Seroprevalence of SARS-CoV-2 and risk factors in Bantul Regency, Yogyakarta, Indonesia
Ahmad, R. A.; Indriani, C.; Arisanti, R. R.; Nanda, R. O.; Mahendradhata, Y.; Wibawa, T.
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COVID-19 case counts in Indonesia inevitably underestimate the true cumulative incidence of infection due to limited barriers to testing accessibility and asymptomatic infections. Therefore, community-based serological data are essential for understanding the true prevalence of infections. This study aims to estimate the seroprevalence of SARS-CoV-2 infection and factors related to the seropositivity in Bantul Regency, Yogyakarta, Indonesia. A cross-sectional study involving 425 individuals in 40 clusters was conducted between March and April 2021. Participants were interviewed using an e-questionnaire developed in the Kobo toolbox to collect information on socio-demographic, COVID-19 suggestive symptoms, history of COVID-19 diagnosis and COVID-19 vaccination status. A venous blood sample was collected from each participant and tested for immunoglobulin G (Ig-G) SARS-CoV-2 antibody titers using the enzyme-linked immunosorbent assay (ELISA). Seroprevalence was 31.1% in the Bantul Regency: 34.2% in semi-urban and 29.9% in urban villages. However, there is no significant proportion difference between both areas. A significant difference was reported in the age group. Participants in the 55-64 age group demonstrated the highest seroprevalence (43.7%; p=0.00), with a higher risk compared to the other age group (aOR= 3.79; 95% CI, 1.46-9.85, p<0.05). Seroprevalence in the unvaccinated participants was 29.9%. Family clusters accounted for 10.6% of the total seropositive cases. No significant difference was observed between individual preventive actions and their mobility with seropositivity status. This study observed a discrepancy with COVID-19 confirmed cumulative incidence data reported in the same period (11 out of 1000 population), indicating silent transmission may have occurred within the community. Higher seroprevalence in semi-urban areas rather than urban areas suggests a gap in health services access. Surveillance improvement through testing, tracing, and treatment, particularly in areas with lower access to health services, are necessary, along with more robust implementations of health protocols.
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