Modelling the Impact of Climate on Cholera

Background Cholera remains a persistent killer in many parts of the world. The disease is highly climate sensitive, however previous attempts to model its future under climate change have been limited to statistical analyses. Mechanistic models are an essential addition because they permit a deeper understanding of the complex feedback loops involved in infectious disease transmission, allowing for better modelling of potential scenarios such as interventions or changes in pathogen dynamics. Methods We compare four mathematical models with differing assumptions of climate sensitivity and fit them to a cholera dataset from Kolkata, India using MCMC. We then use bias-corrected climate projections of temperature and rainfall from 10 independent global climate models to produce climate-based cholera projections for the period 2080–2099. Results Using both temperature and rainfall as inputs, the best performing model recreates seasonal patterns highly effectively. Future projections suggest an average increase in cholera cases ranging from 81% − 150% due to climate change by 2080–2099 with earlier peaks in the infection cycle likely due to heightened transmission rates earlier in the year. Sensitivity analysis reveals that uncertainties in parameters related to the contact rate and water dynamics have the greatest impact on model projections, suggesting that these factors are critical for refining future predictions. Conclusion While our mechanistic model shows promise in projecting cholera under climate scenarios, it also highlights uncertainties and gaps in current literature, such as the effects of extreme temperatures and certain epidemiological parameters. Addressing these gaps through multidisciplinary collaboration and refined modelling will be essential for improving cholera projections under changing climate conditions and informing long-term control strategies.