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. 2022 May 20;22(1):481.
doi: 10.1186/s12879-022-07461-9.

Seroprevalence and characteristics of Coronavirus Disease (COVID-19) in workers with non-specific disease symptoms

Affiliations

Seroprevalence and characteristics of Coronavirus Disease (COVID-19) in workers with non-specific disease symptoms

Wajiha Javed et al. BMC Infect Dis. .

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.

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Conflict of interest statement

The author(s) declare no competing interest.

Figures

Fig. 1
Fig. 1
Symptom profile of the study subjects

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References

    1. Chang L, Hou W, Zhao L, Zhang Y, Wang Y, Wu L. The prevalence of antibodies to SARS-CoV-2 among blood donors in China. MedRxiv. 2020 doi: 10.1101/2020.07.13.20153106v1. - DOI - PMC - PubMed
    1. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8(4):420–422. doi: 10.1016/S2213-2600(20)30076-X. - DOI - PMC - PubMed
    1. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan. China JAMA. 2020;323(11):1061–1069. doi: 10.1001/jama.2020.1585. - DOI - PMC - PubMed
    1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y. Clinical features of patients infected with 2019 novel coronavirus in Wuhan. China Lancet. 2020;395(10223):497–506. doi: 10.1016/S0140-6736(20)30183-5. - DOI - PMC - PubMed
    1. World Health Organization (WHO). https://covid19.who.int/. Accessed 7 Jan 2022.