From spatial clusters to annual rainfall: assessing the relationship between rainfall and annual cholera case counts in Uganda

Abstract

Background Cholera remains a global public health concern, particularly in low- and middle-income countries where inadequate water, sanitation, and hygiene persist. The transmission of cholera can be influenced by environmental factors, such as rainfall, water availability and sanitation conditions, and contamination sources. Building on a spatial cluster analysis that previously reported cholera hotspot districts in Uganda, this study assessed the relationship between mean annual rainfall and annual cholera case counts in previously identified cholera hotspot districts with high occurrence of such clustering between 2012 and 2022. Methods This study employed a retrospective ecological design to examine the relationship between annual rainfall and annual cholera case counts in previously identified cholera hotspot districts in Uganda using districtlevel data from 2012 to 2022. Cholera surveillance data were obtained from the Ministry of Health, while rainfall data were derived from the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset. Daily rainfall estimates were processed in Google Earth Engine and aggregated to district-level annual rainfall totals. Exploratory analyses included descriptive statistics, scatterplots, and assessments of overdispersion and zero inflation. The relationship between annual rainfall and cholera case counts was evaluated using Generalized estimating equation (GEE) negative binomial regression as the primary analytic approach in Stata version 18. The district-level analyses were conducted as exploratory assessments to examine heterogeneity in rainfall–cholera relationships across hotspot districts. Results Significant spatial and temporal variation in annual rainfall was observed across hotspot districts. Cholera case counts ranged from 0 to 577 cases, with 46 of 154 district-year observations (29.9%) recording no cases. District-level analyses suggested heterogeneity in rainfall-cholera relationships across hotspot districts. In the primary GEE model analysis, annual rainfall showed a positive association with annual cholera case counts, with a 100 mm increase in rainfall corresponding to an estimated 13.2% increase in annual cholera case counts (CR=1.132, 95% CI: 1.024–1.251). However, sensitivity analyses yielded directionally similar but less precise estimates and did not consistently demonstrate statistical significance, suggesting that this finding should be interpreted with appropriate caution.