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. 2008 Jan-Feb;123(1):61-6.
doi: 10.1177/003335490812300109.

Weather and the transmission of bacillary dysentery in Jinan, northern China: a time-series analysis

Affiliations

Weather and the transmission of bacillary dysentery in Jinan, northern China: a time-series analysis

Ying Zhang et al. Public Health Rep. 2008 Jan-Feb.

Abstract

Objectives: This article aims to quantify the relationship between weather variations and bacillary dysentery in Jinan, a city in northern China with a temperate climate, to reach a better understanding of the effect of weather variations on enteric infections.

Methods: The weather variables and number of cases of bacillary dysentery during the period 1987-2000 has been studied on a monthly basis. The Spearman correlation between each weather variable and dysentery cases was conducted. Seasonal autoregressive integrated moving average (SARIMA) models were used to perform the regression analyses.

Results: Maximum temperature (one-month lag), minimum temperature (one-month lag), rainfall (one-month lag), relative humidity (without lag), and air pressure (one-month lag) were all significantly correlated with the number of dysentery cases in Jinan. After controlling for the seasonality, lag time, and long-term trend, the SARIMA model suggested that a 1 degree C rise in maximum temperature might relate to more than 10% (95% confidence interval 10.19, 12.69) increase in the cases of bacillary dysentery in this city.

Conclusions: Weather variations have already affected the transmission of bacillary dysentery in China. Temperatures could be used as a predictor of the number of dysentery cases in a temperate city in northern China. Public health interventions should be undertaken at this stage to adapt and mitigate the possible consequences of climate change in the future.

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Figures

Figure 1
Figure 1
Sequence of weather variables and bacillary dysentery in Jinan, Northern China, 1987–2000
Figure 2
Figure 2
Notified cases vs. model fit cases of bacillary dysentery in Jinan, Northern China, 1987–2000
Figure 3
Figure 3
Plotting of the residuals of the SARIMA model SARIMA

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