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 < 0.05). Interestingly, cattle were > 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.

Co-creation and priority setting for applied and implementation research in One Health: Improving capacities in public and animal health systems in Kenya.

Background: The Kenyan government has successfully been implementing sector specific and multisectoral projects aligned to the Global Health Security Agenda (GHSA). For operational readiness and to enhance the effective planning and implementation of Global Health Security Programs (GHSP) at national and subnational level, there is an urgent need for stakeholders' engagement process to seek input in identifying challenges, prioritise activities for field implementation, and identify applied research and development questions, that should be addressed in the next five years. Methods: The modified Child Health and Nutrition Research Initiative (CHNRI) method was used to identify global health security related priorities for multisectoral implementation in Kenya. Subject matter experts from human, animal and environmental health sectors at national and subnational level contributed to predefined research questions from a number of sources and activities for consideration for implementation using a One Health approach. Sixty-two experts scored the 193 questions based on five pre-defined criteria: 1) feasibility and answerability; 2) potential for burden reduction; 3) potential for a paradigm shift; 4) potential for translation and implementation; and 5) impact on equity. Data resulting from this process was then analysed in a Microsoft Excel spreadsheet to determine the research priorities and experts' agreements. Results: Among the priority activities identified for implementation research were; strengthening One Health governance and legal frameworks; integration of ecosystem health into One Health programming; strengthening disease reporting, integrated data collection, information sharing and joint outbreak response; socio-anthropological and gender-based approaches in improving risk and behavioural change communication and community engagement; and one health workforce development. In addition, the potentials to invest in collaborative predictive risk modelling to enhance epidemic intelligence systems, while strengthening the One Health approach in the food safety incident and emergency response plans are feasible. Interpretation: Successful multisectoral implementation of global health security program in Kenya calls for a whole of society approach that will harness community and private sector knowledge to build preparedness and response capacities while targeting neglected and marginalised populations. This research provides a framework that is worth emulating for cost-effective planning and implementation of overarching One Health programs.