Evidence map›Paper›PMID 42614493›Full record

ArticleFrontiers in public health2026

Analysis of epidemiological characteristics and influencing factors of Long COVID syndrome among university students in the post-pandemic era.

Songqing Guo, Mingma Li, Yuxiang Liu, Yi Zhang, Yuchen Pan, Xinru Wang, Hongqiao Li, Xiangjun Zhai, Xiang Hong, Bei Wang

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Songqing GuoDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Mingma LiDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Yuxiang LiuDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Yi ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Yuchen PanDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Xinru WangDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Hongqiao LiDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Xiangjun ZhaiScience and Technology Major Project Implementation Office of Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Xiang HongDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.
Bei WangDepartment of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyze the epidemiological characteristics of Long COVID syndrome in university students during the post-pandemic era, providing evidence for developing prevention strategies and rehabilitation plans for COVID-19 patients. Methods: A cohort study was conducted in November 2023, recruiting students from a university in Nanjing for baseline investigations. Demographic characteristics, vaccination history, infection history, and venous blood samples were collected to detect SARS-CoV-2 IgG and IgM antibody levels. For individuals with prior COVID-19 infections, Long COVID syndrome status was assessed 1 year post-infection. Multivariate logistic regression analysis was employed to identify influencing factors. Results: The study included 246 participants (mean age: 21.88 ± 2.06 years; 65.04% female). Median SARS-CoV-2 IgG and IgM levels were 16.500 (105.000, 239.000) AU/ml and 0.095 (0.053, 0.183) AU/ml, respectively. Among 246 participants with prior COVID-19 infection, 82 (33.33%) developed Long COVID syndrome, with alopecia (36.59%), memory decline (28.05%), and sleep disturbances (28.05%) being the most prevalent symptoms. Multivariate analysis revealed that, compared to the non-Long COVID group, depressive symptoms may be positively associated with Long COVID syndrome (adjusted Conclusion: The incidence of Long COVID syndrome among university students is comparable to that of the general population. A bidirectional relationship may exist between depressive symptoms and Long COVID syndrome, warranting increased clinical and public health attention.

Indexed as

COVID-19StudentsAdultChinaCohort StudiesFemaleHumansImmunoglobulin MMalePandemicsPost-Acute COVID-19 SyndromeRisk FactorsSARS-CoV-2UniversitiesYoung AdultImmunoglobulin Mcohort studyinfluencing factors analysisLong COVID syndromepost-pandemic erauniversity student population

Identifiers

PMID42614493
PMCPMC13481728

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