Influencing factors of COVID-19 antigen conversion time in a Chinese university students: a retrospective analysis

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China also experienced a peak of COVID-19 after the Chinese government changed its COVID-19 policy in December 2022. However, little is known about the factors, such as history of previous infection and vaccine dose, whether affect the time antigen test result to turn negative for SARS-CoV-2. Boarding colleges and universities are prone to outbreaks and repeated infections caused by COVID-19. Therefore, we investigated the factors influencing the time of COVID-19 antigen conversion at one university from April to June 2023. Methods This study included college students from one university in Guangzhou who were positive for the COVID-19 antigen, and collected information such as sex, previous COVID-19 infection history, vaccination dose, symptom onset date, and antigen negative conversion date for retrospective analysis. Chi-square tests or t-tests were used to compare differences between groups. Results A total of 255 college students were included. The average antigen conversion time of patients with first infection was 6.12 ± 1.83 days, and that of patients with second infection was 4.70 ± 1.43 days. The difference was statistically significant (P < 0.001). The average antigen conversion time was 6.21 ± 1.92 days in patients with more than 3 symptoms except fever, which was significantly greater than that in patients with 0–1 (5.54 ± 1.79 days)or 2–3 symptoms(5.45 ± 1.78 days)(P 0.05). Conclusion In college students, a history of SARS-CoV-2 infection and the number of symptoms are the influencing factors of the antigen negativity. COVID-19 Time of antigen negative conversion University student Retrospective study Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has spread throughout almost all parts of the world for more than four years, causing hundreds of millions of infections and many people to be reinfected due to mutation of SARS-CoV-2, especially the Omicron strain, which could break through the protection afforded by previous infection and vaccination [ 1 ] . As of November 9, 2022, it is estimated that 94% of people in the United States have had at least one infection and that 65% have had at least two infections [ 2 ] . After the Chinese government announced that it would no longer implement a dynamic zero COVID-19 policy on 7 December 2022, in the two-month period of December 2022 and January 2023, the BF.7 strain spread rapidly in China. For example, in Beijing, by January 31, 2023, the cumulative infection rate had reached 92.3% [ 3 ] . Like many other countries around the world, another wave of SARS-CoV-2 infections peaked in China in April 2023, during which time it was estimated that as many as 860 million people were infected with the XBB strain, accounting for 61% of China's total population [ 4 ] , as immune protection from previous infections or vaccinations would wane significantly within a few months [ 5 ] . Colleges and universities are susceptible to COVID-19 outbreaks. A study in Japan suggested that even in the context of previous infection and vaccination, the proportion of university students who are repeatedly infected with the SARS-CoV-2 is at least 45% [ 6 ] . Unlike in European countries or the United States, the vast majority of university students in China live in on-campus dormitories rather than off-campus dormitories. In addition, most of the dormitories in Chinese universities are occupied by four or more students. As a result, Chinese universities are more susceptible to the spread of the SARS-CoV-2. Therefore, in the technical plan for the prevention and control of SARS-CoV-2 infection in colleges and universities jointly issued by the Ministry of Education and other departments of China, it is proposed that students with mild SARS-CoV-2 infection on campuses should be cared for and treated at the health stations of colleges and universities or at home [ 7 ] , and cannot live in the original dormitory until the COVID-19 antigen becomes negative. During the peak of SARS-CoV-2 infection in China from April to June 2023, an increasing number of people were infected with the virus, and a significant number of them were infected for the second time. However, it is not entirely clear how several factors, such as previous SARS-CoV-2 infection, affect the recovery time of patients with COVID-19. Previous studies in the United States have shown that the duration of secondary infection is shorter than that of the first infection [ 8 ] , but there are no such studies in China. Here, we retrospectively analyzed the influencing factors of antigen conversion time in college students at one university with SARS-CoV-2 infection to help with the management of COVID-19. Methods A retrospective analysis was performed on a total of 255 college students who were febrile and tested positive for the COVID-19 antigen in the outpatient department of a university in Guangzhou, a city located in southern China, from April to June 2023. The inclusion criteria were as follows: (1) meeting the diagnostic criteria of the “Diagnosis and Treatment Plan for COVID-19 ( the Tenth Trial Edition)” [ 9 ] issued by the National Health Commission and the State Administration of Traditional Chinese Medicine. (2) Data collection is complete. This study was reviewed by the Science Ethics Committee of Guangzhou University (Guangda Scientific Ethics [2023] No. 100). Informed consent from participants was waived by the Science