Constantin de Magny Guillaume, Murtugudde Raghu, Sapiano Mathew R P, Nizam Azhar, Brown Christopher W, Busalacchi Antonio J, Yunus Mohammad, Nair G Balakrish, Gil Ana I, Lanata Claudio F, Calkins John, Manna Byomkesh, Rajendran Krishnan, Bhattacharya Mihir Kumar, Huq Anwar, Sack R Bradley, Colwell Rita R
Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA.
Proc Natl Acad Sci U S A. 2008 Nov 18;105(46):17676-81. doi: 10.1073/pnas.0809654105. Epub 2008 Nov 10.
The causative agent of cholera, Vibrio cholerae, has been shown to be autochthonous to riverine, estuarine, and coastal waters along with its host, the copepod, a significant member of the zooplankton community. Temperature, salinity, rainfall and plankton have proven to be important factors in the ecology of V. cholerae, influencing the transmission of the disease in those regions of the world where the human population relies on untreated water as a source of drinking water. In this study, the pattern of cholera outbreaks during 1998-2006 in Kolkata, India, and Matlab, Bangladesh, and the earth observation data were analyzed with the objective of developing a prediction model for cholera. Satellite sensors were used to measure chlorophyll a concentration (CHL) and sea surface temperature (SST). In addition, rainfall data were obtained from both satellite and in situ gauge measurements. From the analyses, a statistically significant relationship between the time series for cholera in Kolkata, India, and CHL and rainfall anomalies was determined. A statistically significant one month lag was observed between CHL anomaly and number of cholera cases in Matlab, Bangladesh. From the results of the study, it is concluded that ocean and climate patterns are useful predictors of cholera epidemics, with the dynamics of endemic cholera being related to climate and/or changes in the aquatic ecosystem. When the ecology of V. cholerae is considered in predictive models, a robust early warning system for cholera in endemic regions of the world can be developed for public health planning and decision making.
霍乱的病原体霍乱弧菌已被证明与其宿主桡足类动物(浮游动物群落的重要成员)一样,原产于河流、河口和沿海水域。温度、盐度、降雨和浮游生物已被证明是霍乱弧菌生态学中的重要因素,影响着世界上那些人口依赖未经处理的水作为饮用水源的地区的疾病传播。在本研究中,分析了1998 - 2006年印度加尔各答和孟加拉国马特莱霍乱疫情的模式以及地球观测数据,目的是建立霍乱预测模型。使用卫星传感器测量叶绿素a浓度(CHL)和海表面温度(SST)。此外,降雨数据来自卫星和实地测量。通过分析,确定了印度加尔各答霍乱时间序列与CHL和降雨异常之间具有统计学意义的关系。在孟加拉国马特莱,观察到CHL异常与霍乱病例数之间存在一个月的统计学显著滞后。从研究结果得出结论,海洋和气候模式是霍乱流行的有用预测指标,地方性霍乱的动态与气候和/或水生生态系统的变化有关。在预测模型中考虑霍乱弧菌的生态学,可为世界流行地区的霍乱建立一个强大的早期预警系统,用于公共卫生规划和决策。