Predicting the next epidemic: DHIS2-based risk modeling
InfoStart date: 1 March, 2020 End date: 28 February, 2025 Project type: Research collaboration projects in Danida priority countries (Window 1) Project code: 19-02-KU Countries: Tanzania Thematic areas: Climate change, Health, Lead institution: University of Copenhagen (UCPH), Faculty of Health and Medical Sciences, Centre for Medical Parasitology, Denmark Partner institutions: National Institute for Medical Research (NIMR), Tanga Research Centre, Tanzania State University of Zanzibar (SUZA), Tanzania Ministry of Health Zanzibar (MOHZ), Tanzania University of Dar es Salaam (UDSM), Tanzania Danish Technical University (DTU), Aarhus, Denmark University of Gothenburg, Sweden Joint Malaria Programme (JMP) Kilimanjaro Christian Medical College (KCMC), Tanzania Project coordinator: Michael Alifrangis Total grant: 11,995,367 DKK
Unexpected onset of large-scale epidemics caused by climate-sensitive vector-borne diseases (VBDs) present a growing risk to human health and societal stability throughout the world. The situation is especially critical in LMICs as health systems struggle to absorb the full scale of mass hospitalizations due to acute VBD epidemics, while public and private sectors may suffer substantial productivity and commercial losses.
Tanzania is experiencing significant changes in VBD transmission patterns in particular with respect to mosquito-borne diseases, such as malaria and dengue. Notably, dengue epidemics recently became a recurrent phenomenon, while observed changes in malaria epidemiology suggest a shift from stable, holoendemic-, to unstable, hypoendemic transmission marked by increasing risk of malaria epidemics. The complex processes that drive VBD epidemics are not fully understood-yet climatic, environmental and socio-economic factors are known modulators.
This project addresses the need for improved prediction and prevention of epidemic risks by assessing novel modelling approaches and opportunities for translating complex model outcomes into easily disseminated risk assessments for targeted and timely interventions.
Specifically, we aim to explore key predictors and to combine modelling approaches, coupling
vector ecological niche models with mathematical micro-epidemiological models, in order to obtain timely, high-resolution risk projections of VBD epidemics. To ensure that these projections are readily available, we will develop an adjunct application on top of the existing DHIS2 platform, through which risk assessments are presented to end-users in the form of user-friendly risk maps and epidemic alerts. The project will use dengue and malaria as tracers for epidemic VBDs in Tanzania - and Unguja and Tanga Regions as specific study areas as they cover diverse climatic, environmental and socio-economic settings for comprehensive model development.