Ethics Committee of Guangzhou University because of the retrospective nature and anonymous information of the study. Information including sex, date of onset and antigen negative conversion, symptoms, previous vaccination doses, health observation location (school health station or home health observation), and whether there was a history of SARS-CoV-2 infection was collected. Antigen samples and tests were conducted by trained doctors or nurses for students with fever when they first visited the doctor. Students who tested positive for antigens needed to stay at the school health station or go home for health observation. Antigen-positive students who stay at health stations were tested daily by doctors or nurses after their body temperature is normal, and students who were under home health observation would be tested for antigen sampling and testing under the online guidance of medical staff. If the antigen was negative twice in a row, and the interval between the two tests was more than 24 hours, it was allowed to be released from health observation. The time of the patient's antigen negative conversion was calculated by subtracting the date of symptom onset from the date of the first negative antigen conversion. The COVID-19 antigen used in this study was produced by Guangzhou Wondfo Biotech CO., LTD, with a colloidal gold test. SPSS 20.0 software was used for statistical analysis. Numerical data are expressed as n (%), and the chi-square test was used to compare differences between groups. The normally distributed data are expressed as the means ± standard deviations (x ± s), and a t-test was used to compare the differences between groups. Results A total of 255 febrile college students who were positive for the COVID-19 antigen test were included in the study, with an average age of 20.89 ± 1.93 years, including 126 males (49.4%) and 129 females (50.6%). 197 cases (77.3%) were observed at school health stations, and 58 cases (22.7%) were observed at home. 169 (66.3%) patients were infected with SARS-CoV-2 for the first time, whereas the other 86 (33.7%) were infected with the virus for the second time. Four (1.6%) students received one dose of the COVID-19 vaccine, 37 (14.5%) received two doses, 199 patients (78.0%) received three doses, and 15 patients (5.9%) received four doses of COVID-19 vaccine. The characteristics of the patients included in this study are listed in Table 1 . Table 1 Characteristics of the included patients Cases, n(%) Gender Male 126(49.4%) Female 129(50.6%) Health observation location University 197(77.3%) At home 58(22.7%) Number of COVID-19 infections Once 169(66.3%) Twice 86(33.7%) Doses of the COVID-19 vaccine 1 4(1.6%) 2 37(14.5%) 3 199(78.0%) 4 15(5.9%) The antigen negative time of all the antigen-positive students was 5.64 ± 1.83 days. The presence or absence of a history of SARS-CoV-2 infection and the number of symptoms are factors influencing the antigen conversion time. The average antigen conversion time was 6.12 ± 1.83 days for the students who were infected with SARS-CoV-2 for the first time, and 4.70 ± 1.43 days for the patients who were infected for the second time, with a statistically significant difference (P < 0.001). In patients with more than 3 symptoms except fever, the average antigen conversion time was 6.21 ± 1.92 days, which was significantly greater than that in patients with 0–1 or 2–3 symptoms (P = 0.038). There was no statistically significant difference in the effects of sex, health observation location or vaccination dose on the time of antigen conversion to negative (P > 0.05). The results of the antigen conversion time are presented in Table 2 . Table 2 Analysis of factors influencing antigen conversion time cases Turning negative time(d) F value P value Gender Male 126 5.66 ± 1.89 0.028 0.867 Female 129 5.62 ± 1.78 Observation location University 197 5.63 ± 1.66 0.025 0.875 At home 58 5.67 ± 2.34 Doses of vaccine 1 4 7.25 ± 2.87 1.390 0.246 2 37 5.54 ± 2.31 3 199 5.59 ± 1.69 4 15 6.07 ± 1.94 Number of COVID-19 infections Once 169 6.12 ± 1.83 39.556 < 0.001* Twice 86 4.70 ± 1.43 Number of symptoms 0–1 99 5.54 ± 1.79 3.305 0.038* 2–3 104 5.45 ± 1.78 More than 3 52 6.21 ± 1.92 Discussion COVID-19 has spread worldwide since the end of 2019, and new variants are constantly emerging. Although many people have already been infected with the virus and have been vaccinated, there are still individual repeat infections and spikes in infections in some countries or regions due to continuous mutation of the virus and a decrease in antibody titers over time [ 10 ] . SARS-CoV-2 can spread rapidly on campuses, especially when new variants emerge, and outbreaks on campuses can spread rapidly to the surrounding community [ 11 ] . Unlike universities in Western countries, the vast majority of students in Chinese universities live on campus rather than outside the campus, and the density of dormitories in Chinese universities is relatively high. As a result, the spread of COVID-19 on Chinese university campuses is likely to affect many people. It is necessary to understand the characteristics of COVID-19 patients on Chinese campuses. In this study, we found that number of times of SARS-CoV-2 infections was significantly associated with the conversion time of the COVID-19 antigen, whereas sex, health observation location and vaccination dose had no statistically significant effect on the conversion time. One study in the United States reported that the average nucleic acid conversion time was 7.2 (6.8, 7.5) days for the first infection and 