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Over 160 years after John Snow first analyzed the spatial pattern of cholera cases in London and identified water as its pathway of contagion, the disease remains a major public health threat in many regions around the globe. It causes an estimated number of 2.86 (1.30 - 4.00) million cases and 95000 (21000 - 143000) deaths in 69 endemic countries every year.

Understanding the epidemiology of cholera, when and where it occurs and how it spreads, is key to its prevention and control.

We have developed set of metapopulation and individual-based, mechanistic and semi-mechanistic epidemiological models to tackle epidemiological questions at the country, sub-national and city scale. Our models explicitly take into account the spatial variability of epidemiological processes such as the spread of the disease through hydrological connectivity and human mobility, or the high resolution spatiotemporal clustering of cases. In addition, different environmental drivers of cholera epidemics have been taken into account. In several case studies, the models have been applied to recent cholera outbreaks in Haiti, Senegal, Chad and the Democratic Republic of the Congo. Results highlight the important part played by human mobility in the spreading of the disease and the influence of rainfall and other climatic variables as drivers of disease dynamics in several settings. Applications demonstrate how models can inform epidemiological policy and show the effect of alternative intervention strategies on the course of an epidemic.

We conclude that the explicit treatment of spatial heterogeneity at an appropriate scale is crucial to reproduce real-world dynamics of cholera outbreaks and how suitable models can address relevant questions about the dynamics of the disease, provide insights into ongoing epidemics, may aid emergency management and complement current epidemiological practice.