Abstract
BackgroundWorldwide, Peru has one of the highest infection fatality rates of COVID-19, and its capital city, Lima, accumulates roughly 50% of diagnosed cases. Despite surveillance efforts to assess the extent of the pandemic, reported cases and deaths only capture a fraction of its impact due to COVID-19′s broad clinical spectrum. This study aimed to estimate the seroprevalence of SARS-CoV-2 in Lima, stratified by age, sex, region, socioeconomic status (SES), overcrowding, and symptoms.MethodsWe conducted a multi-stage, population-based serosurvey in Lima, between June 28th and July 9th, 2020, after 115 days of the index case and after the first peak cases. We collected whole blood samples by finger-prick and applied a structured questionnaire. A point-of-care rapid serological test assessed IgM and IgG antibodies against SARS-CoV-2. Seroprevalence estimates were adjusted by sampling weights and test performance. Additionally, we performed RT-PCR molecular assays to seronegatives and estimated the infection prevalence.FindingsWe enrolled 3212 participants from 797 households and 241 sample clusters from Lima in the analysis. The SARS-CoV-2 seroprevalence was 20·8% (95%CI 17·2–23·5), and the prevalence was 25·2% (95%CI 22·5–28·2). Seroprevalence was equally distributed by sex (aPR=0·96 [95%CI 0·85–1·09, p = 0·547]) and across all age groups, including ≥60 versus ≤11 years old (aPR=0·96 [95%CI 0·73–1·27, p = 0·783]). A gradual decrease in SES was associated with higher seroprevalence (aPR=3·41 [95%CI 1·90–6·12, p<0·001] in low SES). Also, a gradual increase in the overcrowding index was associated with higher seroprevalence (aPR=1·99 [95%CI 1·41–2·81, p<0·001] in the fourth quartile). Seroprevalence was also associated with contact with a suspected or confirmed COVID-19 case, whether a household member (48·9%, aPR=2·67 [95%CI 2·06–3·47, p<0·001]), other family members (27·3%, aPR=1·66 [95%CI 1·15–2·40, p = 0·008]) or a workmate (34·1%, aPR=2·26 [95%CI 1·53–3·35, p<0·001]). More than half of seropositive participants reported never having had symptoms (56·1%, 95% CI 49·7–62·3).InterpretationThis first estimate of SARS-CoV-2 seroprevalence in Lima shows an intense transmission scenario, despite the government's numerous interventions early established. Susceptibles across age groups show that physical distancing interventions must not be relaxed. SES and overcrowding households are associated with seroprevalence. This study highlights the importance of considering the existing social inequalities for implementing the response to control transmission in low- and middle-income countries.
Highlights
Research in contextEvidence before this studyWorldwide, Peru has one of the highest infection fatality rates of COVID-19, and its capital city, Lima, accumulates roughly 50% of diagnosed cases in the country
There are no published studies of seroprevalence of SARS-CoV-2 conducted in Lima or other regions of Peru
The overall SARS-CoV-2 seroprevalence in Lima was 20¢8%, representing approximately 2485,713 people who acquired the infection
Summary
Peru has one of the highest infection fatality rates of COVID-19, and its capital city, Lima, accumulates roughly 50% of diagnosed cases in the country. We searched PubMed, Scielo, and medRxiv preprint server for papers in any language, published from November 1st, 2019 onwards, for epidemiological studies of the prevalence of SARS-CoV-2 infection in Peru and other low-and middle-income countries (LMIC). There are no published studies of seroprevalence of SARS-CoV-2 conducted in Lima or other regions of Peru. Few populationbased studies on the prevalence of antibodies to SARS-CoV-2, conducted in LMIC, have been published. Peru has one of the highest infection fatality rates of COVID-19, and its capital city, Lima, accumulates roughly 50% of diagnosed cases. This study aimed to estimate the seroprevalence of SARS-CoV-2 in Lima, stratified by age, sex, region, socioeconomic status (SES), overcrowding, and symptoms. This study highlights the importance of considering the existing social inequalities for implementing the response to control transmission in low- and middle-income countries
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