4.9 (4.5, 5.3) days for the second infection [ 8 ] . These two numbers are longer than those in this study, which may be caused by the lower sensitivity of the antigen test taken by the patients in this study, and might not have the power to diagnose SARS-CoV-2 infection in the very early and later phases of COVID-19 [ 12 ] . The viral load in patients with first-time infection is also significantly greater than that in second-time-infected patients [ 8 ] . At present, there is a lack of relevant studies on the number of infections and the time of antigen conversion in China. A Korean study of 89 COVID-19 patients revealed that asymptomatic COVID-19 patients experienced a significantly faster decline in viral load than symptomatic patients did. The median duration from symptom onset to negative conversion for genomic RNA detection was 6 days in the asymptomatic group and 9 days in the symptomatic group [ 13 ] . Two other studies have shown that symptomatic COVID-19 patients are more contagious than asymptomatic patients are [ 14 , 15 ] . These findings suggest that there may be a correlation between the severity of symptoms and the viral load in COVID-19 patients. However, there are no studies on the relationship between the number of symptoms and the number of days on which the antigen test results turn negative. More research may be needed to clarify the relationship between symptoms and viral loads and the time to negative conversion. There is no consensus on the relationship between vaccines and the clear timing of SARS-CoV-2 infection. Some studies have shown that vaccination reduces the risk of delta variant infection and accelerates viral clearance [ 16 ] . However, some studies take a different view. For example, one study suggested that booster vaccination led to lower antibody titers and longer clearance times for BA.1-infected patients. Boosted individuals may reflect a less effective immune response, which increases infection risk and reduces the viral RNA clearance rate [ 17 ] . The results of this study revealed that there was no significant association between the number of COVID-19 vaccine doses and the time to negative COVID-19 antigen results. More research is needed on the relationship between viral kinetics and vaccination of Omicron infection to further clarify the relationship between vaccines and the time to viral clearance. This study has certain limitations. First, we included a group of college students, aged 17–30 years. More research is needed in other age groups. Second, owing to the conditions of the university hospital, we are unable to perform viral titer tests for patients to learn more. However, this study still reveals the characteristics of the antigen negativity time and influencing factors of SARS-CoV-2 infection in Chinese college students and reveals that the duration of a positive COVID-19 test may have an impact on isolation policies, testing recommendations and clinical guidelines. Abbreviations COVID-19 Corona Virus Disease 2019 SARS-COV-2 Severe acute respiratory syndrome coronavirus 2 Declarations Acknowledgements Not applicable. Authors ’ contributions Z-P.Y. designed the study, lead data analysis and substantively revised the manuscript. W-J.L and Y.J. contributed to data analysis and manuscript drafting equally. Y-Y.W., Z-N.X and Y.X. contributed to data acquisition and analysis. Z-H.D and J-M.X. contributed to data acquisition and manuscript editing. All authors read and approved the final manuscript. Funding This work did not receive any funding. Availability of data and material The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was reviewed by the Science Ethics Committee of Guangzhou University (Guangda Scientific Ethics 2023 No. 100). Informed consent from participants were waived by Science Ethics Committee of Guangzhou University due to the retrospective nature and anonymous information of the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Chen JJ, Li LB, Peng HH, et al. Neutralization against XBB.1 and XBB.1.5 after omicron subvariants breakthrough infection or reinfection[J]. Lancet Reg Health West Pac. 2023, 33: 100759. Klaassen F, Chitwood MH, Cohen T, et al. Changes in population immunity against infection and severe disease from SARS-CoV-2 Omicron variants in the United States between December 2021 and November 2022[J]. medRxiv. 2022. Tian T, Yang C, Long X, et al. The Long-Term Impacts of COVID-19 on Physical and Psychological Health - Beijing Municipality, China, December 2022-April 2023[J]. China CDC Wkly. 2023, 5(40): 894-899. Liu H, Xu X, Deng X, et al. Counterfactual analysis of the 2023 Omicron XBB wave in China[J]. Infect Dis Model. 2024, 9(1): 195-203. Menegale F, Manica M, Zardini A, et al. Evaluation of Waning of SARS-CoV-2 Vaccine-Induced Immunity: A Systematic Review and Meta-analysis[J]. JAMA Netw Open. 2023, 6(5): e2310650. Miyauchi S, Hiyama T, Nakano Y, et al. Is a booster dose of COVID-19 vaccines effective on newly dominant omicron subvariants among university students? Comparison between BA.1 and BA.2 dominancy[J]. Am J Infect Control. 2023, 51(8): 907-911. Ministry of Education of the People's Republic of China. http://www.moe.gov.cn/srcsite/A17/moe_943/s3285/202303/t20230313_1050708.html. Accessed 27 Feb 2023. Kissler S M, Hay JA, Fauver JR, et al. Viral kinetics of sequential SARS-CoV-2 infections[J]. Nat Commun. 2023, 14(1): 6206. National Health Comission of the People's Republic of China. http://www.nhc.gov.cn/xcs/zhengcwj/202301/32de5b2ff9bf4eaa88e75bdf7223a65a.shtml. Accessed 5 Jan 2023. Forni G, Mantovani A. COVID-19 vaccines: where we stand and challenges ahead[J]. Cell Death Differ. 