Estimation methods of reproduction numbers for epidemics of varying strains of COVID-19
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 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 maximum likelihood estimation and an 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.
Authors
- Jianfeng Xie
- Fengying Wei (ORCID: https://orcid.org/0000-0002-0141-629X)
- Shaowen Xiong (ORCID: https://orcid.org/0000-0002-3531-7206)
- Guangmin Chen (ORCID: https://orcid.org/0000-0001-9103-5193)
- Shaojian Cai
- Kuicheng Zheng
Institutions
- Fujian Medical University (CN)
- Education Department of Fujian Province (CN)
- Fujian Provincial Hospital (CN)
- Fuzhou University (CN)
Publication Details
- Journal
- Journal of Biosafety and Biosecurity
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1016/j.jobb.2024.10.003
- Citations
- 2
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 0.79