Introduction The infection fatality rate (IFR) of COVID-19 has been carefully measured and analysed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries. Methods We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using representative samples collected by February 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analysed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible. Results In most locations in developing countries, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups. Age-specific IFRs were roughly 2 times higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure. Conclusion The burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to ensure medical equity to populations in developing countries through provision of vaccine doses and effective medications. 

https://gh.bmj.com/content/bmjgh/7/5/e008477.full.pdf

Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications

Summary Background All-cause excess mortality is a comprehensive measure of the combined direct and indirect effects of COVID-19 on mortality. Estimates are usually derived from Civil Registration and Vital Statistics (CRVS) systems, but these do not include non-registered deaths, which may be affected by changes in vital registration coverage over time. Methods Our analytical framework and empirical strategy account for registered mortality and under-registration. This provides a better estimate of the actual mortality impact of the first wave of the COVID-19 pandemic in Peru. We use population and crude mortality rate projections from Peru's National Institute of Statistics and Information (INEI, in Spanish), individual-level registered COVID-19 deaths from the Ministry of Health (MoH), and individual-level registered deaths by region and age since 2017 from the National Electronic Deaths Register (SINADEF, in Spanish). We develop a novel framework combining different estimates and using quasi-Poisson models to estimate total excess mortality across regions and age groups. Also, we use logistic mixed-effects models to estimate the coverage of the new SINADEF system. Findings We estimate that registered mortality underestimates national mortality by 37•1% (95% CI 23% - 48•5%) across 26 regions and nine age groups. We estimate total all-cause excess mortality during the period of analysis at 173,099 (95% CI 153,669 - 187,488) of which 108,943 (95% CI 96,507 - 118,261) were captured by the vital registration system. Deaths at age 60 and over accounted for 74•1% (95% CI 73•9% - 74•7%) of total excess deaths, and there were fewer deaths than expected in younger age groups. Lima region, on the Pacific coast and including the national capital, accounts for the highest share of excess deaths, 87,781 (95% CI 82,294 - 92,504), while in the opposite side regions of Apurimac and Huancavelica account for less than 300 excess deaths. Interpretation Estimating excess mortality in low- and middle-income countries (LMICs) such as Peru must take under-registration of mortality into account. Combining demographic trends with data from administrative registries reduces uncertainty and measurement errors. In countries like Peru, this is likely to produce significantly higher estimates of excess mortality than studies that do not take these effects into account. Funding None.

Estimation of all-cause excess mortality by age-specific mortality patterns for countries with incomplete vital statistics: a population-based study of the case of Peru during the first wave of the COVID-19 pandemic

Seroprevalence surveys provide estimates of the extent of SARS-CoV-2 infections in the population, regardless of disease severity and test availability. In Mexico in 2020, COVID-19 cases reached a maximum in July and December. We aimed to estimate the national and regional seroprevalence of SARS-CoV-2 antibodies across demographic and socioeconomic groups in Mexico after the first wave, from August to November 2020. We used nationally representative survey data including 9,640 blood samples. Seroprevalence was estimated by socioeconomic and demographic characteristics, adjusting by the sensitivity and specificity of the immunoassay test. The national seroprevalence of SARS-CoV-2 antibodies was 24.9% (95%CI 22.2, 26.7), being lower for adults 60 years and older. We found higher seroprevalence among urban and metropolitan areas, low socioeconomic status, low education and workers. Among seropositive people, 67.3% were asymptomatic. Social distancing, lockdown measures and vaccination programs need to consider that vulnerable groups are more exposed to the virus and unable to comply with lockdown measures. 

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Nationally representative SARS-CoV-2 antibody prevalence estimates after the first epidemic wave in Mexico

/pdf/nationally-representative-sars-cov-2-antibody-prevalence-2op4zk38.pdf

Worldwide, nations have struggled during the coronavirus disease 2019 (COVID‐19) pandemic. However, Latin America and the Caribbean faced an unmatched catastrophic toll. As of March 2022, the region has reported approximately 15% of cases and 28% of deaths worldwide. Considering the relatively late arrival of SARS‐CoV‐2, several factors in the region were determinants of the humanitarian crisis that ensued. Pandemic unpreparedness, fragile healthcare systems, forthright inequalities, and poor governmental support facilitated the spread of the virus throughout the region. Moreover, reliance on repurposed and ineffective drugs such as hydroxychloroquine and ivermectin—to treat or prevent COVID‐19—was publicised through misinformation and created a false sense of security and poor adherence to social distancing measures. While there were hopes that herd immunity could be achieved after the region's disastrous first peak, the emergence of the Gamma, Lambda, and Mu variants made this unattainable. This review explores how Latin America and the Caribbean fared during the first 2 years of the pandemic, and how, despite all the challenges, the region became a global leader in COVID‐19 vaccination, with 63% of its population fully vaccinated.

COVID‐19 in Latin America and the Caribbean: Two years of the pandemic

SARS-CoV-2 prevalence associated to low socioeconomic status and overcrowding in an LMIC megacity: A population-based seroepidemiological survey in Lima, Peru

Fany Cárdenas

Papers

SARS-CoV-2 prevalence associated to low socioeconomic status and overcrowding in an LMIC megacity: A population-based seroepidemiological survey in Lima, Peru