2021, 28(2): 626-639. White LF, Murray EJ, Chakravarty A. The role of schools in driving SARS-CoV-2 transmission: Not just an open-and-shut case[J]. Cell Rep Med. 2022, 3(3): 100556. Corman VM, Haage VC, Bleicker T, et al. Comparison of seven commercial SARS-CoV-2 rapid point-of-care antigen tests: a single-centre laboratory evaluation study[J]. Lancet Microbe. 2021, 2(7): e311-e319. Bae S, Kim JY, Lim SY, et al. Dynamics of Viral Shedding and Symptoms in Patients with Asymptomatic or Mild COVID-19[J]. Viruses. 2021, 13(11). Li F, Li YY, Liu MJ, et al. Household transmission of SARS-CoV-2 and risk factors for susceptibility and infectivity in Wuhan: a retrospective observational study[J]. Lancet Infect Dis. 2021, 21(5): 617-628. Bender JK, Brandl M, Höhle M, et al. Analysis of Asymptomatic and Presymptomatic Transmission in SARS-CoV-2 Outbreak, Germany, 2020[J]. Emerg Infect Dis. 2021, 27(4): 1159-1163. Singanayagam A, Hakki S, Dunning J, et al. Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study[J]. Lancet Infect Dis. 2022, 22(2): 183-195. Hay JA, Kissler SM, Fauver JR, et al. Quantifying the impact of immune history and variant on SARS-CoV-2 viral kinetics and infection rebound: A retrospective cohort study[J]. Elife. 2022, 11. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2024 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 29 Oct, 2024 Reviews received at journal 23 Sep, 2024 Reviewers agreed at journal 23 Sep, 2024 Reviewers agreed at journal 18 Sep, 2024 Reviews received at journal 16 Sep, 2024 Reviewers agreed at journal 05 Sep, 2024 Reviewers invited by journal 03 Sep, 2024 Editor invited by journal 06 Aug, 2024 Editor assigned by journal 05 Aug, 2024 Submission checks completed at journal 05 Aug, 2024 First submitted to journal 03 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4853644","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":345679017,"identity":"5fe9cd86-ece0-43df-a47e-ed948ea6991f","order_by":0,"name":"Wen-Jin Liu","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wen-Jin","middleName":"","lastName":"Liu","suffix":""},{"id":345679018,"identity":"44474fc5-c8f1-473b-b1b3-ffdb3761648b","order_by":1,"name":"You Jin","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"You","middleName":"","lastName":"Jin","suffix":""},{"id":345679019,"identity":"cb7ebf6d-673d-47d2-b9f5-ccaed24e3679","order_by":2,"name":"Yong-Yan Wu","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yong-Yan","middleName":"","lastName":"Wu","suffix":""},{"id":345679020,"identity":"b1e940a0-e519-48b8-817f-6351c0ecebad","order_by":3,"name":"Zhen-Ni Xiao","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zhen-Ni","middleName":"","lastName":"Xiao","suffix":""},{"id":345679021,"identity":"7c3a02b1-6a6b-4d6c-a0dd-6770af49ea3e","order_by":4,"name":"Yan Xu","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Xu","suffix":""},{"id":345679022,"identity":"dbb461a9-793c-464b-a8a5-2de028338476","order_by":5,"name":"Zhao-Hong Du","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zhao-Hong","middleName":"","lastName":"Du","suffix":""},{"id":345679023,"identity":"6db1932b-84e9-42e7-8c6f-3d58aeafdaf4","order_by":6,"name":"Jian-Mei Xiao","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Jian-Mei","middleName":"","lastName":"Xiao","suffix":""},{"id":345679024,"identity":"b41c0bfd-fd16-45c3-b58e-cec349f3a205","order_by":7,"name":"Zhi-Peng Yan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYBACfvb2Awc+/KhhZmNvIFKLZM+ZxIcze46x8/McIFKLwYwEY2MeNmZ+yRkJxGqRSEiTnMHDJm1w8/HGGww1NtEEtZjzPDwm8cFCxtjgdlqxBcOxtNwGQlos2yG2JBvczjGTYGw4TFiLwYEEM2mgX+o33DxDrJYTEO8zA60iUgsskJn5eYB+SSDGL0hReXjjjQ81NoS1oDhSIoEU5RAtpOoYBaNgFIyCkQEAMZ1A3FlmwWgAAAAASUVORK5CYII=","orcid":"","institution":"Guangzhou University","correspondingAuthor":true,"prefix":"","firstName":"Zhi-Peng","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2024-08-03 13:59:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4853644/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4853644/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-024-10346-8","type":"published","date":"2024-12-18T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":72201677,"identity":"4261ac43-3c6b-4698-a3b7-25e9dacbac38","added_by":"auto","created_at":"2024-12-23 16:09:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":355187,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4853644/v1/529d8905-ed62-4e7d-a0ba-6888c8e2eb0f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing factors of COVID-19 antigen conversion time in a Chinese university students: a retrospective analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has spread throughout almost all parts of the world for more than four years, causing hundreds of millions of infections and many people to be reinfected due to mutation of SARS-CoV-2, especially the Omicron strain, which could break through the protection afforded by previous infection and vaccination\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. As of November 9, 2022, it is estimated that 94% of people in the United States have had at least one infection and that 65% have had at least two infections\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAfter the Chinese government announced that it would no longer implement a dynamic zero COVID-19 policy on 7 December 2022, in the two-month period of December 2022 and January 2023, the BF.7 strain spread rapidly in China. For example, in Beijing, by