Improving early warning and control of mosquito-borne disease outbreaks caused by extreme weather in Uganda

Extreme weather such as heavy rainfall causes flooding and landslides resulting in displacement of populations and humanitarian disasters. Flooding also creates favourable conditions for proliferation of mosquitoes that transmit diseases such as malaria, Rift Valley fever (RVF) and yellow fever (YF). Flooding and landslides have become frequent occurrences in Uganda. Malaria is among the major public health problems. RVF is a viral disease that affects both livestock and humans. Yellow fever is a deadly disease that has occurred in recent years as sporadic outbreaks. These outbreaks have proven difficult to anticipate and may occur unexpectedly. We aim to improve the health system in Uganda to develop a capacity to forecast impending disease outbreaks associated with extreme weather events. We will collect data on past outbreaks and extreme weather conditions and other factors and study whether and how they were associated. We will answer questions such as how long after flooding the outbreaks of malaria, RVF and YF occurred, and the geographical proximities of affected areas. We will then develop computer models that predict the chance of disease transmission by taking into account various factors such as immunity levels in the human or livestock populations, effects of weather conditions on abundance of mosquitoes and transmission of the diseases, livestock movement patterns, and environmental characteristics. We use these models to develop an outbreak risk mapping system. We will also include a method that compares the cost-effectiveness of various courses of action to make informed decisions to prevent or mitigate the outbreaks. The research will be implemented in three phases. In Phase 1, data on past outbreaks will be analysed to determine associations with extreme weather events and other factors. Past data on disease incidence, weather variables, and other risk indicators will be used to develop forecasting models. In Phase 2, we will develop an interactive risk mapping platform based on the forecasting models and data inputs for routine use. The mapping approach will be based on a dashboard portal developed within our research partnership. In Phase 3, We will develop a national outbreak preparedness and response plan based on existing plans in close collaboration with all relevant partners. The plan will be aligned with outputs of the online portal to provide specific guidance on interventions. We will facilitate adoption and use of the outputs by engaging communities and end-users from the start and effectively disseminating the findings. We will involve affected communities, local health services, and village health workers to identify important risk factors and gaps in outbreak preparedness. We will be working closely with governmental and other partners for adoption and routine use of the system and the associated plan for prevention of outbreaks and effective mitigation of their impacts.