Identification and mapping of hotspot areas, risk profiles and prediction of cholera outbreaks in the Oromia region, Ethiopia

PhD candidate: Tewodros Desalegn Nebi
Institution: Haramaya University, Harar, Ethiopia (in collaboration with Arsi University and EpiGen-Ethiopia project)
Supervisors: Dr. Lemessa Oljira, Prof. Torsten Feldt, Dr. Tafese B Tufa, Prof. Tobias Rinke de Wit and Dr. Tesfaye Gobana

This PhD project aims to develop an integrated, data-driven framework for cholera surveillance, risk mapping, and outbreak prediction in the Oromia Region, where recurrent outbreaks remain a major public health challenge. Across Sub-Saharan Africa, cholera continues to cause substantial morbidity and mortality, particularly in resource-limited settings. The disease, caused by Vibrio cholerae, exhibits high genomic variability, complicating detection, transmission tracking, and control. In Ethiopia, these challenges are intensified by inadequate water, sanitation, and hygiene (WASH) infrastructure, weak surveillance systems, and limited community awareness about the disease.

This study employs a mixed-methods approach, integrating epidemiological, environmental, socio-economic, and genomic data (exiting and will be generate with EpiGen Ethiopia), alongside qualitative insights from key stakeholders. Advanced analytical techniques, including Geographic Information Systems (GIS), spatial statistics, bioinformatics, and machine learning, will be used to map cholera hotspots, identify risk factors, characterize drug-resistant strains, and predict outbreaks. Qualitative analysis will assess community knowledge, attitudes, and practices to inform targeted interventions.

The expected outcomes include improved early warning systems, identification of high-risk areas, and development of an integrated surveillance framework. Ultimately, this research will support evidence-based public health decision-making and contribute to reducing cholera-related morbidity and mortality in Ethiopia and similar settings.

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Genotypic characterization, spatiotemporal dynamics, multilevel determinants, case detection timeliness, and forecasting of measles in Amhara Region, Ethiopia

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A multiscalar approach to understanding the dynamics of cholera in Ethiopia