Estimation methods of reproduction numbers for epidemics of varying strains of COVID-19

Q1 Social Sciences
Siying Xiong , Shaojian Cai , Fengying Wei , Guangmin Chen , Kuicheng Zheng , Jianfeng Xie
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引用次数: 0

Abstract

The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases. During the COVID pandemic, China implemented a dynamic zero-COVID policy on the Chinese mainland until the end of 2022. This study compares three estimation methods of basic reproduction numbers on small-scale, short-duration COVID-19 epidemics in Fujian Province. Basic reproduction numbers were investigated using a varying-strain model via a next-generation matrix method. Serial intervals were derived using the infector–infectee pairs of two epidemics from the Fujian Provincial Center for Disease Control and Prevention. Basic reproduction numbers were estimated using the maximum likelihood estimation method and the exponential growth method. The curves of the effective reproduction numbers of the three epidemics were plotted by utilizing daily cases and the EpiEstim R package. The spatial heterogeneity of infection cases was described using the Gini coefficient. This study provides significant insights on the estimation methods of reproduction numbers for policymakers in the local government. The results reveal that social contacts between infectors and susceptible individuals should be reduced to avoid an increase in deaths and to fight against the spread of infectious diseases.
不同菌株 COVID-19 流行病繁殖数量的估算方法
在传染病的早期阶段,繁殖数量和序列间隔的估计方法非常重要。在 COVID 流行期间,中国在中国大陆实施了动态的零 COVID 政策,直至 2022 年底。本研究比较了在福建省小规模、短期 COVID-19 流行中基本繁殖数的三种估算方法。通过新一代矩阵法,使用变株模型对基本繁殖数进行了研究。利用福建省疾病预防控制中心提供的两次疫情的感染者-被感染者对,得出序列间隔。采用最大似然估计法和指数增长法估算基本繁殖数。利用日病例和 EpiEstim R 软件包绘制了三次疫情的有效繁殖数曲线。感染病例的空间异质性采用基尼系数进行描述。这项研究为地方政府决策者提供了有关繁殖数量估算方法的重要启示。研究结果表明,应减少感染者和易感人群之间的社会接触,以避免死亡人数的增加,并防止传染病的传播。
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
Journal of Biosafety and Biosecurity
Journal of Biosafety and Biosecurity Social Sciences-Linguistics and Language
CiteScore
6.00
自引率
0.00%
发文量
20
审稿时长
41 days
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