Predictive time series analysis linking Bengal cholera with terrestrial water storage measured from Gravity Recovery and Climate Experiment sensors

Abstract

Outbreaks of diarrheal diseases, including cholera, are related to floods and droughts in regions where water and sanitation infrastructure are inadequate or insufficient. However, availability of data on water scarcity and abundance in transnational basins, are a prerequisite for developing cholera forecasting systems. With more than a decade of terrestrial water storage (TWS) data from the Gravity Recovery and Climate Experiment, conditions favorable for predicting cholera occurrence may now be determined. We explored lead-lag relationships between TWS in the Ganges-Brahmaputra-Meghna basin and endemic cholera in Bangladesh. Since bimodal seasonal peaks in cholera in Bangladesh occur during spring and autumn seasons, two separate logistical models between TWS and disease time series (2002-2010) were developed. TWS representing water availability showed an asymmetrical, strong association with cholera prevalence in the spring (τ =.0.53; P < 0.001) and autumn (τ = 0.45; P < 0.001) up to 6 months in advance. One unit (centimeter of water) decrease in water availability in the basin increased odds of above normal cholera by 24% (confidence interval [CI] = 20-31%; P < 0.05) in the spring, while an increase in regional water by 1 unit, through floods, increased odds of above average cholera in the autumn by 29% (CI = 22-33%; P < 0.05).