Infection Fatality Ratios for COVID-19 Among Noninstitutionalized Persons 12 and Older: Results of a Random-Sample Prevalence StudyFREE
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Background: Because many cases of coronavirus disease 2019 (COVID-19) are asymptomatic, generalizable data on the true number of persons infected are lacking. Mortality rates therefore are calculated from confirmed cases, which overestimates the infection fatality ratio (IFR). To calculate a true IFR, population prevalence data are needed from large geographic areas where reliable death data also exist. Most previous IFR estimates came from non-U.S. populations, including a cruise ship, or were calculated by using simulation techniques (1–3). Previous estimates also are not age specific, are relatively ungeneralizable, and are unsuitable for making clinical or policy decisions.
Objective: To estimate IFRs among noninstitutionalized (that is, community-dwelling) populations by age, race, ethnicity, and sex by using the first U.S. statewide random-sample study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence.
Methods and Findings: We combined prevalence estimates from a statewide random sample with Indiana vital statistics data of confirmed COVID-19 deaths (4). In brief, our stratified random sample consisted of state residents aged 12 years and older. Known decedents and incarcerated persons were excluded. Because nursing homes were limiting residents' ability to leave and re-enter the facilities, their participation was unlikely. Participants were tested from 25 April to 29 April 2020 for active viral infection and SARS-CoV-2 antibodies, which would indicate prior infection. Demographic information was collected.
We accounted for nonresponse by weighting prevalence estimates for age, race (dichotomized as White or non-White), and Hispanic ethnicity to reflect state demographics. Estimated prevalence included all current and past infections with bootstrapped 95% CIs. The prevalence of each demographic stratum was multiplied by the stratum-specific state population estimate to determine the number of cumulative infections by group.
We calculated the IFR by age, race, sex, and ethnicity on the basis of the cumulative number of confirmed COVID-19 deaths as of 29 April 2020, divided by the number of infections. Although nursing home residents were not tested, they represented 54.9% of Indiana's deaths. Thus, we excluded nursing home residents from all calculations (that is, deaths and infections). To account for all infections, we added the number of patients hospitalized with COVID-19 during the testing period and noninstitutionalized COVID-19 deaths into the denominator.
As of 29 April 2020, Indiana had recorded 1099 COVID-19 deaths, 495 of which occurred in noninstitutionalized persons. Our random-sample study estimated 187 802 cumulative infections, to which 180 hospitalizations were added. The average age among all COVID-19 decedents was 76.9 years (SD, 13.1). The overall noninstitutionalized IFR was 0.26%. In order of magnitude, the demographic-stratified IFR varied most by age, race, ethnicity, and sex (Table). Persons younger than 40 years had an IFR of 0.01%; those aged 60 or older had an IFR of 1.71%. Whites had an IFR of 0.18%; non-Whites had an IFR of 0.59%.
Discussion: By using SARS-CoV-2 population prevalence data, we found that the risk for death among infected persons increased with age. Indiana's IFR for noninstitutionalized persons older than 60 years is just below 2% (1 in 50). In comparison, the ratio is approximately 2.5 times greater than the estimated IFR for seasonal influenza, 0.8% (1 in 125), among those aged 65 years and older (5). Of note, the IFR for non-Whites is more than 3 times that for Whites, despite COVID-19 decedents in that group being 5.6 years younger on average.
We are unaware of any similar IFR estimates by demographic group but recognize several limitations of our analysis. First, despite random selection and weighting for nonresponse, the potential for response bias remains. Second, imperfections in tests have the potential for false-positives, which may bias estimated infections upward. Separately, use of confirmed COVID-19 deaths may undercount the true number of deaths; both issues might result in lower IFRs. Third, because children and non–state tax filers were excluded, our estimates may lack generalizability to persons who were not studied. Fourth, we could not account for disease severity among random-sample participants with positive test results. Although participants represented persons with less severe illness, some with positive test results may have later died of COVID-19, resulting in a potential underestimation of the IFR. However, accounting for right-censoring bias also might overestimate the IFR, because we cannot distinguish deaths among persons we randomly tested from those among patients who were hospitalized during the testing period. Race and ethnicity data for confirmed COVID-19 deaths may have been inaccurate, thus biasing these IFR estimates. Lastly, IFR is a population-based measure and should be interpreted cautiously as a measure of individual risk.
