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Bacillary dysentery is an infectious disease and external environmental factors including climate factors play a significant role in its transmission. In this paper, climate-related risk factor is identified and prediction model is built for bacillary dysentery. The database used in this study is integrated monthly climate factors and incidence rates in Harbin City from 1986 to 1990. Three consecutive months' climate data are used to predict one month's incidence in order to find the relevant factors for bacillary dysentery transmission. The least absolute shrinkage and selectionator operator is applied to select related climate factors. Then, the prediction model is built by using the selected climate factors. Through the results of the experiments, monthly accumulative precipitation, daily maximum precipitation, daily maximum precipitation of the past one month, monthly mean minimum temperature and monthly mean wind velocity are found to result in the highest relative risk for bacillary dysentery.
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Shao et al. (2015) studied this question.
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