January 31, 2023, the cumulative infection rate had reached 92.3%\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Like many other countries around the world, another wave of SARS-CoV-2 infections peaked in China in April 2023, during which time it was estimated that as many as 860\u0026nbsp;million people were infected with the XBB strain, accounting for 61% of China's total population\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, as immune protection from previous infections or vaccinations would wane significantly within a few months\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eColleges and universities are susceptible to COVID-19 outbreaks. A study in Japan suggested that even in the context of previous infection and vaccination, the proportion of university students who are repeatedly infected with the SARS-CoV-2 is at least 45%\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Unlike in European countries or the United States, the vast majority of university students in China live in on-campus dormitories rather than off-campus dormitories. In addition, most of the dormitories in Chinese universities are occupied by four or more students. As a result, Chinese universities are more susceptible to the spread of the SARS-CoV-2. Therefore, in the technical plan for the prevention and control of SARS-CoV-2 infection in colleges and universities jointly issued by the Ministry of Education and other departments of China, it is proposed that students with mild SARS-CoV-2 infection on campuses should be cared for and treated at the health stations of colleges and universities or at home\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, and cannot live in the original dormitory until the COVID-19 antigen becomes negative.\u003c/p\u003e \u003cp\u003eDuring the peak of SARS-CoV-2 infection in China from April to June 2023, an increasing number of people were infected with the virus, and a significant number of them were infected for the second time. However, it is not entirely clear how several factors, such as previous SARS-CoV-2 infection, affect the recovery time of patients with COVID-19. Previous studies in the United States have shown that the duration of secondary infection is shorter than that of the first infection\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, but there are no such studies in China. Here, we retrospectively analyzed the influencing factors of antigen conversion time in college students at one university with SARS-CoV-2 infection to help with the management of COVID-19.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA retrospective analysis was performed on a total of 255 college students who were febrile and tested positive for the COVID-19 antigen in the outpatient department of a university in Guangzhou, a city located in southern China, from April to June 2023. The inclusion criteria were as follows: (1) meeting the diagnostic criteria of the \u0026ldquo;Diagnosis and Treatment Plan for COVID-19 ( the Tenth Trial Edition)\u0026rdquo;\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e issued by the National Health Commission and the State Administration of Traditional Chinese Medicine. (2) Data collection is complete. This study was reviewed by the Science Ethics Committee of Guangzhou University (Guangda Scientific Ethics [2023] No. 100). Informed consent from participants was waived by the Science Ethics Committee of Guangzhou University because of the retrospective nature and anonymous information of the study.\u003c/p\u003e \u003cp\u003eInformation including sex, date of onset and antigen negative conversion, symptoms, previous vaccination doses, health observation location (school health station or home health observation), and whether there was a history of SARS-CoV-2 infection was collected. Antigen samples and tests were conducted by trained doctors or nurses for students with fever when they first visited the doctor. Students who tested positive for antigens needed to stay at the school health station or go home for health observation. Antigen-positive students who stay at health stations were tested daily by doctors or nurses after their body temperature is normal, and students who were under home health observation would be tested for antigen sampling and testing under the online guidance of medical staff. If the antigen was negative twice in a row, and the interval between the two tests was more than 24 hours, it was allowed to be released from health observation. The time of the patient's antigen negative conversion was calculated by subtracting the date of symptom onset from the date of the first negative antigen conversion. The COVID-19 antigen used in this study was produced by Guangzhou Wondfo Biotech CO., LTD, with a colloidal gold test.\u003c/p\u003e \u003cp\u003eSPSS 20.0 software was used for statistical analysis. Numerical data are expressed as n (%), and the chi-square test was used to compare differences between groups. The normally distributed data are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (x\u0026thinsp;\u0026plusmn;\u0026thinsp;s), and a t-test was used to compare the differences between groups.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 255 febrile college students who were positive for the COVID-19 antigen test were included in the study, with an average age of 20.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93 years, including 126 males (49.4%) and 129 females (50.6%). 