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. 2025 Jul 31;17(7):4732-4745.
doi: 10.21037/jtd-24-1703. Epub 2025 Jul 28.

Epidemiological features and risk factors of SARS-CoV-2 reinfection: a retrospective cohort analysis in Xiamen, China

Yunkang Zhao #  1 , Yao Wang #  1 , Yidun Zhang #  2 , Zeyu Zhao  1 , Buasiyamu Abudunaibi  1 , Kang Fang  1 , Huimin Qu  1 , Qiao Liu  1 , Yanhua Su  1 , Chenghao Su  2   3 , Zhinan Guo  2 , Tianmu Chen  1
Affiliations

Epidemiological features and risk factors of SARS-CoV-2 reinfection: a retrospective cohort analysis in Xiamen, China

Yunkang Zhao et al. J Thorac Dis. .

Abstract

Background: Recently, surges in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfections in China have raised public concern. We investigated the epidemiological features and risk factors for SARS-CoV-2 reinfection in China.

Methods: A retrospective cohort study was conducted in Xiamen, China (2021-2023) with two subcohorts: Delta-Omicron (cohort 1) and Omicron-Omicron (cohort 2). Descriptive analysis and ensemble modeling were employed to evaluate reinfections.

Results: A total of 327 cases without fatalities were included. Reinfections accounted for 14.68% of cases, with 22.51% in cohort 1 and 3.68% in cohort 2. Compared with primary infections (PIs) (99.69% symptomatic, 56.54% hospitalized), reinfections were less severe, with fewer symptomatic instances (47.92%) and hospitalizations (4.65%). The majority of reinfections (83.33%) occurred following the relaxation of strict public health and social measures. The median time interval between PI and reinfection was longer for cohort 1 (462 days) than for cohort 2 (280 days). Reinfection risks were noted among lesser developed regions, those without persistent PI, those with primary Delta variant infection, government and hospital workers, and unvaccinated individuals.

Conclusions: SARS-CoV-2 reinfections are generally less severe and are influenced by the relaxation of control measures, viral evolution, and changing patterns of population immunity and contact; this underscores the need for ongoing surveillance and targeted public health strategies to manage future infection waves.

Keywords: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); coronavirus disease 2019 (COVID-19); primary infection (PI); reinfection.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1703/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Epidemiological features of the SARS-CoV-2 reinfection. (A) The epidemic curve of the study population. (B) The distribution of key time intervals of SARS-CoV-2 reinfection. COVID-19, coronavirus disease 2019; PI, primary infection; RI, reinfection; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Tpr, the time interval between primary infection and reinfection; Tvr, the time interval from the most recent vaccination to the occurrence of reinfection.
Figure 2
Figure 2
Risk factors analysis of the SARS-CoV-2 reinfection. (A) Result of the optimal multivariate logistic regression for SARS-CoV-2 reinfection. (B) Result of the optimal GAM for SARS-CoV-2 reinfection. GAM, generalized additive model; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
Figure 3
Figure 3
The survival analysis for the SARS-CoV-2 reinfection. (A) The survival curve of the population examined for SARA-COV-2 reinfection. (B) Result of the univariate survival analysis and log-rank test for SARS-CoV-2 reinfection. (C) Result of the hierarchical analysis and log-rank test for SARS-CoV-2 reinfection. (D) Result of the optimal the optimal Cox proportional-hazards model for SARS-CoV-2 reinfection. KM, Kaplan-Meier; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
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