Report on the evaluation of surveillance systems relevant to zoonotic diseases in Kenya, 2015: A basis for design of an integrated human–livestock surveillance system

The Zoonoses in Livestock in Kenya (ZooLinK) is a project that seeks to enable Kenya develop an effective surveillance programme for zoonotic diseases (infectious diseases transmissible between animals and human beings). The surveillance programme will be integrated across both human and animal health sectors. To achieve this goal the project will work in close collaboration with Kenyan government departments in responsible for animal and human health. As a prelude to the start of the project, an evaluation of the existing surveillance systems for human and animal health was carried out. The evaluation focused on the national surveillance system and the systems at the western part of Kenya (Busia county, Kakamega county and Bungoma county) where the initial programme will be developed. In conducting the evaluation the investigators used key informant interviews, focused group discussion participant questionnaires, audio recordings and observation for data collection. Data analysis for the qualitative data focused on generating themes or theory around the responses obtained in the key informants interviews and focused group discussions. Univariate analysis was performed by use of simple proportions in calculation for surveillance system attributes like sensitivity, completeness, PVP and Timeliness for the human health surveillance systems. The findings of the evaluation revealed that there was poor linkage between animal health surveillance and the human health surveillance systems. None of the systems had surveillance structures dedicated to zoonotic diseases. Most practitioners used clinical signs for diagnosis of diseases with little reference to acceptable case definitions. Laboratory diagnosis in animal health services focused more on suspected notifiable diseases as opposed to being a standard operating procedure for diagnosis. In Human health services the health care facilities that had laboratory within the facility conducted laboratory diagnosis for cases referred by the clinicians. However, some clinicians preferred using clinical signs for diagnosis to avoid the wait or turn-around time in the laboratory. For effective surveillance of zoonoses to be realized it would be advisable to establish surveillance structures specific to zoonoses and the necessary resources allocated to the surveillance activities. In addition, an integrated approach that incorporated both human and animal disease surveillance should be employed in the surveillance of zoonoses

Imported SARS-CoV-2 variants of concern drove spread of infections across Kenya during the second year of the pandemic

Using classical and genomic epidemiology, we tracked the COVID-19 pandemic in Kenya over 23 months to determine the impact of SARS-CoV-2 variants on its progression. SARS-CoV-2 surveillance and testing data were obtained from the Kenya Ministry of Health, collected daily from 306 health facilities. COVID-19-associated fatality data were also obtained from these health facilities and communities. Whole SARS-CoV-2 genome sequencing were carried out on 1241 specimens. Over the pandemic duration (March 2020–January 2022), Kenya experienced five waves characterized by attack rates (AR) of between 65.4 and 137.6 per 100,000 persons, and intra-wave case fatality ratios (CFR) averaging 3.5%, two-fold higher than the national average COVID-19 associated CFR. The first two waves that occurred before emergence of global variants of concerns (VoC) had lower AR (65.4 and 118.2 per 100,000). Waves 3, 4, and 5 that occurred during the second year were each dominated by multiple introductions each, of Alpha (74.9% genomes), Delta (98.7%), and Omicron (87.8%) VoCs, respectively. During this phase, government-imposed restrictions failed to alleviate pandemic progression, resulting in higher attack rates spread across the country. In conclusion, the emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country

Temporal and spatial distribution of anthrax outbreaks among Kenyan wildlife, 1999–2017

The burden of anthrax in wildlife is demonstrated through high numbers of sudden mortalities among herbivore species, including endangered animal species. East Africa is home of multiple species of faunal wildlife numbering in the millions but there are limited disease surveillance programmes, resulting in a paucity of information on the role of anthrax and other infectious diseases on declining wildlife populations in the region. We reviewed historical data on anthrax outbreaks from Kenya Wildlife Service (KWS) spanning from 1999 to 2017 in Kenya to determine the burden, characteristics and spatial distribution of anthrax outbreaks. A total of 51 anthrax outbreaks associated with 1014 animal deaths were reported across 20 of 60 wildlife conservation areas located in six of the seven agro-ecological zones. Overall, 67% of the outbreaks were reported during the dry seasons, affecting 24 different wildlife species. Over 90% (22 of 24) of the affected species were herbivore, including 12 grazers, five browsers and five mixed grazers and browsers. Buffaloes (23.5%), black rhinos (21.6%) and elephants (17.6%) were the most frequently affected species. Our findings demonstrate the extensive geographic distribution of wildlife anthrax in the country, making it one of the important infectious diseases that threaten wildlife conservation

Comparison of knowledge, attitude, and practices of animal and human brucellosis between nomadic pastoralists and non-pastoralists in Kenya

