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. 2025 Jun 2:13:1521658.
doi: 10.3389/fpubh.2025.1521658. eCollection 2025.

Analysis of COVID-19 reinfection and its influencing factors among primary healthcare workers in Jiangsu Province: a study based on the omicron variant epidemic

Mingwang Fu  1 , Hualing Chen  1 , Yongkang Qian  1 , Yongjie Zhang  2 , Haijian Guo  2 , Ya Shen  2 , Biyun Xu  3 , Wantong Han  1 , Haoran Zhou  1 , Jinshui Xu  2 , Bingwei Chen  1   4
Affiliations

Analysis of COVID-19 reinfection and its influencing factors among primary healthcare workers in Jiangsu Province: a study based on the omicron variant epidemic

Mingwang Fu et al. Front Public Health. .

Abstract

Objectives: Since the global outbreak of SARS-CoV-2 in 2019, COVID-19 reinfection has become an increasing concern, particularly during the spread of the Omicron variant. Despite numerous international studies on COVID-19 reinfection, research focusing on healthcare workers, particularly those in primary care settings in mainland China, remains limited. This study aims to evaluate COVID-19 reinfection rates among primary healthcare workers (PHWs) in Jiangsu Province and to explore potential risk factors contributing to reinfection.

Methods: This study utilized a combination of online questionnaires and on-site surveys to conduct two waves of investigation targeting PHWs after epidemic control policy adjustment in Jiangsu Province. Differences between the infection at the baseline visit and re-infection at the follow-up visit were analyzed, and multivariate logistic regression was used to assess the factors influencing reinfection.

Results: A total of 5,541 PHWs were included in the study. At the baseline visit, the initial infection rate was 85.85% [95% confidence interval (CI): 84.93-86.77%], and the self-reported reinfection rate was 40.05% (95% CI: 38.65-41.44%). After adjustment, the reinfection rate was 29.41% (95% CI: 28.12-30.71%). The median reinfection interval between the two infections was 146 days (Interquartile range: 129-164 days). Logistic regression model revealed that female sex [odds ratio (OR) = 1.376, 95% CI: 1.190-1.592], history of fever clinic work (OR = 1.179, 95% CI: 1.045-1.330), working over 8 h per day (OR = 1.178, 95% CI: 1.040-1.336), being a nurse (OR = 1.201, 95% CI: 1.029-1.402), and a "less meat, more vegetables" diet (OR = 1.206, 95% CI: 1.020-1.426) were significant risk factors for reinfection. Additionally, regular physical exercise was found to be a protective factor (OR = 0.861, 95% CI: 0.754-0.983).

Conclusion: COVID-19 reinfection rates were relatively high among PHWs in Jiangsu Province, particularly among women, nurses, those with fever clinic experience and working over 8 h per day. This study offers valuable insights for the prevention of COVID-19 reinfection and the development of protection strategies for PHWs. It is recommended that more targeted protective measures be implemented for high-risk groups, including appropriate work arrangements, regular health monitoring, and the promotion of healthy lifestyle habits.

Keywords: COVID-19; COVID-19 reinfection; SARS-CoV-2; omicron variant; primary healthcare workers.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Distribution of infection dates.
Figure 2
Figure 2
Distribution of reinfection intervals.
Figure 3
Figure 3
Newly diagnosed diseases after infection at baseline visit.
Figure 4
Figure 4
Comparison of symptom frequencies between infection at baseline visit and self-reported re-infection at follow-up visit. All symptom comparisons were performed using Chi-square tests.
Figure 5
Figure 5
Comparison of hospitalization and ICU admission rates between infection at baseline visit and re-infection at follow-up visit.
See this image and copyright information in PMC

References

    1. World Health Organization . WHO COVID-19 dashboard: global case data 2024. Available online at: https://data.who.int/dashboards/covid19/cases?m49=001&n=c.
    1. Wang H, Paulson KR, Pease SA, Watson S, Comfort H, Zheng P, et al. Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21. Lancet. (2022) 399:1513–36. doi: 10.1016/S0140-6736(21)02796-3, PMID: - DOI - PMC - PubMed
    1. Goldberg Y, Mandel M, Bar-On YM, Bodenheimer O, Freedman LS, Ash N, et al. Protection and waning of natural and hybrid immunity to SARS-CoV-2. N Engl J Med. (2022) 386:2201–12. doi: 10.1056/NEJMoa2118946, PMID: - DOI - PMC - PubMed
    1. To KK-W, Hung IF-N, Ip JD, Chu AW-H, Chan W-M, Tam AR, et al. Coronavirus disease 2019 (COVID-19) re-infection by a phylogenetically distinct severe acute respiratory syndrome coronavirus 2 strain confirmed by whole genome sequencing. Clin Infect Dis. (2020) 73:e2946–51. doi: 10.1093/cid/ciaa1275, PMID: - DOI - PMC - PubMed
    1. Sabino EC, Buss LF, Carvalho MPS, Prete CA, Jr, Crispim MAE, Fraiji NA, et al. Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence. Lancet. (2021) 397:452–5. doi: 10.1016/S0140-6736(21)00183-5, PMID: - DOI - PMC - PubMed

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