A Bayesian estimate of the early COVID-19 infection fatality ratio in Brazil based on a random seroprevalence survey. 2021

Valerio Marra, and Miguel Quartin
Núcleo de Astrofísica e Cosmologia & Departamento de Física, Universidade Federal do Espírito Santo, Vitória, ES, Brazil.

BACKGROUND A number of estimates of the infection fatality ratio (IFR) of SARS-CoV-2 in different countries have been published. In Brazil, the fragile political situation, together with socioeconomic and ethnic diversity, could result in substantially different IFR estimates. METHODS We infer the IFR in Brazil in 2020 by combining three datasets. We compute the prevalence via the population-based seroprevalence survey, EPICOVID19-BR. For the fatalities we obtain the absolute number using the public Painel Coronavírus dataset and the age-relative number using the public SIVEP-Gripe dataset. The time delay between the development of antibodies and subsequent fatality is estimated via the SIVEP-Gripe dataset. We obtain the IFR for each survey stage and 27 federal states. We include the effect of fading IgG antibody levels by marginalizing over the test detectability time window. RESULTS We infer a country-wide average IFR (maximum posterior and 95% CI) of 1.03% (0.88-1.22%) and age-specific IFRs of 0.032% (0.023-0.041%) [< 30 years], 0.22% (0.18-0.27%) [30-49 years], 1.2% (1.0-1.5%) [50-69 years], and 3.0% (2.4-3.9%) [≥ 70 years]. We find that the fatality ratio in the country increased significantly at the end of June 2020, likely due to the increased strain on the health system. CONCLUSIONS Our IFR estimate is based on data and does not rely on extrapolating models. This estimate sets a baseline value with which future medications and treatment protocols may be confronted.

UI MeSH Term Description Entries
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D011795 Surveys and Questionnaires Collections of data obtained from voluntary subjects. The information usually takes the form of answers to questions, or suggestions. Community Survey,Nonrespondent,Questionnaire,Questionnaires,Respondent,Survey,Survey Method,Survey Methods,Surveys,Baseline Survey,Community Surveys,Methodology, Survey,Nonrespondents,Questionnaire Design,Randomized Response Technique,Repeated Rounds of Survey,Respondents,Survey Methodology,Baseline Surveys,Design, Questionnaire,Designs, Questionnaire,Methods, Survey,Questionnaire Designs,Questionnaires and Surveys,Randomized Response Techniques,Response Technique, Randomized,Response Techniques, Randomized,Survey, Baseline,Survey, Community,Surveys, Baseline,Surveys, Community,Techniques, Randomized Response
D001938 Brazil A country located on the eastern coast of South America, located between Colombia and Peru, that borders the Atlantic Ocean. It is bordered on the north by Venezuela, Guyana, Suriname, and French Guiana, on the south by Uruguay, and on the west by Argentina. The capital is Brasilia.
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000086382 COVID-19 A viral disorder generally characterized by high FEVER; COUGH; DYSPNEA; CHILLS; PERSISTENT TREMOR; MUSCLE PAIN; HEADACHE; SORE THROAT; a new loss of taste and/or smell (see AGEUSIA and ANOSMIA) and other symptoms of a VIRAL PNEUMONIA. In severe cases, a myriad of coagulopathy associated symptoms often correlating with COVID-19 severity is seen (e.g., BLOOD COAGULATION; THROMBOSIS; ACUTE RESPIRATORY DISTRESS SYNDROME; SEIZURES; HEART ATTACK; STROKE; multiple CEREBRAL INFARCTIONS; KIDNEY FAILURE; catastrophic ANTIPHOSPHOLIPID ANTIBODY SYNDROME and/or DISSEMINATED INTRAVASCULAR COAGULATION). In younger patients, rare inflammatory syndromes are sometimes associated with COVID-19 (e.g., atypical KAWASAKI SYNDROME; TOXIC SHOCK SYNDROME; pediatric multisystem inflammatory disease; and CYTOKINE STORM SYNDROME). A coronavirus, SARS-CoV-2, in the genus BETACORONAVIRUS is the causative agent. 2019 Novel Coronavirus Disease,2019 Novel Coronavirus Infection,2019-nCoV Disease,2019-nCoV Infection,COVID-19 Pandemic,COVID-19 Pandemics,COVID-19 Virus Disease,COVID-19 Virus Infection,Coronavirus Disease 2019,Coronavirus Disease-19,SARS Coronavirus 2 Infection,SARS-CoV-2 Infection,Severe Acute Respiratory Syndrome Coronavirus 2 Infection,COVID19,2019 nCoV Disease,2019 nCoV Infection,2019-nCoV Diseases,2019-nCoV Infections,COVID 19,COVID 19 Pandemic,COVID 19 Virus Disease,COVID 19 Virus Infection,COVID-19 Virus Diseases,COVID-19 Virus Infections,Coronavirus Disease 19,Disease 2019, Coronavirus,Disease, 2019-nCoV,Disease, COVID-19 Virus,Infection, 2019-nCoV,Infection, COVID-19 Virus,Infection, SARS-CoV-2,Pandemic, COVID-19,SARS CoV 2 Infection,SARS-CoV-2 Infections,Virus Disease, COVID-19,Virus Infection, COVID-19
D000086402 SARS-CoV-2 A species of BETACORONAVIRUS causing atypical respiratory disease (COVID-19) in humans. The organism was first identified in 2019 in Wuhan, China. The natural host is the Chinese intermediate horseshoe bat, RHINOLOPHUS affinis. 2019 Novel Coronavirus,COVID-19 Virus,COVID19 Virus,Coronavirus Disease 2019 Virus,SARS Coronavirus 2,SARS-CoV-2 Virus,Severe Acute Respiratory Syndrome Coronavirus 2,Wuhan Coronavirus,Wuhan Seafood Market Pneumonia Virus,2019-nCoV,2019 Novel Coronaviruses,COVID 19 Virus,COVID-19 Viruses,COVID19 Viruses,Coronavirus 2, SARS,Coronavirus, 2019 Novel,Coronavirus, Wuhan,Novel Coronavirus, 2019,SARS CoV 2 Virus,SARS-CoV-2 Viruses,Virus, COVID-19,Virus, COVID19,Virus, SARS-CoV-2,Viruses, COVID19
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D016036 Seroepidemiologic Studies EPIDEMIOLOGIC STUDIES based on the detection through serological testing of characteristic change in the serum level of specific ANTIBODIES. Latent subclinical infections and carrier states can thus be detected in addition to clinically overt cases. Seroprevalence,Seroepidemiologic Study,Seroepidemiological Study,Studies, Seroepidemiologic,Study, Seroepidemiologic,Seroepidemiological Studies,Seroprevalences,Studies, Seroepidemiological,Study, Seroepidemiological

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