Variation in the COVID-19 infection–fatality ratio by age, time, and geography during the pre-vaccine era: a systematic analysis
PhD, R M Barber BS Reed J D Sorensen, Melinda Gates Foundation, J Stanton, T Gillespie, Ryan M Barber, PhD David M Pigott, Austin Carter, Cory N Spencer, PhD, R C Reiner Samuel M Ostroff Jr, Robert C Reiner Jr, Cristiana Abbafati, Christopher Adolph, PhD Adrien Allorant, PhD Joanne O Amlag, MPH Aleksandr Y Aravkin, Steven D Bachmeier, Bree L Bang-Jensen, Catherine Bisignano, Sabina S Bloom, Rachel Castellano, MS Emma Castro, BS, H Comfort MPH James K Collins, Haley Comfort, PhD, W J Xiaochen Dai, William James Dangel, Carolyn Dapper, Amanda Deen, Lucas Earl, Megan Erickson, Samuel B Ewald, PhD Alize J Ferrari, PhD, J J Frostad MPH, N Fullman MPH Abraham D Flaxman, Joseph Jon Frostad, Nancy Fullman, Amiran Gamkrelidze, PhD, G Guo MPH, J He MSc John R Giles, Gaorui Guo, Jiawei He, Monika Helak, MPH, B M Erin N Hulland, Bethany M Huntley, Maia Kereselidze, BSc, K E LeGrand MPH, E Linebarger BA Alice Lazzar-Atwood, Kate E Legrand, Akiaja Lindstrom, Emily Linebarger, Prof Rafael Lozano, Beatrice Magistro, Deborah Carvalho Malta, MD Johan Månsson, Mantilla Herrera, Fatima Marinho, Alemnesh H Mirkuzie, MS Ali H Mokdad, Lorenzo Monasta, Prof Mohsen Naghavi, Hasan Nassereldine, Shuhei Nomura, Christopher M Odell, Tesfaye Latera, Maja Olana, Spencer A Pasovic, Louise Pease, Grace Penberthy, Antonio Reinke, P Luiz, Damian Francesco Ribeiro, Aleksei Santomauro, Natia Sholokhov, Emma Elizabeth Skhvitaridze, Ruri Spurlock, Roman Syailendrawati, Anh Truc Topor-Madry, Theo Vo, Rebecca Vos, Ally Walcott, Stefanie Walker, Charles Shey Watson, Nahom Alemseged Wiysonge, Peng Worku, Simon I Zheng, Emmanuela Hay, Gakidou, J L Christopher, Murray, A Carter Mph, C N, Spencer Ba, MS, B L Bang-Jensen Ma, S S Bloom BA Bisignano Mph, Dangel Med, MS B Ewald, Helak Ba, Huntley Ba, PhD, H Nassereldine MD, C M Odell Mpp, Pasovic Med, BS S A Pease, MS L Penberthy, G Reinke, PhD, A Sholokhov MSc, E E Spurlock MPH F Santomauro, A T Vo BSc Syailendrawati Ma, Prof T Vos, Walker Ma, MS S Watson, PhD P Zheng, Prof E Gakidou
The Lancet, doi:10.1016/s0140-6736(21)02867-1
Background The infection-fatality ratio (IFR) is a metric that quantifies the likelihood of an individual dying once infected with a pathogen. Understanding the determinants of IFR variation for COVID-19, the disease caused by the SARS-CoV-2 virus, has direct implications for mitigation efforts with respect to clinical practice, non-pharmaceutical interventions, and the prioritisation of risk groups for targeted vaccine delivery. The IFR is also a crucial parameter in COVID-19 dynamic transmission models, providing a way to convert a population's mortality rate into an estimate of infections.
Methods We estimated age-specific and all-age IFR by matching seroprevalence surveys to total COVID-19 mortality rates in a population. The term total COVID-19 mortality refers to an estimate of the total number of deaths directly attributable to COVID-19. After applying exclusion criteria to 5131 seroprevalence surveys, the IFR analyses were informed by 2073 all-age surveys and 718 age-specific surveys (3012 age-specific observations). When seroprevalence was reported by age group, we split total COVID-19 mortality into corresponding age groups using a Bayesian hierarchical model to characterise the non-linear age pattern of reported deaths for a given location. To remove the impact of vaccines on the estimated IFR age pattern, we excluded age-specific observations of seroprevalence and deaths that occurred after vaccines were introduced in a location. We estimated age-specific IFR with a non-linear meta-regression and used the resulting age pattern to standardise all-age IFR observations to the global age distribution. All IFR observations were adjusted for baseline and waning antibody-test sensitivity. We then modelled age-standardised IFR as a function of time, geography, and an ensemble of 100 of the top-performing covariate sets. The covariates included seven clinical predictors (eg, age-standardised obesity prevalence) and two measures of health system performance. Final estimates for 190 countries and territories, as well as subnational locations in 11 countries and territories, were obtained by predicting age-standardised IFR conditional on covariates and reversing the age standardisation.
Findings We report IFR estimates for April 15, 2020, to January 1, 2021, the period before the introduction of vaccines and widespread evolution of variants. We found substantial heterogeneity in the IFR by age, location, and time. Agespecific IFR estimates form a J shape, with the lowest IFR occurring at age 7 years (0•0023%, 95% uncertainty interval [UI] 0•0015-0•0039) and increasing exponentially through ages 30 years (0•0573%, 0•0418-0•0870), 60 years (1•0035%, 0•7002-1•5727), and 90 years (20•3292%, 14•6888-28•9754). The countries with the highest IFR on July 15, 2020, were Portugal (2•085%, 0•946-4•395), Monaco (1•778%, 1•265-2•915), Japan (1•750%, 1•302-2•690), Spain (1•710%, 0•991-2•718), and Greece (1•637%, 1•155-2•678). All-age IFR varied by a factor..
Saint Vincent and the Grenadines
Contributors Individual author contributions to the study are divided into the following categories: managing the estimation or publication process; writing the first draft of the manuscript; primary responsibility for applying analytical methods to produce estimates; primary responsibility for seeking, cataloguing, extracting, or cleaning data; designing or coding figures and tables; providing data or crucial feedback on data sources; development of methods or computational machinery; providing critical feedback on methods or results; drafting the manuscript or revising it critically for important intellectual content; designing or coding figures and tables; and managing the overall research enterprise. Members of the core research team for this topic area had full access to the underlying data used to generate estimates presented in this paper. All other authors had access to, and reviewed, estimates as part of the research evaluation process, which includes additional stages of formal review. Individual author contributions are listed in appendix 1 (p 21).
Declaration of interests CA reports support for the present manuscript from the Benificus Foundation as funding support for the collection of data on state-level social-distancing policies in the USA. XD reports support for the present manuscript from the University of Washington through their employment at the Institute for Health Metrics and Evaluation. ADF reports stock or stock..
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