疑似密切接触者作为新冠肺炎大流行期间确诊人口增长趋势的试点指标:一种模拟方法

IF 2 Q3 INFECTIOUS DISEASES
Sisi Huang, Anding Zhu, Yan Wang, Yancong Xu, Lu Li, Dexing Kong
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引用次数: 0

摘要

摘要背景:关于2019新型冠状病毒病疫情的实际情况,需要考虑社会因素,并解释确诊人口的增长趋势。需要建立一个适当的模型,不仅要模拟疫情,还要评估未来的疫情,并为疫情的爆发找到一个试点指标。方法:将原来的易感传染病康复模型修改为易感传染检疫确认康复与社会因素相结合(SIDCRL)模型,该模型将自然传播与外部干预、隔离等社会因素相融合。采用数值模拟方法模拟累计确诊病例数和治愈人数的变化曲线。此外,我们采用模拟方法研究了疑似密切接触者(SCC)与确诊病例增长趋势的最终结果之间的关系。结果:本文选取了中国、韩国、意大利和美国四个具有代表性的国家,分别进行了数值模拟。模型的仿真结果符合疫情发展的实际情况,并做出了合理的预测。此外,据分析,SCC数量的增加导致了疫情的爆发,美国基于SCC人口的预测突出了外部干预和积极预防措施的重要性。结论:该模型的模拟验证了其可靠性,并强调可观察变量SCC可以作为2019冠状病毒病大流行的试点指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Suspected Close Contacts as the Pilot Indicator of the Growth Trend of Confirmed Population During the COVID-19 Pandemic: A Simulation Approach
Abstract Background: Regarding to the actual situation of the new coronavirus disease 2019 epidemic, social factors should be taken into account and the increasing growth trend of confirmed populations needs to be explained. A proper model needs to be established, not only to simulate the epidemic, but also to evaluate the future epidemic situation and find a pilot indicator for the outbreak. Methods: The original susceptible-infectious-recover model is modified into the susceptible-infectious-quarantine-confirm-recover combined with social factors (SIDCRL) model, which combines the natural transmission with social factors such as external interventions and isolation. The numerical simulation method is used to imitate the change curve of the cumulative number of the confirmed cases and the number of cured patients. Furthermore, we investigate the relationship between the suspected close contacts (SCC) and the final outcome of the growth trend of confirmed cases with a simulation approach. Results: This article selects four representative countries, that is, China, South Korea, Italy, and the United States, and gives separate numerical simulations. The simulation results of the model fit the actual situation of the epidemic development and reasonable predictions are made. In addition, it is analyzed that the increasing number of SCC contributes to the epidemic outbreak and the prediction of the United States based on the population of the SCC highlights the importance of external intervention and active prevention measures. Conclusions: The simulation of the model verifies its reliability and stresses that observable variable SCC can be taken as a pilot indicator of the coronavirus disease 2019 pandemic.
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