197 cases (77.3%) were observed at school health stations, and 58 cases (22.7%) were observed at home. 169 (66.3%) patients were infected with SARS-CoV-2 for the first time, whereas the other 86 (33.7%) were infected with the virus for the second time. Four (1.6%) students received one dose of the COVID-19 vaccine, 37 (14.5%) received two doses, 199 patients (78.0%) received three doses, and 15 patients (5.9%) received four doses of COVID-19 vaccine. The characteristics of the patients included in this study are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the included patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases, \u003cem\u003en(%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126(49.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129(50.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth observation location\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197(77.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58(22.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNumber of COVID-19 infections\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169(66.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86(33.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDoses of the COVID-19 vaccine\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(14.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199(78.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe antigen negative time of all the antigen-positive students was 5.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83 days. The presence or absence of a history of SARS-CoV-2 infection and the number of symptoms are factors influencing the antigen conversion time. The average antigen conversion time was 6.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83 days for the students who were infected with SARS-CoV-2 for the first time, and 4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43 days for the patients who were infected for the second time, with a statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In patients with more than 3 symptoms except fever, the average antigen conversion time was 6.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92 days, which was significantly greater than that in patients with 0\u0026ndash;1 or 2\u0026ndash;3 symptoms (P\u0026thinsp;=\u0026thinsp;0.038). There was no statistically significant difference in the effects of sex, health observation location or vaccination dose on the time of antigen conversion to negative (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The results of the antigen conversion time are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of factors influencing antigen conversion time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurning negative time(d)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eF value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDoses of vaccine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of COVID-19 infections\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e39.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCOVID-19 has spread worldwide since the end of 2019, and new variants are constantly emerging. Although many people have already been infected with the virus and have been vaccinated, there are still individual repeat infections and spikes in infections in some countries or regions due to continuous mutation of the virus and a decrease in antibody titers over time\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. SARS-CoV-2 can spread rapidly on campuses, especially when new variants emerge, and outbreaks on campuses can spread rapidly to the surrounding community\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Unlike universities in Western countries, the vast majority of students in Chinese universities live on campus rather than outside the campus, and the density of dormitories in Chinese universities is relatively high. As a result, the spread of COVID-19 on Chinese university campuses is likely to affect many people. It is necessary to understand the characteristics of COVID-19 patients on Chinese campuses.\u003c/p\u003e \u003cp\u003eIn this study, we found that number of times of SARS-CoV-2 infections was significantly associated with the conversion time of the COVID-19 antigen, whereas sex, health observation location and vaccination dose had no statistically significant effect on the conversion time. One study in the United States reported that the average nucleic acid conversion time was 7.2 (6.8, 7.5) days for the first infection and 4.9 (4.5, 5.3) days for the second infection\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. These two numbers are longer than those in this study, which may be caused by the lower sensitivity of the antigen test taken by the patients in this study, and might not have the power to diagnose SARS-CoV-2 infection in the very early and later phases of COVID-19\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The viral load in patients with first-time infection is also significantly greater than that in second-time-infected patients\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. At present, there is a lack of relevant studies on the number of infections and the time of antigen conversion in China.