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SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates in Qatar.

ABSTRACT: The SARS-CoV-2 pandemic resulted in considerable morbidity and mortality as well as severe economic and societal disruptions. Despite scientific progress, true infection severity, factoring both diagnosed and undiagnosed infections, remains poorly understood. This study aimed to estimate SARS-CoV-2 age-stratified and overall morbidity and mortality rates based on analysis of extensive epidemiological data for the pervasive epidemic in Qatar, a country where < 9% of the population are ≥ 50 years. We show that SARS-CoV-2 severity and fatality demonstrate a striking age dependence with low values for those aged < 50 years, but rapidly growing rates for those ≥ 50 years. Age dependence was particularly pronounced for infection criticality rate and infection fatality rate. With Qatar's young population, overall SARS-CoV-2 severity and fatality were not high with < 4 infections in every 1000 being severe or critical and < 2 in every 10,000 being fatal. Only 13 infections in every 1000 received any hospitalization in acute-care-unit beds and < 2 in every 1000 were hospitalized in intensive-care-unit beds. However, we show that these rates would have been much higher if Qatar's population had the demographic structure of Europe or the United States. Epidemic expansion in nations with young populations may lead to considerably lower disease burden than currently believed.

SUBMITTER: Seedat S

PROVIDER: S-EPMC8440606 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:INTRODUCTION:The SARS-CoV-2 pandemic has posed a real challenge to health systems. In Spain, the heterogeneous distribution of the virus infection and the different health strategies have conditioned the morbidity and fatality rate. The aim of this study was to analyse the lethality of the infection by sex and age range in the Autonomous Communities (AC) of Spain. MATERIAL AND METHODS:To perform the analysis, data were extracted from the Ministry of Health, Regional and Public Health Departments of the different AC. The infected population was estimated from the results of the ENE-COVID19 and the population registered on 1 January 2020 (INE) for the validity of the IgG antibody test with 80% sensitivity and 100% specificity. The case fatality rate (TL) (deaths/1000 estimated infected) by sex and age (<20years, 20-64 and ?65years) was calculated for each AC. The standardized case fatality ratio (REL) was calculated by the exact method (EPIDAT). RESULTS:The estimated prevalence of SARS-CoV-2 infection in Spain was 6% (range, 1.4% [Ceuta] -14.1% [Community of Madrid]). The TL in Spain was 9,6/1000, ranged per AC from 1/1000 in Melilla to 26.6/1000 in La Rioja, with no correlation between case fatality and prevalence of infection. The TL was higher in men (10.2/1000, ratio 1.17 with respect to women), except in Cataluña (ratio 0.92), and especially high in those over 64years of age in La Rioja (143.5/1000), Asturias (69.2/1000) and Basque Country (46.6/1000). Overall excess REL was found to be over 30% in La Rioja (2.91; 95%CI: 2.36-3.57), Asturias (1.51; 95%CI: 1.27-1.80), Basque Country (1.42; 95%CI: 1.31-1.54) and Extremadura (1.37; 95%CI: 1.20-1.57) and in those over 64 years in Madrid and the Canary Islands. CONCLUSIONS:SARs-CoV-2 virus infection has been very unevenly distributed in the different ACs, with notably differences in TL between ACs, particularly high in La Rioja, Asturias and the Basque Country. Is important to study the excess in TL the population over 64years of age in the ACs of Madrid and the Canary Islands.

Project description:ObjectiveThere has been much discussion and debate around the underreporting of COVID-19 infections and deaths in India. In this short report we first estimate the underreporting factor for infections from publicly available data released by the Indian Council of Medical Research on reported number of cases and national seroprevalence surveys. We then use a compartmental epidemiologic model to estimate the undetected number of infections and deaths, yielding estimates of the corresponding underreporting factors. We compare the serosurvey based ad hoc estimate of the infection fatality rate (IFR) with the model-based estimate. Since the first and second waves in India are intrinsically different in nature, we carry out this exercise in two periods: the first wave (April 1, 2020-January 31, 2021) and part of the second wave (February 1, 2021-May 15, 2021). The latest national seroprevalence estimate is from January 2021, and thus only relevant to our wave 1 calculations.ResultsBoth wave 1 and wave 2 estimates qualitatively show that there is a large degree of "covert infections" in India, with model-based estimated underreporting factor for infections as 11.11 (95% credible interval (CrI) 10.71-11.47) and for deaths as 3.56 (95% CrI 3.48-3.64) for wave 1. For wave 2, underreporting factor for infections escalate to 26.77 (95% CrI 24.26-28.81) and to 5.77 (95% CrI 5.34-6.15) for deaths. If we rely on only reported deaths, the IFR estimate is 0.13% for wave 1 and 0.03% for part of wave 2. Taking underreporting of deaths into account, the IFR estimate is 0.46% for wave 1 and 0.18% for wave 2 (till May 15). Combining waves 1 and 2, as of May 15, while India reported a total of nearly 25 million cases and 270 thousand deaths, the estimated number of infections and deaths stand at 491 million (36% of the population) and 1.21 million respectively, yielding an estimated (combined) infection fatality rate of 0.25%. There is considerable variation in these estimates across Indian states. Up to date seroprevalence studies and mortality data are needed to validate these model-based estimates.

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SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates in Qatar.

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