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Predicting endemic cholera: the role of climate variability and disease dynamics

ABSTRACT: Retrospective studies of cholera time series in Bangladesh have established a role of theEl Nino Southern Oscillation (ENSO), but also of the non-linear dynamics of the disease itself,through changes in the population levels of immunity in this endemic region. The prediction abilityof a semi-mechanistic time series model that incorporates both these elements is examined. Resultsshow that ENSO is a key covariate and confirm the importance of its interplay with immunity levels,now from the perspective of prediction. They support the feasibility of using the model as a forecast-ing tool: the lack of extreme events between 2001 and 2005 would have been anticipated with 75%confidence half a year ahead with a model fitted to data up to 2000. Long-term change in the trans-mission rate, the non-mechanistic part of the model, sets limits to the forecasting horizon because ofa breakdown in its relationship with river discharge towards the end of the 1990s. We discuss this andother limitations of the approach as well as future directions related to the development of an earlywarning system for cholera in this region.KEY WORDS: Cholera prediction · ENSO · Climate forcing · Population immunity · Early-warningsystems · Time series model · TSIRS · Nonlinear disease dynamics