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张晶, 王海英, 顾长贵, 杨会杰

Travel behavior adjustment based epidemic spreading model and prediction for COVID-19

Zhang Jing, Wang Hai-Ying, Gu Chang-Gui, Yang Hui-Jie
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  • 由于新冠病毒不断变异, 在很长的时期内疫情会多次爆发, 每次有不同的特点. 对局部地区爆发的每一波疫情进行预测, 成为人们制定应对策略的关键. 在宏观层面对疫情防控措施优化, 意味着疫情演化数据的缺乏, 这给基于实证数据的疫情预测带来了特殊的困难. 考虑疫情与出行行为的相互影响, 本文提出了一个改进的虫口模型, 用以描述新冠疫情传播动力学过程, 试图利用少量疫情相关数据对局部地区爆发的某一特定疫情进行预测. 实证分析表明, 该模型可以很好地复现上海市2022年3月1日到6月28日发布的新冠病毒阳性感染者数据. 采用这一模型对上海市2022年12月以来的疫情趋势和关键节点进行了预测. 建议决策部门按照统计学抽样原则, 建立和完善疫情监测系统, 为疫情预测提供可靠的数据.
    Owing to the continuous variant of the COVID-19 virus, the present epidemic may persist for a long time, and each breakout displays strongly region/time-dependent characteristics. Predicting each specific burst is the basic task for the corresponding strategies. However, the refinement of prevention and control measures usually means the limitation of the existing records of the evolution of the spread, which leads to a special difficulty in making predictions. Taking into account the interdependence of people’s travel behaviors and the epidemic spreading, we propose a modified logistic model to mimic the COVID-19 epidemic spreading, in order to predict the evolutionary behaviors for a specific bursting in a megacity with limited epidemic related records. It continuously reproduced the COVID-19 infected records in Shanghai, China in the period from March 1 to June 28, 2022. From December 7, 2022 when Mainland China adopted new detailed prevention and control measures, the COVID-19 epidemic broke out nationwide, and the infected people themselves took “ibuprofen” widely to relieve the symptoms of fever. A reasonable assumption is that the total number of searches for the word “ibuprofen” is a good representation of the number of infected people. By using the number of searching for the word “ibuprofen” provided on Baidu, a famous searching platform in Mainland China, we estimate the parameters in the modified logistic model and predict subsequently the epidemic spreading behavior in Shanghai, China starting from December 1, 2022. This situation lasted for 72 days. The number of the infected people increased exponentially in the period from the beginning to the 24th day, reached a summit on the 31st day, and decreased exponentially in the period from the 38th day to the end. Within the two weeks centered at the summit, the increasing and decreasing speeds are both significantly small, but the increased number of infected people each day was significantly large. The characteristic for this prediction matches very well with that for the number of metro passengers in Shanghai. It is suggested that the relevant departments should establish a monitoring system composed of some communities, hospitals, etc. according to the sampling principle in statistics to provide reliable prediction records for researchers.
        通信作者:杨会杰,hjyang@usst.edu.cn
      • 基金项目:国家自然科学基金(批准号: 1227051117, 11875042, 11505114)资助的课题
        Corresponding author:Yang Hui-Jie,hjyang@usst.edu.cn
      • Funds:Project supported by the National Natural Science Foundation of China (Grant Nos. 1227051117, 11875042, 11505114)
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    出版历程
    • 收稿日期:2022-12-25
    • 修回日期:2023-02-24
    • 上网日期:2023-04-14
    • 刊出日期:2023-05-05

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