References
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Park M, Cook AR, Lim JT, et al. A systematic review of COVID-19 epidemiology based on current evidence. J Clin Med. 2020;9. [PMID: 32244365] doi: 10.3390/jcm9040967
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Russell TW, Hellewell J, Jarvis CI, et al. Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020. Euro Surveill. 2020;25. [PMID: 32234121] doi: 10.2807/1560-7917.ES.2020.25.12.2000256
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Basu A. Estimating the infection fatality rate among symptomatic COVID-19 cases in the United States. Health Aff (Millwood). 2020;39:1229-1236. [PMID: 32379502] doi: 10.1377/hlthaff.2020.00455
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Menachemi N, Yiannoutsos CT, Dixon BE, et al. Population point prevalence of SARS-CoV-2 infection based on a statewide random sample - Indiana, April 25-29, 2020. MMWR Morb Mortal Wkly Rep. 2020;69:960-964. [PMID: 32701938] doi: 10.15585/mmwr.mm6929e1
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Centers for Disease Control and Prevention. Estimated influenza illnesses, medical visits, hospitalizations, and deaths in the United States—2018–2019 influenza season. Accessed at www.cdc.gov/flu/about/burden/2018-2019.html on 4 June 2020.
Information & Authors
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Published In
Annals of Internal Medicine
Volume 174 • Number 1 • January 2021
Pages: 135 - 136
History
Published online: 2 September 2020
Published in issue: January 2021
Keywords
- COVID-19
- Health care
- Health care facilities
- Hospital medicine
- Hospitalizations
- Hospitals
- Infectious diseases
- Medical ethics, humanities, and education
- Nursing homes
- Population statistics
- Prevention, policy, and public health
- Public policy
- Pulmonary diseases
- Racial and ethnic issues
- Research and reporting methods
- Respiratory infections
- Science policy
- Statistical data
- Statistical methods
- Upper respiratory tract infections
- Vital statistics
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© 2020 American College of Physicians.
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Infection Fatality Ratios for COVID-19 Among Noninstitutionalized Persons 12 and Older: Results of a Random-Sample Prevalence Study. Ann Intern Med.2021;174:135-136. [Epub 2 September 2020]. doi:10.7326/M20-5352
Infection Fatality Ratios for COVID-19 Among Noninstitutionalized Persons 12 and Older: Results of a Random-Sample Prevalence Study. Ann Intern Med.2021;174:135-136. [Epub 2 September 2020]. doi:10.7326/M20-5352
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Multivariate model.
It would be nice to see an additional column in the table that adjust of the other factors, for example what was the IFR in men and women after adjusting for age and race and other covariates.
Comparison with influenza
So, how does the Covid-19 IFR compare with influenza IFR?
Mortality comparisons between COVID-19 and seasonal influenza
It is important to understand the virulence of SARS-CoV-2, a commonly examined parameter being its lethality as compared to seasonal influenza. Blackburn et al. have reported an infection fatality ratio among community-living adults of 0.26% (1). If institutionalized adults had been included the ratio would inevitably be higher, likely approximating the 0.6% mortality rate among exposed individuals that can be calculated by combining official death tolls, the known 30% undercount (2), and an CDC study that found 10 times as many people have been exposed to the novel coronavirus than are reported as cases (3).
Among the elderly, Blackburn et al. estimated the case-fatality rate at 2.5 times the rate provided by the CDC for seasonal influenza. This is likely to be the takehome message for many readers and commentators, and therefore deserves careful attention. For two reasons, I believe this relatively low ratio is an underestimate.
