Java® platform, freely downloadable for android compatible mobile phones, and supported by web-based account management, form editing and data monitoring. The application was integrated into the surveillance systems of Kenya's domestic and wild animal sectors by adopting their existing data collection tools, and targeting disease syndromes prioritized by national, regional and international animal and human health agencies. Smartphone-owning government and private domestic and wild animal health officers were recruited and trained on the application, and reports received and analyzed by Kenya Directorate of Veterinary Services. The KABS application performed automatic basic analyses (frequencies, spatial distribution), which were immediately relayed to reporting officers as feedback. Of 697 trained domestic animal officers, 662 (95%) downloaded the application, and >72% of them started reporting using the application within three months. Introduction of the application resulted in 2- to 14-fold increase in number of disease reports when compared to the previous year (relative risk = 14, CI 13.8-14.2, p<0.001), and reports were more widely distributed. Among domestic animals, food animals (cattle, sheep, goats, camels, and chicken) accounted for >90% of the reports, with respiratory, gastrointestinal and skin diseases constituting >85% of the reports. Herbivore wildlife (zebra, buffalo, elephant, giraffe, antelopes) accounted for >60% of the wildlife disease reports, followed by carnivores (lions, cheetah, hyenas, jackals, and wild dogs). Deaths, traumatic injuries, and skin diseases were most reported in wildlife. This open-source system was user friendly and secure, ideal for rolling out in other countries in SSA to improve disease reporting and enhance preparedness for epidemics of zoonotic diseases.

Background Brucellosis is a neglected zoonotic disease that affects both animals and humans, causing debilitating illness in humans and socio-economic losses in livestock-keeping households globally. The disease is endemic in many developing countries, including Kenya, but measures to prevent and control the disease are often inadequate among high-risk populations. This study aimed to investigate the human and livestock seroprevalence of brucellosis and associated risk factors of Brucella spp. in a pastoralist region of northern Kenya. Methods A cross-sectional survey was conducted using a two-stage cluster sampling method to select households, livestock, and humans for sampling. Blood samples were collected from 683 humans and 2157 animals, and Brucella immunoglobulin G (IgG) antibodies were detected using enzyme-linked immunosorbent assays. A structured questionnaire was used to collect data on potential risk factors associated with human and animal exposures. Risk factors associated with Brucella spp. exposures in humans and livestock were identified using Multivariate logistic regression. Results The results indicated an overall livestock Brucella spp. seroprevalence of 10.4% (95% Confidence Interval (CI): 9.2-11.7). Camels had the highest exposure rates at 19.6% (95% CI: 12.4-27.3), followed by goats at 13.2% (95% CI: 9.3-17.1), cattle at 13.1% (95% CI: 11.1-15.3) and sheep at 5.4% (95% CI: 4.0-6.9). The herd-level seroprevalence was 51.7% (95% CI: 47.9-55.7). Adult animals (Adjusted Odds Ratio (aOR) = 2.3, CI: 1.3-4.0), female animals (aOR = 1.7, CI: 1.1-2.6), and large herd sizes (aOR = 2.3, CI: 1.3-4.0) were significantly associated with anti-brucella antibody detection while sheep had significantly lower odds of Brucella spp. exposure compared to cattle (aOR = 1.3, CI: 0.8-2.1) and camels (aOR = 2.4, CI: 1.2-4.8). Human individual and household seroprevalences were 54.0% (95% CI: 50.2-58.0) and 86.4% (95% CI: 84.0-89.0), respectively. Significant risk factors associated with human seropositivity included being male (aOR = 2.1, CI:1.3-3.2), residing in Sericho ward (aOR = 1.6, CI:1.1-2.5) and having no formal education (aOR = 3.0, CI:1.5-5.9). There was a strong correlation between human seropositivity and herd exposure (aOR = 1.6, CI:1.2-2.3). Conclusions The study provides evidence of high human and livestock exposures to Brucella spp. and identifies important risk factors associated with disease spread. These findings emphasize the need for targeted prevention and control measures to curb the spread of brucellosis and implement a One Health surveillance to ensure early detection of the disease in Isiolo County, Northern Kenya.

Although seroprevalence of Middle East respiratory coronavirus syndrome is high among camels in Africa, researchers have not detected zoonotic transmission in Kenya. We followed a cohort of 262 camel handlers in Kenya during April 2018-March 2020. We report PCR-confirmed Middle East respiratory coronavirus syndrome in 3 asymptomatic handlers.