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To determine population-based estimates of coronavirus disease 2019 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 hightransmission 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.

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Background Pakistan is among the first low- and middle-income countries affected by COVID-19 pandemic. Monitoring progress through serial sero-surveys, particularly at household level, in densely populated urban communities can provide insights in areas where testing is non-uniform. Methods Two serial cross-sectional household surveys were performed in April (phase 1) and June (phase 2) 2020 each in a low- (District Malir) and high-transmission (District East) area of Karachi, Pakistan. Household were selected using simple random sampling (Malir) and systematic random sampling (East). Individual participation rate from consented households was 82.3% (1000/1215 eligible) in phase 1 and 76.5% (1004/1312 eligible) in phase 2. All household members or their legal guardians answered questions related to symptoms of Covid-19 and provided blood for testing with commercial Elecsys Anti-SARS-CoV-2 immunoassay targeting combined IgG and IgM. Seroprevalence estimates were computed for each area and time point independently. Given correlation among household seropositivity values, a Bayesian regression model accounting for household membership, age and gender was used to estimate seroprevalence. These estimates by age and gender were then post-stratified to adjust for the demographic makeup of the respective district. The household conditional risk of infection was estimated for each district and its confidence interval were obtained using a non-parametric bootstrap of households. Findings Post-stratified seroprevalence was estimated to be 0.2% (95% CI 0-0.7) in low-and 0.4% (95% CI 0 - 1.3) in high-transmission areas in phase 1 and 8.7% (95% CI 5.1-13.1) in low- and 15.1% (95% CI 9.4 -21.7) in high-transmission areas in phase 2, with no consistent patterns between prevalence rates for males and females. Conditional risk of infection estimates (possible only for phase 2) were 0.31 (95% CI 0.16-0.47) in low- and 0.41(95% CI 0.28-0.52) in high-transmission areas. Of the 166 participants who tested positive, only 9(5.4%) gave a history of any symptoms. Interpretation A large increase in seroprevalence to SARS-CoV-2 infection is seen, even in areas where transmission is reported to be low. Mostly the population is still seronegative. A large majority of seropositives do not report any symptoms. The probability that an individual in a household is infected, given that another household member is infected is high in both the areas. These results emphasise the need to enhance surveillance activities of COVID-19 especially in low-transmission sites and provide insights to risks of household transmission in tightly knit neighbourhoods in urban LMIC settings.