LAUSR

Objective To determine population-based estimates of coronavirus disease 2019 (COVID-19) in a densely populated urban community of Karachi, Pakistan. Methods Three cross-sectional surveys were conducted in April, June and August 2020 in low- and high-transmission neighbourhoods. Participants were selected at random to provide blood for Elecsys immunoassay for detection of anti-severe acute respiratory syndrome coronavirus-2 antibodies. A Bayesian regression model was used to estimate seroprevalence after adjusting for the demographic characteristics of each district. Results In total, 3005 participants from 623 households were enrolled in this study. In Phase 2, adjusted seroprevalence was estimated as 8.7% [95% confidence interval (CI) 5.1–13.1] and 15.1% (95% CI 9.4–21.7) in low- and high-transmission areas, respectively, compared with 0.2% (95% CI 0–0.7) and 0.4% (95% CI 0–1.3) in Phase 1. In Phase 3, it was 12.8% (95% CI 8.3–17.7) and 21.5% (95% CI 15.6–28) in low- and high-transmission areas, respectively. The conditional risk of infection was 0.31 (95% CI 0.16–0.47) and 0.41 (95% CI 0.28–0.52) in low- and high-transmission neighbourhoods, respectively, in Phase 2. Similar trends were observed in Phase 3. Only 5.4% of participants who tested positive for COVID-19 were symptomatic. The infection fatality rate was 1.66%, 0.37% and 0.26% in Phases 1, 2 and 3, respectively. Conclusion Continuing rounds of seroprevalence studies will help to improve understanding of secular trends and the extent of infection during the course of the pandemic.