2020
DOI: 10.1016/j.ijid.2020.09.028
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Coronavirus disease 2019 population-based prevalence, risk factors, hospitalization, and fatality rates in southern Brazil

Abstract: Highlights Cross-sectional data from two household surveys were summarized using meta-analysis. Prevalence of infection was 3.40% overall and 2.26% in elders ≥60 years-old. Prevalence was 12.7 and 5.4 times higher among household contacts and meat-processing plant workers, respectively. COVID-19-related hospitalization rate and IFR were exponentially higher in elders. IFR ranged from 0.08% in adults aged 20 to 39 years… Show more

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Cited by 16 publications
(20 citation statements)
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“…The mortality rate among the hospitalized patients in this study (13.72%) was also significantly lower compared with reports in Brazil (39.6%) 2 and New York, USA (21%). 12 India has globally one of the highest recovery and the lowest COVID-19 mortality rates.…”
Section: Discussioncontrasting
confidence: 64%
See 1 more Smart Citation
“…The mortality rate among the hospitalized patients in this study (13.72%) was also significantly lower compared with reports in Brazil (39.6%) 2 and New York, USA (21%). 12 India has globally one of the highest recovery and the lowest COVID-19 mortality rates.…”
Section: Discussioncontrasting
confidence: 64%
“…It is well-established that although most patients with coronavirus disease 2019 (COVID-19) have mild-moderate symptoms and show recovery, a significant proportion require timely hospitalization to reduce the risk of complications and mortality. 1,2 The state of Delhi comprising the Indian capital city with a population of 19.6 million had recorded 0.48 million COVID-19 cases and 7614 associated deaths as of November 16, 2020. 3 Previous studies show that the risk of severe COVID-19 illness and fatality is higher among men, elderly, and in individuals with comorbidities, especially diabetes.…”
Section: Introductionmentioning
confidence: 99%
“…A number of studies reporting anti-SARS-CoV-2 seroprevalence data have been published (Barzin et al, 2020 ; Biggs et al, 2020 ; Chen et al, 2020 ; Hallowell et al, 2020 ; Kshatri et al, 2020 ; Lai et al, 2020 ; Majdoubi et al, 2020 ; Makaronidis et al, 2020 ; Murhekar et al, 2020 ; Picon et al, 2020 ; Rudberg et al, 2020 ; Song et al, 2020 ; Squeri et al, 2020 ; Stadlbauer et al, 2020 ; Takita et al, 2020 ; Wells et al, 2020 ), including a few with respect to blood donors (Amorim Filho et al, 2020 ; Erikstrup et al, 2020 ; Fiore et al, 2020 ; Fischer et al, 2020 ; Gallian et al, 2020 ; Ng et al, 2020 ; Percivalle et al, 2020 ; Younas et al, 2020 ). Our results are consistent with these reports in that seroprevalence estimates are generally low, albeit often several-fold higher than cumulative COVID-19 incidence rates.…”
Section: Discussionmentioning
confidence: 99%
“…However, to date we are aware of only two studies in any LMIC that estimate age-specific IFRs, and these are limited to small or non-representative samples. The sample in Picon et al ( 24 ) is representative for one city in Brazil; the sample in Verity et al ( 25 ) is limited to repatriated international residents leaving Wuhan Province (China) in a two-day span. Thus, this paper is the first to provide representative age- and sex-specific IFR estimates for a large population (the combined population of Mumbai and Karnataka is 73 million) in a low- or middle-income setting.…”
mentioning
confidence: 99%
“…IFR estimates almost universally rely upon large-scale seroprevalence samples drawn from the larger population, matched to administrative data on deaths. There have been very few seroprevalence studies (listed above) that can be matched to mortality counts in lower-income settings and none with sufficient sample size to calculate age-specific IFRs with any granularity ( 24 ). But IFRs that are not age-specific are difficult to compare across contexts, because the age pattern of infection may vary and aggregate IFRs will be larger in places where older people have a larger share of infections.…”
mentioning
confidence: 99%