Rift Valley Fever Early Warning Systems for Pandemic preparedness in Kenya

Dr.Nanyingi M O

Interdecadal and interannual climate variability has led to emergence and reemergence of zoonoses in Kenya. Pastoralists and small holder farmers are mostly affected due to their higher vulnerability and poor adaptive capacity; predisposed by lack of accurate predictive warning systems. The Global Information and Early Warning and Information System (GLEWS), FAO Emergency Prevention System (EMPRES), Famine Early Warning System (FEWSNET) and Malaria Early Warning System (MEWS) are existing but inadequate databases that rely on seasonal weather forecasts, governments’ meteorological data and geospatial mapping repositories to predict pandemics of climate sensitive diseases (CSD). In Kenya the Department of Veterinary Services (DVS) under the Epidemiology communications Office has established a community based early warning (CBEWS) contingency plan to monitor the convergence of risk factors that predispose to Rift Valley Fever (RVF) outbreaks and effectively communicate to stakeholders for early response in a 3-5 month lead period. This is supported by non-governmental partners’; it involves the vulnerable communities, educational and research institutions. Some of the impediments in tackling CSD are lack of understanding of the drivers of climate change by local experts, dysfunctional communication channels, financial constraints, Ethno-religious barriers, trans-boundary conflicts, poor government policies and lack of human capacity and equipment in designing predictive tools. The prioritized beneficiaries of climate risk detection and prediction information systems are the pastoral and vulnerable communities; however this may be utilized by research institutions, government and donors for planning. Sustainable planning and decision making tools to support the development of appropriate climate change adaptation and mitigation strategies have been achieved by conducting community sensitization, awareness raising in schools, continuous training of veterinary, medical and public health personnel. The Kenya Meteorological Department in conjunction with DVS are working on rejuvenating information and dissemination EWS that targets end users like vernacular radio stations to confer a sense of ownership in the final results. We are investigating the Spatio-temporal distribution and burden analysis of RVF in Garissa, Northern Kenya; using model-based approaches in prediction of future outbreaks in response to climate change. We envisage employing participatory approaches and hotspots risk mapping in estimating the economic impacts on livelihoods and develop RVF -EWS for public preparedness. A Kenyan Zoonotic disease department has been specifically established for technical capacity building to standardize the management of emerging zoonoses including CSD. Quasi real-time syndromic and sentinel e- surveillance using mobile phones involving communities is in experimental phase in RVF monitoring. Our dissemination of geographic, statistical and meteorological data for vulnerability and early warning platforms is hinged on collaboration of regional animal and human health institutions in managing of existing and emerging diseases of veterinary and public health significance. We take therefore cognizance of a community based approach in early and timely detection of RVF is vital to veterinary, health authorities and policy-makers in immediate decision making. It contributes to an integrated climate risk assessment of livestock vulnerability analysis using climate dependent RVF model to develop predictive risk maps that will be crucial in current and future control plans of other climate sensitive diseases and possibly provide Early Warning Systems (EWS). The output will contribute to institutional contingency frameworks dealing with concepts and indicators of warning systems which will facilitate the early identification of potential climate sensitive epidemics and decision support systems