Forecast of peak infection and estimate of excess deaths in COVID-19 transmission and prevalence in Taiyuan City, 2022 to 2023

IF 8.8 3区 医学 Q1 Medicine
Jia-Lin Wang , Xin-Long Xiao , Fen-Fen Zhang , Xin Pei , Ming-Tao Li , Ju-Ping Zhang , Juan Zhang , Gui-Quan Sun
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Abstract

In this paper, with the method of epidemic dynamics, we assess the spread and prevalence of COVID-19 after the policy adjustment of prevention and control measure in December 2022 in Taiyuan City in China, and estimate the excess population deaths caused by COVID-19. Based on the transmission mechanism of COVID-19 among individuals, a dynamic model with heterogeneous contacts is established to describe the change of control measures and the population's social behavior in Taiyuan city. The model is verified and simulated by basing on reported case data from November 8th to December 5th, 2022 in Taiyuan city and the statistical data of the questionnaire survey from December 1st to 23rd, 2022 in Neijiang city. Combining with reported numbers of permanent residents and deaths from 2017 to 2021 in Taiyuan city, we apply the dynamic model to estimate theoretical population of 2022 under the assumption that there is no effect of COVID-19. In addition, we carry out sensitivity analysis to determine the propagation character of the Omicron strain and the effect of the control measures. As a result of the study, it is concluded that after adjusting the epidemic policy on December 6th, 2022, three peaks of infection in Taiyuan are estimated to be from December 22nd to 31st, 2022, from May 10th to June 1st, 2023, and from September 5th to October 13th, 2023, and the corresponding daily peaks of new cases can reach 400 000, 44 000 and 22 000, respectively. By the end of 2022, excess deaths can range from 887 to 4887, and excess mortality rate can range from 3.06% to 14.82%. The threshold of the infectivity of the COVID-19 variant is estimated 0.0353, that is if the strain infectivity is above it, the epidemic cannot be control with the previous normalization measures.

2022 至 2023 年太原市 COVID-19 传播和流行高峰感染预测及超额死亡估计数
本文采用流行病学的方法,评估了2022年12月太原市防控措施政策调整后COVID-19在太原市的传播和流行情况,并估算了COVID-19导致的人口超额死亡。根据 COVID-19 在个体间的传播机制,建立了一个异质性接触的动态模型来描述太原市防控措施的变化和人群的社会行为。根据太原市 2022 年 11 月 8 日至 12 月 5 日的病例报告数据和内江市 2022 年 12 月 1 日至 23 日的问卷调查统计数据,对模型进行了验证和模拟。结合太原市 2017 年至 2021 年常住人口报告数和死亡人数,在不考虑 COVID-19 影响的前提下,运用动态模型对 2022 年的理论人口数进行估算。此外,我们还进行了敏感性分析,以确定 Omicron 菌株的传播特性和控制措施的效果。研究结果表明,2022 年 12 月 6 日调整疫情政策后,太原市预计将出现三个感染高峰,分别是 2022 年 12 月 22 日至 31 日、2023 年 5 月 10 日至 6 月 1 日和 2023 年 9 月 5 日至 10 月 13 日,相应的日新增病例高峰分别可达 400 000 例、44 000 例和 22 000 例。到 2022 年底,超额死亡人数可达 887 至 4887 人,超额死亡率可达 3.06% 至 14.82%。COVID-19变异株的传染性临界值估计为0.0353,即如果该变异株的传染性超过该临界值,则疫情将无法通过之前的正常化措施得到控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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