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

Moser, Wendelin; Fahal, Mohammed Ahmed Hassan; Abualas, Elamin; Bedri, Shahinaz; Elsir, Mahgoub Taj; Mohamed, Mona Fateh El Rahman Omer; Mahmoud, Abdelhalim Babiker; Ahmad, Amna Ismail Ibrahim; Mohammed, Mohammed A.; Altalib, Sami; DafaAllah, Ola Adil; Hmed, Salahaldin Abdallah; Azman, Andrew S.; Ciglenečki, Iza; Gignoux, Etienne; González, Alan; Mwongera, Christine; Albela, Manuel

doi:10.1101/2021.08.22.21262294

Cited by 7 publications

(7 citation statements)

References 25 publications

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“…We briefly review preliminary evidence from researchers, journalists and various officials of significant excess mortality in many of the countries for which we have no ACM data. This includes, but is not limited to, evidence from Honduras (EFE, 2021), Haiti (DeGennaro et al, 2021), Pakistan (Kirmani et al, 2020), Tanzania (Parkinson, 2021), Bangladesh (Hanifi et al, 2021;Rahman et al, 2021a,b), Zambia (Mwananyanda et al, 2021;Hamukale et al, 2021), Syria (Watson et al, 2021), Yemen (Besson et al, 2021), Sudan (News, 2020;Moser et al, 2021) and Papua New Guinea (Jorari, 2021). Also, evidence from territories which are not member countries show significant excess that tracks reported COVID-19 deaths.…”

Section: Resultsmentioning

confidence: 99%

Estimating Global and Country-Specific Excess Mortality During the COVID-19 Pandemic

Knutson¹,

Aleshin-Guendel²,

Karlinsky³

et al. 2022

Preprint

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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 estimate this for all countries on a monthly time scale for 2020 and 2021. 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 these countries. The expected deaths are based on historic data and we develop a model for producing expected estimates for all countries and we allow for uncertainty in the modeled expected numbers when calculating the excess. We describe the methods that were developed 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 sub-regions 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 or in some non-standard data situations, using our own MCMC code. Based on our modeling, the point estimate for global excess mortality, over 2020-2021, is 14.9 million, with a 95% credible interval of (13.3, 16.6) million. This leads to a point estimate of the ratio of excess deaths to reported COVID-19 deaths of 2.75, which is a huge discrepancy.

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Section: Resultsmentioning

confidence: 99%

Estimating Global and Country-Specific Excess Mortality During the COVID-19 Pandemic

Knutson¹,

Aleshin-Guendel²,

Karlinsky³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Consequently, the impact on the healthcare system and society may be far greater than would be reflected in mortality rates alone. Focusing only on survival rates obscures the large number of deaths that occur when many people are infected,63 the relatively high fatality rate of COVID-19 in comparison to other diseases and other causes of death,64 and non-mortality harms of COVID-19, such as hospitalisation from serious disease 62. Future work should address these non-mortality harms, including long COVID-19.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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IntroductionThe 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.MethodsWe 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.ResultsIn 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.ConclusionThe 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.

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“…Consequently, the impact on the healthcare system and society may be far greater than would be reflected in mortality rates alone. Focusing only on survival rates obscures the large number of deaths that occur from non-COVID-19 when many people are infected (48), SARS-CoV-2’s relatively high fatality rate in comparison to other pathogens and other causes of death (49), and non-mortality harms of COVID-19, such hospitalization from serious disease (47). Future work should address these non-mortality harms, including Long COVID.…”

Section: Discussionmentioning

confidence: 99%

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

Owusu‐Boaitey

Pugh

Fosdick

et al. 2021

Preprint

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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.

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

Cited by 7 publications

References 25 publications

Estimating Global and Country-Specific Excess Mortality During the COVID-19 Pandemic

Estimating Global and Country-Specific Excess Mortality During the COVID-19 Pandemic

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

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

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