Background The seroprevalence of brucellosis among nomadic pastoralists and their livestock in arid lands is reported to be over10-fold higher than non-pastoralists farmers and their livestock in Kenya. Here, we compared the seroprevalence of nomadic pastoralists and mixed farming with their knowledge of the disease and high-risk practices associated with brucellosis infection. Methods Across-sectional study was conducted in two counties - Kiambu County where farmers primarily practice smallholder livestock production and crop farming, and Marsabit County where farmers practice nomadic pastoral livestock production. Stratified random sampling was applied, in which sublocations were initially selected based on predominant livestock production system, before selecting households using randomly generated geographical coordinates. In each household, up to three persons aged 5 years and above were randomly selected, consented, and tested for Brucella spp IgG antibodies. A structured questionnaire was administered to the household head and selected individuals on disease knowledge and risky practices among the pastoralists and mixed farmers compared. Multivariable mixed effects logistic regression model was used to assess independent practices associated with human Brucella spp. IgG seropositivity. Results While the majority (74%) of pastoralist households had little to no formal education when compared to mixed (8%), over 70% of all households (pastoralists and mixed farmers) had heard of brucellosis and mentioned its clinical presentation in humans. However, fewer than 30% of all participants (pastoralists and mixed farmers) knew how brucellosis is transmitted between animals and humans or how its transmission can be prevented. Despite their comparable knowledge, significantly more seropositive pastoralists compared to mixed farmers engaged in risky practices including consuming unboiled milk (79.5% vs 1.7%, p < 0.001) and raw blood (28.3% vs 0.4%, p < 0.001), assisting in animal birth (43.0% vs 9.3%, p < 0.001), and handling raw hides (30.6% vs 5.5%, p < 0.001)., Conclusion Nomadic pastoralists are more likely to engage in risky practices that promote Brucella Infection, probably because of their occupation and culture, despite having significant knowledge of the disease

Anthrax hotspot mapping in Kenya support establishing a sustainable two-phase elimination program targeting less than 6% of the country landmass

Using data collected from previous (n = 86) and prospective (n = 132) anthrax outbreaks, we enhanced prior ecological niche models (ENM) and added kernel density estimation (KDE) approaches to identify anthrax hotspots in Kenya. Local indicators of spatial autocorrelation (LISA) identified clusters of administrative wards with a relatively high or low anthrax reporting rate to determine areas of greatest outbreak intensity. Subsequently, we modeled the impact of vaccinating livestock in the identified hotspots as a national control measure. Anthrax suitable areas included high agriculture zones concentrated in the western, southwestern and central highland regions, consisting of 1043 of 1450 administrative wards, covering 18.5% country landmass, and hosting 30% of the approximately 13 million cattle population in the country. Of these, 79 wards covering 5.5% landmass and hosting 9% of the cattle population fell in identified anthrax hotspots. The rest of the 407 administrative wards covering 81.5% of the country landmass, were classified as low anthrax risk areas and consisted of the expansive low agricultural arid and semi-arid regions of the country that hosted 70% of the cattle population, reared under the nomadic pastoralism. Modelling targeted annual vaccination of 90% cattle population in hotspot administrative wards reduced > 23,000 human exposures. These findings support an economically viable first phase of anthrax control program in low-income countries where the disease is endemic, that is focused on enhanced animal and human surveillance in burden hotspots, followed by rapid response to outbreaks anchored on public education, detection and treatment of infected humans, and ring vaccination of livestock. Subsequently, the global anthrax elimination program focused on sustained vaccination and surveillance in livestock in the remaining few hotspots for a prolonged period (> 10 years) may be implemented

Spatial clustering of livestock anthrax events associated with agro-ecological zones in Kenya, 1957-2017

Background Developing disease risk maps for priority endemic and episodic diseases is becoming increasingly important for more effective disease management, particularly in resource limited countries. For endemic and easily diagnosed diseases such as anthrax, using historical data to identify hotspots and start to define ecological risk factors of its occurrence is a plausible approach. Using 666 livestock anthrax events reported in Kenya over 60 years (1957–2017), we determined the temporal and spatial patterns of the disease as a step towards identifying and characterizing anthrax hotspots in the region. Methods Data were initially aggregated by administrative unit and later analyzed by agro-ecological zones (AEZ) to reveal anthrax spatio-temporal trends and patterns. Variations in the occurrence of anthrax events were estimated by fitting Poisson generalized linear mixed-effects models to the data with AEZs and calendar months as fixed effects and sub-counties as random effects. Results The country reported approximately 10 anthrax events annually, with the number increasing to as many as 50 annually by the year 2005. Spatial classification of the events in eight counties that reported the highest numbers revealed spatial clustering in certain administrative sub-counties, with 12% of the sub-counties responsible for over 30% of anthrax events, whereas 36% did not report any anthrax disease over the 60-year period. When segregated by AEZs, there was significantly greater risk of anthrax disease occurring in agro-alpine, high, and medium potential AEZs when compared to the agriculturally low potential arid and semi-arid AEZs of the country (p 10 times more likely to be infected by B. anthracis than sheep, goats, or camels. There was lower risk of anthrax events in August (P = 0.034) and December (P = 0.061), months that follow long and short rain periods, respectively. Conclusion Taken together, these findings suggest existence of certain geographic, ecological, and demographic risk factors that promote B. anthracis persistence and trasmission in the disease hotspots