First, the CDC estimates its case-fatality rates on the basis of all Americans, whereas Blackburn et al. examined only those dwelling in the community. Inclusion of institutionalized individuals would increase Blackburn’s figures, and in the case of the elderly would likely increase them considerably.
Second, it is not always recognized that the seasonal influenza case fatality rates reported by the CDC, including the 0.1% overall rate, are for symptomatic cases. Their denominators are estimated by using the reported number of influenza hospitalizations to guess the burden of clinical illness (4). But antibody studies (5) show, unsurprisingly, that most people infected with influenza never develop symptoms – between 65% and 85%, somewhat more than for SARS-CoV-2. The 0.6% mortality rate I have calculated for SARS-CoV-2-exposed individuals is 6 times higher than the 0.1% usually cited for seasonal influenza. But given the overestimation of commonly accepted influenza mortality rates due to failure to take asymptomatic infections into account, SARS-CoV-2 can be seen to be not 6 times, or 2.5 times, but at least 10 times as lethal as seasonal flu.
1. Blackburn J, Yiannoutsos CT, Carroll AE, et al. Infection Fatality Ratios for COVID-19 Among Noninstitutionalized Persons 12 and Older: Results of a Random-Sample Prevalence Study. Ann Int Med. Published online Sept 2, 2020 www.acpjournals.org/doi/10.7326/M20-5352
2. Weinberger DM, Chen J, Cohen T, et al. Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020. JAMA Intern Med. Published online July 01, 2020. doi:10.1001/jamainternmed.2020.3391
3. Havers FP, Reed C, Lim T, et al. Seroprevalence of Antibodies to SARS-CoV-2 in 10 Sites in the United States, March 23-May 12, 2020. JAMA Intern Med. Published online July 21, 2020. doi:10.1001/jamainternmed.2020.4130.
4. How CDC Estimates the Burden of Seasonal Influenza in the U.S., https://www.cdc.gov/flu/about/burden/how-cdc-estimates.htm [accessed September 4, 2020]
5. Leung NH, Xu C, Ip DK, Cowling BJ. Review Article: The Fraction of Influenza Virus Infections That Are Asymptomatic: A Systematic Review and Meta-analysis. Epidemiology. 2015;26(6):862-872. doi:10.1097/EDE.0000000000000340
Flu comparison.
Flu comparisons are often made, and I have used them myself, but I think they are extremely problematic. Susan Levenstein clearly points this out. I've seen flu IFR estimates as low as 0.04%, and a number of researchers that suggest the often used 0.1% is just too high. Does the posted study differentiate flu IFR between institutionalised cases and the non-institutionalised cases?Forgive me if I missed that point. Of course, if the 200,000 or so deaths as reported so far, is accurate, a bad flu season of about 60,000 deaths (with very little mitigation), will be beaten by at least 4 times for the country. And those eastern states, New York, Massachusetts, New Jersey, have all surpassed expected Heart disease deaths (former leading cause of death).
RE: Mortality comparisons between COVID-19 and seasonal influenza
Thank you for your comment on our recently published research letter. We agree that the infection fatality ratio (IFR) is likely higher among institutionalized individuals, but as stated in our paper, we do not have data for this population that would allow for a calculation of the IFR. As such, we are unable to comment on the accuracy of the 0.6% mortality rate that you have calculated. The focus of our work was to calculate IFRs for SARS-CoV-2 infection stratified by demographic characteristics. We provided a comparison to the published CDC estimated IFR for influenza for context only. As pointed out by Leung et al,1 the rate of asymptomatic infections for influenza is difficult to measure and available estimates vary considerably. As a result, drawing definitive conclusions or making perfect "apples-to-apples" comparison challenging.
1. Leung NH, Xu C, Ip DK, Cowling BJ. Review Article: The Fraction of Influenza Virus Infections That Are Asymptomatic: A Systematic Review and Meta-analysis. Epidemiology. 2015;26(6):862-872. doi:10.1097/EDE.0000000000000340