Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (sR 2 increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0)52 offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention.
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This research was funded by Huainan science and technology plan projects (no. 2015 B44).
Conflict of interest
The authors declare that they have no conflict of interest.
Electronic supplementary material
(DOC 30 kb)
(DOC 30 kb)
The monthly distribution of HFMD in Huainan, China, during 2009–2014. (DOC 104 kb)
The lagged effects on HFMD at 95th percentile of temperature (reference at 50th percentile). (DOC 26 kb)
The ACF and PACF of the residual on weekly data in Model_1 (model without ambient temperature) and Model_2(model with ambient temperature). (DOC 48 kb)
Results of the prediction models on weekly data in different groups in Huainan. (DOC 150 kb)
Results of the prediction model on monthly data in Model_1 (model without ambient temperature) and Model_2 (model with ambient temperature). (DOC 92 kb)
Results of the prediction models on monthly data in different groups in Huainan. (DOC 138 kb)
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Zhao, D., Wang, L., Cheng, J. et al. Impact of weather factors on hand, foot and mouth disease, and its role in short-term incidence trend forecast in Huainan City, Anhui Province. Int J Biometeorol 61, 453–461 (2017). https://doi.org/10.1007/s00484-016-1225-9
- Weather factors
- Hand, foot, and mouth disease
- SARIMA model