Highly localized sensitivity to climate forcing drives endemic cholera in a megacity

Abstract

The population dynamics of endemic cholera in urban environments--in particular interannual variation in the size and distribution of seasonal outbreaks--remain poorly understood and highly unpredictable. In part, this situation is due to the considerable demographic, socioeconomic, and environmental heterogeneity of large and growing urban centers. Despite this heterogeneity, the influence of climate variability on the population dynamics of infectious diseases is considered a large-scale, regional, phenomenon, and as such has been previously addressed for cholera only with temporal models that do not incorporate spatial structure. Here we show that a probabilistic spatial model can explain cholera dynamics in the megacity of Dhaka, Bangladesh, and afford a basis for cholera forecasts at lead times of 11 mo. Critically, we find that the action of climate variability (El Niño southern oscillation and flooding) is quite localized: There is a climate-sensitive urban core that acts to propagate risk to the rest of the city. The modeling framework presented here should be applicable to cholera in other cities, as well as to other infectious diseases in urban settings and other biological systems with spatiotemporal interactions.

Fig. 1.

The thanas (administrative subdivisions) of Dhaka. We divided thanas into two groups: older, core thanas (orange) and newer, peripheral thanas (blue).

Fig. 2.

Cases of cholera per 10,000 in Dhaka (in black) superimposed to an index for the El Niño southern oscillation (ENSO) (in blue) and annualized flood extent at the level of the country as a whole (red). (Top) The whole city of Dhaka; (Middle) the core, older region of the city; (Bottom) the peripheral, new regions. The interannual variability in the cholera rate is coherent with that of the climate covariates, especially for the older thanas and for the very large El Niño of 1998.

Fig. 3.

Schematic representation of MDIMC model. Thanas of the same hue are governed by the same rules. Each thana can be in one of three states (0, 1, or 2 for no cholera, low cholera, or high cholera, respectively) as indicated by the different shades within each of the two groups. Probability of transitions between states from one month to the next can vary according to season, district group, state of neighboring districts, and climate covariates.

Fig. 4.

Eleven-month predictions (blue dots) with empirical estimate of 95% confidence interval (yellow shaded region) vs. the observed data (black line). (Left Inset) Distribution of predictions for October 1998. (Right Inset) Distribution of predictions for May 2003.