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Modelling dengue and chikungunya transmission patterns for improved public health decision-making in the Horn of Africa (AeDST-HORN)

In plain English

AI plain-English summary

Dengue and chikungunya are spreading faster across the Horn of Africa, and this project will build mathematical models to predict where and when outbreaks will hit Ethiopia, Kenya, and Somalia. Climate change, shifting land use, and population growth are driving a surge in mosquito-borne viruses in Africa, but public health officials in the region lack reliable tools to anticipate outbreaks. Current surveillance is reactive—authorities only respond after cases appear. This project fills that gap by turning data on mosquito populations, species distribution, and human infection patterns into forecasting models that can predict transmission weeks or months ahead. If successful, the models will power online decision-support tools that guide risk-based surveillance and control. Health ministries could target mosquito control and public warnings to specific districts before an outbreak peaks, rather than scrambling after the fact. The project also builds a lasting network of institutions—from Ethiopia’s Public Health Institute to Kenya’s disease surveillance unit—that will champion model-driven decision-making long after the grant ends. The outcome is not a vaccine or a drug, but a practical system for making scarce public health resources count where they are needed most.

View original technical description
Africa is facing an increasing burden of mosquito-borne arboviral diseases primarily due to climate, land use and demographic changes. To support evidence-based decision-making in the management of these diseases, the project aims to develop mathematical models for forecasting dengue and chikungunya occurrence patterns in Ethiopia, Kenya and Somalia. Models developed will be used to drive online decision support tools to guide risk- based surveillance and control. The project also aims to build a network of institutions including the Ethiopia Public Health Institute, Kenya’s Department of Disease Surveillance and Epidemic Response, the Federal Ministry of Health in Somalia, Jomo Kenyatta University of Agriculture and Technology, the Kenya Medical Research Institute, Ohio State University, Global One Health Initiative and the International Livestock Research Institute that would champion the use of mathematical models for dengue and chikungunya control in the region. The study will use primary and secondary data on mosquito population and species distribution patterns as well as the infection patterns of the two diseases in humans. The outcome will be an improved capacity for dengue and chikungunya control within and between the target countries in the Horn of Africa.

View the original record at the funder ↗

Researchers

Ahmed Hassan-Kadle (EPMC Awardee)Bernard Bett (EPMC Awardee)Rebecca Garabed (EPMC Awardee)Rosemary Sang (EPMC Awardee)Zelalem Mekuria (EPMC Awardee)

Related Research

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Using Mathematical Models to Explore the Co-infection Dynamics Between Dengue, Chikungunya, Zika and Malaria
Mathematical Modelling for Infectious Disease Dynamics and Control in East Africa (MMIDD-EA)
Optimising strategic combinations of malaria interventions in western Kenya through a mechanistic model

Original classification

Strengthening health and disease modelling for public health decision making

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