Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
Proc Natl Acad Sci U S A. 2012 Feb 7;109(6):2033-6. doi: 10.1073/pnas.1108438109. Epub 2012 Jan 23.
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.
城市环境中地方性霍乱的种群动态——特别是季节性疫情的规模和分布的年际变化——仍未被充分理解，且极具不可预测性。部分原因是，大型和不断发展的城市中心在人口统计学、社会经济学和环境方面存在很大差异。尽管存在这种异质性，但气候变化对传染病种群动态的影响被认为是一种大规模的区域性现象，因此，以前仅使用不包含空间结构的时间模型来探讨霍乱的这种影响。在这里，我们表明，概率空间模型可以解释孟加拉国达卡大都市的霍乱动态，并为提前 11 个月的霍乱预测提供基础。关键的是，我们发现气候变化（厄尔尼诺南方涛动和洪水）的作用相当局限：存在一个对城市其他地区传播风险起作用的气候敏感的城市核心区。这里提出的建模框架应该适用于其他城市的霍乱，以及城市环境中的其他传染病和具有时空相互作用的其他生物系统。
