BACKGROUND: We estimated the effects of rainfall and temperature on the number of non-cholera diarrhoea cases and identified population factors potentially affecting vulnerability to the effect of the climate factors in Dhaka, Bangladesh. METHODS: Weekly rainfall, temperature and number of hospital visits for non-cholera diarrhoea were analysed by time-series regression. A Poisson regression model was used to model the relationships controlling for seasonally varying factors other than the weather variables. Modifications of weather effects were investigated by fitting the models separately to incidence series according to their characteristics (sex, age, socio-economic, hygiene and sanitation status). RESULTS: The number of non-cholera diarrhoea cases per week increased by 5.1% (95% CI: 3.3-6.8) for every 10 mm increase above the threshold of 52 mm of average rainfall over lags 0-8 weeks. The number of cases also increased by 3.9% (95% CI: 0.6-7.2) for every 10 mm decrease below the same threshold of rainfall. Ambient temperature was also positively associated with the number of non-cholera diarrhoea cases. There was no evidence for the modification of both 'high and low rainfall' effects by individual characteristics, while the effect of temperature was higher amongst those individuals at a lower educational attainment and unsanitary toilet users. CONCLUSIONS: The number of non-cholera diarrhoea cases increased both above and below a threshold level with high and low rainfall in the preceding weeks. The number of cases also increased with higher temperature, particularly in those individuals at a lower socio-economic and sanitation status.
BACKGROUND: We estimated the effects of rainfall and temperature on the number of non-cholera diarrhoea cases and identified population factors potentially affecting vulnerability to the effect of the climate factors in Dhaka, Bangladesh. METHODS: Weekly rainfall, temperature and number of hospital visits for non-cholera diarrhoea were analysed by time-series regression. A Poisson regression model was used to model the relationships controlling for seasonally varying factors other than the weather variables. Modifications of weather effects were investigated by fitting the models separately to incidence series according to their characteristics (sex, age, socio-economic, hygiene and sanitation status). RESULTS: The number of non-cholera diarrhoea cases per week increased by 5.1% (95% CI: 3.3-6.8) for every 10 mm increase above the threshold of 52 mm of average rainfall over lags 0-8 weeks. The number of cases also increased by 3.9% (95% CI: 0.6-7.2) for every 10 mm decrease below the same threshold of rainfall. Ambient temperature was also positively associated with the number of non-cholera diarrhoea cases. There was no evidence for the modification of both 'high and low rainfall' effects by individual characteristics, while the effect of temperature was higher amongst those individuals at a lower educational attainment and unsanitary toilet users. CONCLUSIONS: The number of non-cholera diarrhoea cases increased both above and below a threshold level with high and low rainfall in the preceding weeks. The number of cases also increased with higher temperature, particularly in those individuals at a lower socio-economic and sanitation status.
Authors: Adam Bennett; Leonardo D Epstein; Robert H Gilman; Vitaliano Cama; Caryn Bern; Lilia Cabrera; Andres G Lescano; Jonathan Patz; Cesar Carcamo; Charles R Sterling; William Checkley Journal: Am J Public Health Date: 2012-05-17 Impact factor: 9.308
Authors: Darlene Bhavnani; Jason E Goldstick; William Cevallos; Gabriel Trueba; Joseph N S Eisenberg Journal: Am J Trop Med Hyg Date: 2014-02-24 Impact factor: 2.345