首页> 外文期刊>Transactions of the Royal Society of Tropical Medicine and Hygiene >Influence of temperature and rainfall on the evolution of cholera epidemics in Lusaka, Zambia, 2003-2006: analysis of a time series.
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Influence of temperature and rainfall on the evolution of cholera epidemics in Lusaka, Zambia, 2003-2006: analysis of a time series.

机译:温度和降雨对赞比亚卢萨卡霍乱疫情演变的影响,2003-2006年:时间序列分析。

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摘要

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.
机译:在这项研究中,我们旨在描述2003年至2006年间在赞比亚卢萨卡发生的三种霍乱流行病的演变,并分析病例数增加与气候因素之间的关系。建立了控制季节和趋势的Poisson自回归模型,以估计每周病例数增加与每日最高温度和降雨量的每周平均值之间的关联。所有流行病均显示与雨季(11月至3月)一致的季节性趋势。爆发前6周温度升高1摄氏度,可解释霍乱病例数增加的5.2%[相对风险(RR)1.05,95%CI 1.04-1.06](2003-2006)。另外,在三周前降雨增加了50毫米,说明增加了2.5%(RR 1.02,95%CI 1.01-1.04)。归因于温度的风险为4.9%,降雨为2.4%。如果在雨季开始之前的6周观察到温度升高,然后在3周后降雨增加,都超过了预期水平,则预计在接下来的3周内霍乱病例数将增加。我们的解释模型可能有助于开发警告信号,以减少假定的霍乱流行的影响。

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