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

Estimating the true mortality burden of COVID-19 for every country in the world is a difficult, but crucial, public health endeavor. Attributing deaths, direct or indirect, to COVID-19 is problematic. A more attainable target is the "excess deaths," the number of deaths in a particular period, relative to that expected during "normal times," and we develop a model for this endeavor. The excess mortality requires two numbers, the total deaths and the expected deaths, but the former is unavailable for many countries, and so modeling is required for such countries. The expected deaths are based on historic data, and we develop a model for producing estimates of these deaths for all countries. We allow for uncertainty in the modeled expected numbers when calculating the excess. The methods we describe were used to produce the World Health Organization (WHO) excess death estimates. To achieve both interpretability and transparency we developed a relatively simple overdispersed Poisson count framework within which the various data types can be modeled. We use data from countries with national monthly data to build a predictive log-linear regression model with time-varying coefficients for countries without data. For a number of countries, subnational data only are available, and we construct a multinomial model for such data, based on the assumption that the fractions of deaths in subregions remain approximately constant over time. Our inferential approach is Bayesian, with the covariate predictive model being implemented in the fast and accurate INLA software. The subnational modeling was carried out using MCMC in Stan. Based on our modeling, the point estimate for global excess mortality during 2020-2021 is 14.8 million, with a 95% credible interval of (13.2, 16.6) million.

Estimating global and country-specific excess mortality during the Covid-19 pandemic

Introduction The infection-fatality rate (IFR) of COVID-19 has been carefully measured and analyzed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries. Indeed, it has been suggested that the death rate in developing countries may be far lower than in high-income countries—an outcome that would be starkly different from the typical pattern for many other infectious diseases. Methods We systematically reviewed the literature to identify all serology studies in developing countries that were conducted using representative samples of specimens collected by early 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 analyzed 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 Seroprevalence in many developing country locations was markedly higher than in high-income countries but still far short of herd immunity. In most locations, seroprevalence among older adults was similar to that of younger age-groups. Age-specific IFRs were 1.3-2.5x higher than in high-income countries. The median value of population IFR was 0.5% among developing countries with satisfactory death reporting as of 2016, compared to a median of 0.05% for other developing countries. 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 accelerate the provision of vaccine doses to vulnerable populations in developing countries. Key Points ‐Age-specific prevalence and infection fatality rate (IFR) of COVID-19 for developing countries has not been well assessed. ‐Seroprevalence in developing countries (as measured by antibodies against SARS-CoV-2) is markedly higher than in high-income countries but still far short of herd immunity. ‐Seroprevalence among older adults is broadly similar to that of younger age-groups. ‐Age-specific IFRs in developing countries are roughly twice those of high-income countries. ‐Population IFR in developing countries with satisfactory death reporting (based on UN/WHO data as of 2016) is ten times higher than in other developing countries. ‐These results underscore the urgency of disseminating vaccines to vulnerable people in developing countries.

/pdf/assessing-the-burden-of-covid-19-in-developing-countries-18v13gmana.pdf

Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications

Abstract We conducted 3 successive seroprevalence surveys, 3 months apart, using multistage cluster sampling to measure the extent and dynamics of the severe acute respiratory syndrome coronavirus 2 epidemic in Conakry, the capital city of Guinea. Seroprevalence increased from 17.3% (95% CI, 12.4%–23.8%) in December 2020 during the first survey (S1) to 28.9% (95% CI, 25.6%–32.4%) in March/April 2021 (S2), then to 42.4% (95% CI, 39.5%–45.3%) in June 2021 (S3). This significant overall trend of increasing seroprevalence (P < .0001) was also significant in every age class, illustrating a sustained transmission within the whole community. These data may contribute to defining cost-effective response strategies.

https://academic.oup.com/ofid/article-pdf/9/5/ofac152/43471952/ofac152.pdf

High and Rapid Increase in Seroprevalence for SARS-CoV-2 in Conakry, Guinea: Results From 3 Successive Cross-Sectional Surveys (ANRS COV16-ARIACOV)

Recent evidence suggests that women in high-income countries desired to delay or forgo childbearing due to COVID-19, yet there remains insufficient evidence of COVID-19's impact on fertility desires in low- and middle-income countries, particularly in sub-Saharan Africa (SSA). We examined how quantum and tempo of fertility intentions changed in the first year of COVID-19 and assessed the impact of economic insecurity and sociodemographic characteristics on these changes in SSA. We used longitudinal data collected among 14,053 women from Kenya, Burkina Faso, two provinces in the Democratic Republic of Congo (Kinshasa and Kongo Central), and two states in Nigeria (Kano and Lagos). Descriptive analyses and logistic regression examined overall changes and economic and sociodemographic factors associated with quantum and tempo shifts. At the population-level, most women remained stable in their fertility intentions throughout the first year of COVID-19. Despite widespread income loss, few women reported that COVID-19 influenced their near-term childbearing intentions. However, among women who changed their intentions in Burkina Faso and Kenya, income loss was associated with transitions toward wanting to delay or limit childbearing, particularly among the poorest women. These findings underscore the importance of accounting for context when anticipating the consequences of public health emergencies on fertility. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/padr.12543

Change in Fertility Intentions in the First Year of COVID‐19: Evidence from Four Countries in Sub‐Saharan Africa

Summary Background Even after adjusting for the expected lower severity due to the younger age of the population, relatively low SARS-CoV-2 incidence and mortality rates have been reported throughout Africa. For investigating whether this is truly the case, we conducted a survey to estimate the COVID-19 related mortality and cumulative incidence of SARS-CoV-2 infections in Omdurman the most populated city of the tripartite metropolis Khartoum in Sudan. Methods A retrospective, cross–sectional, mortality and seroprevalence survey was conducted in Omdurman, Sudan, from March 1, until April 10 2021. A two–stage cluster sampling method was used to investigate the death rate for the pre–pandemic (January 1, 2019–February 29, 2020) and pandemic (March 1, 2020 – day of the survey) period using questionnaires. The seroprevalence survey was performed in a subset of households and all consenting members were tested with a rapid serological test (SD–Biosensor) and a subgroup additionally with ELISA (EUROIMMUN). Fisher’s exact test was used to assess differences between the pre–and pandemic periods and a random effect and Bayesian latent class model to adjust for test performance. Findings Data from 27315 people (3716 households) for the entire recall period showed a 67% (95% CI 32–110) increase in death rate between the pre–pandemic (0.12 deaths/10000 people/day [95% CI 0.10–0.14]) and pandemic (0.20 [0.16–0.23]) periods. Notably, a 74% (30–133) increase in death was observed among people aged ≥50 years. The adjusted seroprevalence of SARS-CoV-2 was 54.6% (95% CI 51.4–57.8). The seroprevalence was significantly associated with age, increasing up to 80.7% (71.7–89.7) for the oldest age group (≥50 years). Interpretation Our results showed a significant elevated mortality for the pandemic period with a considerable excess mortality in Omdurman, Sudan. The overall high seroprevalence indicated a different age pattern compared to other countries, with a significant increase by age. Funding Medecins Sans Frontieres

https://medrxiv.org/content/10.1101/2021.08.22.21262294v1.full.pdf

Wendelin Moser

Papers

Retrospective mortality and prevalence of SARS-CoV-2 antibodies in greater Omdurman, Sudan: a population-based cross-sectional survey