AI Article Synopsis
- The study analyzed three cholera epidemics in Lusaka, Zambia (2003-2006) and examined the connection between case increases and climate factors.
- A Poisson autoregressive model was used to link weekly cholera case numbers with temperature and rainfall data, showing that epidemics correlated with the rainy season.
- A temperature rise of 1°C and a 50 mm increase in rainfall prior to outbreaks were found to significantly correlate with increased cholera cases, indicating potential methods for early warning systems to mitigate future epidemics.
Article Abstract
In this study, we aimed to describe the evolution of three cholera epidemics that occurred in Lusaka, Zambia, between 2003 and 2006 and to analyse the association between the increase in number of cases and climatic factors. A Poisson autoregressive model controlling for seasonality and trend was built to estimate the association between the increase in the weekly number of cases and weekly means of daily maximum temperature and rainfall. All epidemics showed a seasonal trend coinciding with the rainy season (November to March). A 1 degrees C rise in temperature 6 weeks before the onset of the outbreak explained 5.2% [relative risk (RR) 1.05, 95% CI 1.04-1.06] of the increase in the number of cholera cases (2003-2006). In addition, a 50 mm increase in rainfall 3 weeks before explained an increase of 2.5% (RR 1.02, 95% CI 1.01-1.04). The attributable risks were 4.9% for temperature and 2.4% for rainfall. If 6 weeks prior to the beginning of the rainy season an increase in temperature is observed followed by an increase in rainfall 3 weeks later, both exceeding expected levels, an increase in the number of cases of cholera within the following 3 weeks could be expected. Our explicative model could contribute to developing a warning signal to reduce the impact of a presumed cholera epidemic.
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| http://dx.doi.org/10.1016/j.trstmh.2008.07.017 | DOI Listing |
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