Author(s)

Emmanuel Chinkaka^1,2*, Francis Chauluka³, Ruth Chinkaka⁴, Billy Kachingwe², Esther Banda Latif⁵

¹Department of Geography and Spatial Sciences, University of Delaware, Newark, USA.
²Department of Earth Sciences, Malawi University of Science and Technology, Limbe, Malawi.
³Department of Water Resources Management, Malawi University of Science and Technology, Limbe, Malawi.
⁴Department of Obstetrics and Gynecology, Queen Elizabeth Central Hospital, Blantyre, Malawi.
⁵Department of Public Health, Nkhoma Mission Hospital, Nkhoma, Malawi.

Cholera remains a public health threat in most developing countries in Asia and Africa including Malawi with seasonal recurrent outbreaks. Malawi’s recent Cholera outbreak in 2022 and 2023, exhibited higher morbidity and mortality rates than the past two decades. Lack of spatiotemporal-based technology and variability assessment tools in Malawi’s Cholera monitoring and management, limit our understanding of the disease’s epidemiology. The present work developed a spatiotemporal variability model for Cholera disease at district level and its relationship to socioeconomic and climatic factors based on cumulative confirmed Cholera cases in Malawi from March 2022 to July 2023 using Z-score statistic and multiscale geographically weighted regression (MGWR) in a Geographical Information System (GIS). We found out that socioeconomic factors such as access to safe drinking water, population density and poverty level, and climatic factors including temperature and rainfall strongly influenced Cholera prevalence in a complex and multifaceted manner. The model shows that Lilongwe, Mangochi, Blantyre and Balaka districts were highly vulnerable to Cholera disease followed by lakeshore districts of Salima, Nkhotakota, Nkhata-Bay and Karonga than other districts. We recommend strategic measures such as Water, Sanitation, and Hygiene (WASH) interventions, community awareness on proper water storage, Cholera case management, vaccination campaigns and spatial-based surveillance systems in the most affected districts. This research has shown that MGWR, as a surveillance system, has the potential of providing insights on the disease’s spatial patterns for public health authorities to identify high-risk districts and implement early response interventions to reduce the spread of the disease.

Cholera, Geospatial Variability, Prevalence, GIS, MGWR, Vulnerability, Malawi

Chinkaka, E. , Chauluka, F. , Chinkaka, R. , Kachingwe, B. and Latif, E. (2024) Geospatial Variability of Cholera Cases in Malawi Based on Climatic and Socioeconomic Influences. Journal of Geographic Information System, 16, 1-20. doi: 10.4236/jgis.2024.161001.