Seroprevalence and characteristics of Coronavirus Disease (COVID-19) in workers with non-specific disease symptoms
- PMID: 35596145
- PMCID: PMC9120800
- DOI: 10.1186/s12879-022-07461-9
Seroprevalence and characteristics of Coronavirus Disease (COVID-19) in workers with non-specific disease symptoms
Abstract
Background: The population-based serosurveys are essential for estimating Coronavirus Disease-19 (COVID-19) burden and monitoring the progression of this pandemic. We aimed to assess the seroprevalence of SARS-CoV-2 antibodies and potential predictors of seropositivity in the Pakistani population.
Methodology: This population-based seroprevalence study includes consenting subjects from the workplaces (factories, corporates, restaurants, media houses, schools, banks, and hospitals) located in the urban areas of Karachi, Lahore, Multan, Peshawar, and Quetta. We analyzed each subject's serum sample for SARS-CoV-2-IgM and/or IgG antibodies using UNIPER IgG/IgM Rapid COVID-19 Testing Kit. The subject's demographics, exposure history, and symptoms experienced (in last 7 days) were also obtained. The collected data was analyzed using SPSS version 22.0.
Results: The overall seroprevalence of SARS-CoV-2 antibodies was 16.0% (2810/17,764). The total antibody seropositivity was higher in males than females (OR 1.22, 95% CI 1.110-1.340). The symptomatic subjects had 2.18 times higher odds of IgG seropositivity while 1.2 times for IgM seropositivity than the asymptomatic subjects. The multivariable logistic regression model showed that the odds of SARS-CoV-2 total antibody seroprevalence were affected by the number of dependents (OR = 1.077; 95% CI 1.054-1.099), apparent symptomology (OR = 1.288; 95% CI 1.011-1.643), close unprotected contact with a confirmed or probable case of COVID-19 (OR 2.470; 95% CI 2.164-2.819), traveling history (last 14 days) (OR = 1.537; 95% CI 1.234-1.914) and proximity with someone who traveled (OR = 1.534; 95% CI 1.241-1.896).
Conclusion: We found a reasonable seroprevalence of SARS-CoV-2 antibodies in the studied population. Several factors like the number of dependents, apparent symptoms, close unprotected contact with a confirmed or probable case of COVID-19, traveling history, and proximity with someone who traveled are associated with increased odds of SARS-CoV-2 antibody seropositivity.
Keywords: COVID-19; IgG; IgM; Potential Predictors; Risk Factors; SARS-CoV-2; Seroprevalence.
© 2022. The Author(s).
Conflict of interest statement
The author(s) declare no competing interest.
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- World Health Organization (WHO). https://covid19.who.int/. Accessed 7 Jan 2022.
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