Data from: Serosurvey of SARS-COV-2 at a large public university
Data files
Jul 12, 2023 version files 157.24 KB
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Hou_et_al_SSI_RawData.xlsx
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README.md
Abstract
Objective: This study investigated the seroprevalence of SARS-CoV-2 antibodies among adults over 18 years.
Design: Prospective cohort study.
Settings: a population-based study among the big university community.
Participants: This study took volunteers over five days and recruited adult 1064 participants.
Primary outcome measures: We conducted a seroprevalence in our community with SARS-CoV-2-specific antibodies due to previous exposure to SARS-CoV-2 and/or vaccination.
Results: The seroprevalence of the anti-receptor binding domain (RBD) antibody was 90% by a lateral flow assay and 88% by a semi-quantitative chemiluminescent immunoassay. The seroprevalence for anti-nucleocapsid (NC) was 20%. In addition, individuals with previous natural COVID infection plus vaccination had higher anti-RBD antibody levels compared to those who had vaccination only or infection only. Individuals who had a breakthrough infection had the highest anti-RBD antibody levels.
Conclusion: Accurate estimates of the cumulative incidence of SARS-CoV-2 infection can inform the development of university risk mitigation protocols such as encouraging booster shots, extending mask mandates, or reverting to online classes. It could help us to have clear guidance to act at the first sign of the next surge as well, especially since there is a surge of COVID subvariant infections.
Methods
This is a survey and lab data. Survey data is exported from Qualtrics and lab experimental data is added separately. Additional information regarding the methodology will be published in BMJ Open.
All demographic information and assay results were provided via Excel files. Any participant under the age of 18, those who did not provide a biological sample, or those with non-unique sample IDs were removed from the study. Assay information was first merged together by a sample ID and those in common were kept in the study (inner join). The combined assay data was then merged with the demographic information. Those who provided biological samples but no demographic information were removed from the study (left join). Finally, we performed data cleaning in order to fix input mistakes (e.g. spelling, wrong dates, etc.) and group responses in the appropriate categories. We also generated new variables based on the information received from participants, such as calculating the participant’s last vaccination date, if applicable, or whether a participant completed their vaccination cycle.
Usage notes
Empty cells in the data file represent data not available in the study due to failure to report by the study participant.