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Recent studies arising from both statistical analysis and dynamical disease models indicate that there is a link between the incidence of cholera, a paradigmatic waterborne bacterial illness endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). Cholera incidence typically increases following boreal winter El Niño events for the period 1973–2001. Observational and model analyses find that Bangladesh summer rainfall is enhanced following winter El Niño events, providing a plausible physical link between El Niño and cholera incidence. However, rainfall and cholera incidence do not increase following every winter El Niño event. Substantial variations in Bangladesh precipitation also occur in simulations in which identical sea surface temperature (SST) anomalies are prescribed in the central and eastern tropical Pacific. Bangladesh summer precipitation is thus not uniquely determined by forcing from the tropical Pacific, with significant implications for predictions of cholera risk. Nonparametric statistical analysis is used to identify regions of SST anomalies associated with variations in Bangladesh rainfall in an ensemble of pacemaker simulations. The authors find that differences in the response of Bangladesh summer precipitation to winter El Niño events are strongly associated with the persistence of warm SST anomalies in the central Pacific. Also there are significant differences in the SST patterns associated with positive and negative Bangladesh rainfall anomalies, indicating that the response is not fully linear. SST anomalies in the Indian Ocean also modulate the influence of the tropical Pacific, with colder Indian Ocean SST tending to enhance Bangladesh precipitation relative to warm Indian Ocean SST for identical conditions in the central and eastern tropical Pacific. This influence is not fully linear. Forecasts of Bangladesh rainfall and cholera risk may thus be improved by considering the Niño-3 and Niño-4 indices separately, rather than the Niño-3.4 index alone. Additional skill may also be gained by incorporating information on the southeast Indian Ocean and by updating the forecast with information on the evolution of the SST anomalies into spring. [ABSTRACT FROM AUTHOR]

Background: A stationary (i.e., constant through time) association between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and epidemics of cholera in Bangladesh has been widely assumed. However, whether or not elements of the local climate that are relevant for cholera transmission have stationary signatures of the IOD on their dynamics over different time scales is still not clear. Here we report results on the time-varying relationships between the various remote and local environmental drivers and cholera incidence in Bangladesh., Methodology/principal Findings: We performed a cross wavelet coherency analysis to examine patterns of association between monthly cholera cases in the hospitals in Dhaka and Matlab (1983-2008) and indices for both IOD and ENSO. Our results showed that the strength of both the IOD and ENSO associations with cholera hospitalizations changed across time scales during the study period. In Dhaka, 4-year long coherent cycles were observed between cholera and the index of IOD in 1988-1997. In Matlab, the effect of ENSO was more dominant while there was no evidence for an IOD effect on cholera hospitalizations., Conclusions/significance: Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between cholera hospitalizations and climatic factors in cholera epidemic early warning systems.

Background: It has been reported that the El Niño-Southern Oscillation (ENSO) influences the interannual variation of endemic cholera in Bangladesh. There is increased interest in the influence of the Indian Ocean dipole (IOD), a climate mode of coupled ocean-atmosphere variability, on regional ocean climate in the Bay of Bengal and on Indian monsoon rainfall., Objectives: We explored the relationship between the IOD and the number of cholera patients in Bangladesh, controlling for the effects of ENSO., Methods: Time-series regression was performed. Negative binomial models were used to estimate associations between the monthly number of hospital visits for cholera in Dhaka and Matlab (1993-2007) and the dipole mode index (DMI) controlling for ENSO index [NINO3, a measure of the average sea surface temperature (SST) in the Niño 3 region], seasonal, and interannual variations. Associations between cholera cases and SST and sea surface height (SSH) of the northern Bay of Bengal were also examined., Results: A 0.1-unit increase in average DMI during the current month through 3 months before was associated with an increase in cholera incidence of 2.6% [(95% confidence interval (CI), 0.0-5.2; p = 0.05] in Dhaka and 6.9% (95% CI, 3.2-10.8; p < 0.01) in Matlab. Cholera incidence in Dhaka increased by 2.4% (95% CI, 0.0-5.0; p = 0.06) after a 0.1-unit decrease in DMI 4-7 months before. Hospital visits for cholera in both areas were positively associated with SST 0-3 months before, after adjusting for SSH (p < 0.01)., Conclusions: These findings suggest that both negative and positive dipole events are associated with an increased incidence of cholera in Bangladesh with varying time lags.