\u003c/p\u003e \u003cp\u003eA Korean study of 89 COVID-19 patients revealed that asymptomatic COVID-19 patients experienced a significantly faster decline in viral load than symptomatic patients did. The median duration from symptom onset to negative conversion for genomic RNA detection was 6 days in the asymptomatic group and 9 days in the symptomatic group\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Two other studies have shown that symptomatic COVID-19 patients are more contagious than asymptomatic patients are\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. These findings suggest that there may be a correlation between the severity of symptoms and the viral load in COVID-19 patients. However, there are no studies on the relationship between the number of symptoms and the number of days on which the antigen test results turn negative. More research may be needed to clarify the relationship between symptoms and viral loads and the time to negative conversion.\u003c/p\u003e \u003cp\u003eThere is no consensus on the relationship between vaccines and the clear timing of SARS-CoV-2 infection. Some studies have shown that vaccination reduces the risk of delta variant infection and accelerates viral clearance\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. However, some studies take a different view. For example, one study suggested that booster vaccination led to lower antibody titers and longer clearance times for BA.1-infected patients. Boosted individuals may reflect a less effective immune response, which increases infection risk and reduces the viral RNA clearance rate\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. The results of this study revealed that there was no significant association between the number of COVID-19 vaccine doses and the time to negative COVID-19 antigen results. More research is needed on the relationship between viral kinetics and vaccination of Omicron infection to further clarify the relationship between vaccines and the time to viral clearance.\u003c/p\u003e \u003cp\u003eThis study has certain limitations. First, we included a group of college students, aged 17\u0026ndash;30 years. More research is needed in other age groups. Second, owing to the conditions of the university hospital, we are unable to perform viral titer tests for patients to learn more. However, this study still reveals the characteristics of the antigen negativity time and influencing factors of SARS-CoV-2 infection in Chinese college students and reveals that the duration of a positive COVID-19 test may have an impact on isolation policies, testing recommendations and clinical guidelines.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCOVID-19 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Corona Virus Disease 2019\u003c/p\u003e\n\u003cp\u003eSARS-COV-2 \u0026nbsp; \u0026nbsp; Severe acute respiratory syndrome coronavirus 2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ-P.Y. designed the study, lead data analysis and substantively revised the manuscript. W-J.L and Y.J. contributed to data analysis and manuscript drafting equally. Y-Y.W., Z-N.X and Y.X. contributed to data acquisition and analysis. Z-H.D and J-M.X. contributed to data acquisition and manuscript editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work did not receive any funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed by the Science Ethics Committee of Guangzhou University (Guangda Scientific Ethics 2023 No. 100). Informed consent from participants were waived by Science Ethics Committee of Guangzhou University due to the retrospective nature and anonymous information of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen JJ, Li LB, Peng HH, et al. Neutralization against XBB.1 and XBB.1.5 after omicron subvariants breakthrough infection or reinfection[J]. Lancet Reg Health West Pac. 2023, 33: 100759.\u003c/li\u003e\n\u003cli\u003eKlaassen F, Chitwood MH, Cohen T, et al. Changes in population immunity against infection and severe disease from SARS-CoV-2 Omicron variants in the United States between December 2021 and November 2022[J]. medRxiv. 2022.\u003c/li\u003e\n\u003cli\u003eTian T, Yang C, Long X, et al. The Long-Term Impacts of COVID-19 on Physical and Psychological Health - Beijing Municipality, China, December 2022-April 2023[J]. China CDC Wkly. 2023, 5(40): 894-899.\u003c/li\u003e\n\u003cli\u003eLiu H, Xu X, Deng X, et al. Counterfactual analysis of the 2023 Omicron XBB wave in China[J]. Infect Dis Model. 2024, 9(1): 195-203.\u003c/li\u003e\n\u003cli\u003eMenegale F, Manica M, Zardini A, et al. Evaluation of Waning of SARS-CoV-2 Vaccine-Induced Immunity: A Systematic Review and Meta-analysis[J]. JAMA Netw Open. 2023, 6(5): e2310650.\u003c/li\u003e\n\u003cli\u003eMiyauchi S, Hiyama T, Nakano Y, et al. Is a booster dose of COVID-19 vaccines effective on newly dominant omicron subvariants among university students? Comparison between BA.1 and BA.2 dominancy[J]. Am J Infect Control. 2023, 51(8): 907-911.\u003c/li\u003e\n\u003cli\u003eMinistry of Education of the People\u0026apos;s Republic of China. http://www.moe.gov.cn/srcsite/A17/moe_943/s3285/202303/t20230313_1050708.html. Accessed 27 Feb 2023.\u003c/li\u003e\n\u003cli\u003eKissler S M, Hay JA, Fauver JR, et al. Viral kinetics of sequential SARS-CoV-2 infections[J]. Nat Commun. 2023, 14(1): 6206.\u003c/li\u003e\n\u003cli\u003eNational Health Comission of the People\u0026apos;s Republic of China. http://www.nhc.gov.cn/xcs/zhengcwj/202301/32de5b2ff9bf4eaa88e75bdf7223a65a.shtml. Accessed 5 Jan 2023.\u003c/li\u003e\n\u003cli\u003eForni G, Mantovani A. COVID-19 vaccines: where we stand and challenges ahead[J]. Cell Death Differ. 2021, 28(2): 626-639.\u003c/li\u003e\n\u003cli\u003eWhite LF, Murray EJ, Chakravarty A. The role of schools in driving SARS-CoV-2 transmission: Not just an open-and-shut case[J]. Cell Rep Med. 2022, 3(3): 100556.