A hierarchical Bayesian model for estimating age-specific COVID-19 infection fatality rates in developing countries (preprint)

The COVID-19 infection fatality rate (IFR) is the proportion of individuals infected with SARS-CoV-2 who subsequently die. As COVID-19 disproportionately affects older individuals, age-specific IFR estimates are imperative to facilitate comparisons of the impact of COVID-19 between locations and prioritize distribution of scare resources. However, there lacks a coherent method to synthesize available data to create estimates of IFR and seroprevalence that vary continuously with age and adequately reflect uncertainties inherent in the underlying data. In this paper we introduce a novel Bayesian hierarchical model to estimate IFR as a continuous function of age that acknowledges heterogeneity in population age structure across locations and accounts for uncertainty in the estimates due to seroprevalence sampling variability and the imperfect serology test assays. Our approach simultaneously models test assay characteristic, serology, and death data, where the serology and death data are often available only for binned age groups. Information is shared across locations through hierarchical modeling to improve estimation of the parameters with limited data. Modeling data from 26 developing country locations during the first year of the COVID-19 pandemic, we found seroprevalence did not change dramatically with age, and the IFR at age 60 was above the high-income country benchmark for most locations.

Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modeling study (preprint)

We performed a systematic review and meta-analysis of SARS-CoV-2 serology studies to estimate time-dependent sensitivity for a large set of serological assays. We find that seroreversion depends strongly on the antigen and the analytic technique of the assay. We estimate the average time-varying sensitivity for different types of assays, as defined by their technical characteristics, which can be used to approximate the sensitivity of out-of-sample assays. We find large variability between types of assays, with assays of certain characteristics (nucleocapsid antigen, lateral flow assay) having an average of 20% sensitivity at 6 months, while others (receptor-binding domain antigen, sandwich design) have 98% sensitivity. Importantly, we estimate that almost a third of included assays depart significantly from manufacturer specified sensitivity after 6 months. Our analysis outlines the importance of monitoring the seroreversion of serological tests, and provides a tool for researchers to account for this phenomenon.

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

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. Methods We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using population representative samples 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. In most locations, 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 2x 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 accelerate the provision of vaccine doses to populations in developing countries. Key Points - Age-stratified infection fatality rates (IFRs) of COVID-19 in developing countries are about twice those of high-income countries. - Seroprevalence (as measured by antibodies against SARS-CoV-2) is broadly similar across age cohorts, underscoring the challenges of protecting older age groups in developing countries. - Population IFR in developing countries is similar to that of high-income countries, because differences in population age structure are roughly offset by disparities in healthcare access as well as elevated infection rates among older age cohorts. - These results underscore the urgency of disseminating vaccines throughout the developing world.

Assessing the Age Specificity of Infection Fatality Rates for COVID-19: Systematic Review, Meta-Analysis, and Public Policy Implications (preprint)

Objective: Determine age-specific infection fatality rates for COVID-19 to inform public health policies and communications that help protect vulnerable age groups.Methods: Studies of COVID-19 prevalence were collected by conducting an online search of published articles, preprints, and government reports. A total of 89 studies were reviewed in depth and screened. Studies of 31 locations satisfied the inclusion criteria and were included in the meta-analysis. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities four weeks after the midpoint date of the study, reflecting typical lags in fatalities and reporting. Meta-regression procedures in Stata were used to analyze IFR by age.Results: Our analysis finds a exponential relationship between age and IFR for COVID-19. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.5% at age 75, and 15% at age 85. We find that differences in the age structure of the population and the age-specific prevalence of COVID-19 explain 90% of the geographical variation in population IFR.Discussion: These results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate is two orders of magnitude greater than the annualized risk of a fatal automobile accident and far more dangerous than seasonal influenza. Moreover, the overall IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to mitigate infections in older adults could substantially decrease total deaths.Funding Statement: No funding was received for conducting this study.Declaration of Interests: The authors have no financial interests nor any other conflicts of interest related to this study.

ASSESSING THE AGE SPECIFICITY OF INFECTION FATALITY RATES FOR COVID-19: META-ANALYSIS & PUBLIC POLICY IMPLICATIONS (preprint)

Structured AbstractO_ST_ABSObjectiveC_ST_ABSDetermine age-specific infection fatality rates for COVID-19 to inform public health policies and communications that help protect vulnerable age groups. MethodsStudies of COVID-19 prevalence were collected by conducting an online search of published articles, preprints, and government reports. A total of 111 studies were reviewed in depth and screened. Studies of 33 locations satisfied the inclusion criteria and were included in the meta-analysis. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities four weeks after the midpoint date of the study, reflecting typical lags in fatalities and reporting. Meta-regression procedures in Stata were used to analyze IFR by age. ResultsOur analysis finds a exponential relationship between age and IFR for COVID-19. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.2% at age 75, and 14% at age 85. We find that differences in the age structure of the population and the age-specific prevalence of COVID-19 explain nearly 90% of the geographical variation in population IFR. DiscussionThese results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate is two orders of magnitude greater than the annualized risk of a fatal automobile accident and far more dangerous than seasonal influenza. Moreover, the overall IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to mitigate infections in older adults could substantially decrease total deaths.