{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T01:10:30Z","timestamp":1775005830044,"version":"3.50.1"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T00:00:00Z","timestamp":1748822400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Objectives<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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\u201386.77%], and the self-reported reinfection rate was 40.05% (95% CI: 38.65\u201341.44%). After adjustment, the reinfection rate was 29.41% (95% CI: 28.12\u201330.71%). The median reinfection interval between the two infections was 146\u202fdays (Interquartile range: 129\u2013164\u202fdays). Logistic regression model revealed that female sex [odds ratio (OR)\u202f=\u202f1.376, 95% CI: 1.190\u20131.592], history of fever clinic work (OR\u202f=\u202f1.179, 95% CI: 1.045\u20131.330), working over 8\u202fh per day (OR\u202f=\u202f1.178, 95% CI: 1.040\u20131.336), being a nurse (OR\u202f=\u202f1.201, 95% CI: 1.029\u20131.402), and a \u201cless meat, more vegetables\u201d diet (OR\u202f=\u202f1.206, 95% CI: 1.020\u20131.426) were significant risk factors for reinfection. Additionally, regular physical exercise was found to be a protective factor (OR\u202f=\u202f0.861, 95% CI: 0.754\u20130.983).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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\u202fh 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.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1521658","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T05:24:00Z","timestamp":1748841840000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Analysis of COVID-19 reinfection and its influencing factors among primary healthcare workers in Jiangsu Province: a study based on the omicron variant epidemic"],"prefix":"10.3389","volume":"13","author":[{"given":"Mingwang","family":"Fu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hualing","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongkang","family":"Qian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongjie","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haijian","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ya","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Biyun","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wantong","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoran","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinshui","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingwei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,2]]},"reference":[{"key":"ref1","volume-title":"WHO COVID-19 dashboard: global case data 2024","year":""},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1513","DOI":"10.1016\/S0140-6736(21)02796-3","article-title":"Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020\u201321","volume":"399","author":"Wang","year":"2022","journal-title":"Lancet"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"2201","DOI":"10.1056\/NEJMoa2118946","article-title":"Protection and waning of natural and hybrid immunity to SARS-CoV-2","volume":"386","author":"Goldberg","year":"2022","journal-title":"N Engl J Med"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"e2946","DOI":"10.1093\/cid\/ciaa1275","article-title":"Coronavirus disease 2019 (COVID-19) re-infection by a phylogenetically distinct severe acute respiratory syndrome coronavirus 2 strain confirmed by whole genome sequencing","volume":"73","author":"To","year":"2020","journal-title":"Clin Infect Dis"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1016\/S0140-6736(21)00183-5","article-title":"Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence","volume":"397","author":"Sabino","year":"2021","journal-title":"Lancet"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"100812","DOI":"10.1016\/j.nmni.2020.100812","article-title":"COVID-19 reinfection: prolonged shedding or true reinfection?","volume":"38","author":"Falahi","year":"2020","journal-title":"New Microb New Infect"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"S257","DOI":"10.1016\/j.mjafi.2021.02.010","article-title":"Reinfection in COVID-19: a scoping review","volume":"77","author":"Pinto","year":"2021","journal-title":"Med J Armed Forces India"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1038\/s43856-024-00539-2","article-title":"Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and long COVID","volume":"4","author":"Hadley","year":"2024","journal-title":"Commun Med"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"2414","DOI":"10.1002\/jmv.27634","article-title":"An exploratory study on the propagation of SARS-CoV-2 variants: omicron is the most predominant variant","volume":"94","author":"Rathinasamy","year":"2022","journal-title":"J Med Virol"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1186\/s12879-024-09225-z","article-title":"How does the SARS-CoV-2 reinfection rate change over time? 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