\u003c/li\u003e\n\u003cli\u003eCorman VM, Haage VC, Bleicker T, et al. Comparison of seven commercial SARS-CoV-2 rapid point-of-care antigen tests: a single-centre laboratory evaluation study[J]. Lancet Microbe. 2021, 2(7): e311-e319.\u003c/li\u003e\n\u003cli\u003eBae S, Kim JY, Lim SY, et al. Dynamics of Viral Shedding and Symptoms in Patients with Asymptomatic or Mild COVID-19[J]. Viruses. 2021, 13(11).\u003c/li\u003e\n\u003cli\u003eLi F, Li YY, Liu MJ, et al. Household transmission of SARS-CoV-2 and risk factors for susceptibility and infectivity in Wuhan: a retrospective observational study[J]. Lancet Infect Dis. 2021, 21(5): 617-628.\u003c/li\u003e\n\u003cli\u003eBender JK, Brandl M, H\u0026ouml;hle M, et al. Analysis of Asymptomatic and Presymptomatic Transmission in SARS-CoV-2 Outbreak, Germany, 2020[J]. Emerg Infect Dis. 2021, 27(4): 1159-1163.\u003c/li\u003e\n\u003cli\u003eSinganayagam A, Hakki S, Dunning J, et al. Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study[J]. Lancet Infect Dis. 2022, 22(2): 183-195.\u003c/li\u003e\n\u003cli\u003eHay JA, Kissler SM, Fauver JR, et al. Quantifying the impact of immune history and variant on SARS-CoV-2 viral kinetics and infection rebound: A retrospective cohort study[J]. Elife. 2022, 11.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Time of antigen negative conversion, University student, Retrospective study","lastPublishedDoi":"10.21203/rs.3.rs-4853644/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4853644/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSARS-CoV-2 can cause repeated infections. China also experienced a peak of COVID-19 after the Chinese government changed its COVID-19 policy in December 2022. However, little is known about the factors, such as history of previous infection and vaccine dose, whether affect the time antigen test result to turn negative for SARS-CoV-2. Boarding colleges and universities are prone to outbreaks and repeated infections caused by COVID-19. Therefore, we investigated the factors influencing the time of COVID-19 antigen conversion at one university from April to June 2023.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study included college students from one university in Guangzhou who were positive for the COVID-19 antigen, and collected information such as sex, previous COVID-19 infection history, vaccination dose, symptom onset date, and antigen negative conversion date for retrospective analysis. Chi-square tests or t-tests were used to compare differences between groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 255 college students were included. The average antigen conversion time of patients with first infection was 6.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83 days, and that of patients with second infection was 4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43 days. The difference was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The average antigen conversion time was 6.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92 days in patients with more than 3 symptoms except fever, which was significantly greater than that in patients with 0\u0026ndash;1 (5.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79 days)or 2\u0026ndash;3 symptoms(5.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78 days)(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was no significant difference in antigen conversion time according to sex, health observation location or vaccination dose (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn college students, a history of SARS-CoV-2 infection and the number of symptoms are the influencing factors of the antigen negativity.\u003c/p\u003e","manuscriptTitle":"Influencing factors of COVID-19 antigen conversion time in a Chinese university students: a retrospective analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-30 08:52:25","doi":"10.21203/rs.3.rs-4853644/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-29T18:41:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-23T20:19:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16820015089389506486450020916634380100","date":"2024-09-23T20:13:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"97782825013340188252680629829813244010","date":"2024-09-18T13:28:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-16T15:58:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183234040767135698165640891466002840700","date":"2024-09-05T14:02:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-03T13:51:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-08-06T05:16:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-05T23:08:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-05T23:07:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2024-08-03T13:58:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"085a532f-b1bc-4a0d-a703-64b38e45dddd","owner":[],"postedDate":"August 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:00:28+00:00","versionOfRecord":{"articleIdentity":"rs-4853644","link":"https://doi.org/10.1186/s12879-024-10346-8","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2024-12-18 15:57:11","publishedOnDateReadable":"December 18th, 2024"},"versionCreatedAt":"2024-08-30 08:52:25","video":"","vorDoi":"10.1186/s12879-024-10346-8","vorDoiUrl":"https://doi.org/10.1186/s12879-024-10346-8","workflowStages":[]},"version":"v1","identity":"rs-4853644","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4853644","identity":"rs-4853644","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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