BACKGROUND: The mechanisms underlying the seasonality of cholera are still not fully understood, despite long-standing recognition of clear bimodal seasonality in Bangladesh. We aimed to quantify the contribution of climatic factors to seasonal variations in cholera incidence. METHODS: We investigated the association of seasonal and weather factors with the weekly number of cholera patients in Dhaka, Bangladesh, using Poisson regression models. The contribution of each weather factor (temperature and high and low rainfall) to seasonal variation was estimated as the mean over the study period (1983-2008) for each week of the year of each weather term. Fractions of the number of cholera patients attributed to each weather factor, assuming all values were constant at their minimum risk levels throughout the year, were estimated for spring and monsoon seasons separately. RESULTS: Lower temperature predicted a lower incidence of cholera in the first 15 weeks of the year. Low rainfall predicted a peak in spring, and high rainfall predicted a peak at the end of the monsoon. The risk predicted from all the weather factors combined showed a broadly bi-modal pattern, as observed in the raw data. Low rainfall explained 18% of the spring peak, and high rainfall explained 25% of the peak at the end of the monsoon. CONCLUSIONS: Seasonal variation in temperature and rainfall contribute to cholera incidence in complex ways, presumably in interaction with unmeasured environmental or behavioral factors.
BACKGROUND: The mechanisms underlying the seasonality of cholera are still not fully understood, despite long-standing recognition of clear bimodal seasonality in Bangladesh. We aimed to quantify the contribution of climatic factors to seasonal variations in cholera incidence. METHODS: We investigated the association of seasonal and weather factors with the weekly number of cholera patients in Dhaka, Bangladesh, using Poisson regression models. The contribution of each weather factor (temperature and high and low rainfall) to seasonal variation was estimated as the mean over the study period (1983-2008) for each week of the year of each weather term. Fractions of the number of cholera patients attributed to each weather factor, assuming all values were constant at their minimum risk levels throughout the year, were estimated for spring and monsoon seasons separately. RESULTS: Lower temperature predicted a lower incidence of cholera in the first 15 weeks of the year. Low rainfall predicted a peak in spring, and high rainfall predicted a peak at the end of the monsoon. The risk predicted from all the weather factors combined showed a broadly bi-modal pattern, as observed in the raw data. Low rainfall explained 18% of the spring peak, and high rainfall explained 25% of the peak at the end of the monsoon. CONCLUSIONS: Seasonal variation in temperature and rainfall contribute to cholera incidence in complex ways, presumably in interaction with unmeasured environmental or behavioral factors.
Authors: Stephanie N Hughes; Denise J Greig; Woutrina A Miller; Barbara A Byrne; Frances M D Gulland; James T Harvey Journal: Microb Ecol Date: 2013-02-08 Impact factor: 4.552
Authors: Farhana Haque; M Jahangir Hossain; Subodh Kumar Kundu; Abu Mohd Naser; Mahmudur Rahman; Stephen P Luby Journal: Epidemiology (Sunnyvale) Date: 2013-07-02
Authors: Margherita Grasso; Matteo Manera; Aline Chiabai; Anil Markandya Journal: Int J Environ Res Public Health Date: 2012-04-25 Impact factor: 3.390
Authors: Anette L Christensen; Søren Lundbye-Christensen; Kim Overvad; Lars H Rasmussen; Claus Dethlefsen Journal: BMC Med Res Methodol Date: 2012-11-20 Impact factor: 4.615
Authors: Masahiro Hashizume; Luis Fernando Chaves; A S G Faruque; Md Yunus; Kim Streatfield; Kazuhiko Moji Journal: PLoS One Date: 2013-03-29 Impact factor: 3.240