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| Construction and evaluation of a statistical model for COVID-19 imported cases in Xiamen |
| Zhang Yidun1, Tong Yiqi2, Huang Shijie1, Huang Siying2, Zhuang Fuzhen2 |
1 Xiamen Center for Disease Control and Prevention, Xiamen 361000, China;
2 Xiamen Institute of Data Intelligence, Xiamen 361000, China |
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Abstract Objective To analyze the risk of imported COVID-19 cases in Xiamen, and to provide data support for the public health department to prevent the spread of imported cases; to assess the future shortage of medical resources in Xiamen, and to provide a reference basis for administrative decisions.Methods A statistical model was constructed to predict imported cases in Xiamen. Due to the small number of initial samples in Xiamen, the model was first initialized based on the overseas import situation of Guangzhou, and then fitted based on the daily epidemic situation in Xiamen. Considering the constant change of entry policies and the rapid development of epidemic in various countries (regions), a dictionary was constructed and maintained to dynamically calculate the risk weights of travelers from different countries. Finally, exponential smoothing method was used to update the parameters of the model.Results From March 23, 2020 to December 31, 2020, Xiamen reported a total of 277 imported cases in which asymptomatic infections were included, and 257 cases were predicted by our model. The experimental results showed that the F1-score of our proposed model reached 77.3%.Conclusion The statistical model has good predictive-ability.
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Received: 11 June 2021
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