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1.
COVID ; 3(5):728-743, 2023.
Article in English | Academic Search Complete | ID: covidwho-20236578

ABSTRACT

1. Background: Some reports have suggested that as many as one-half of all hospital inpatients identified as COVID-19-positive during the Omicron BA.1 variant-driven wave were incidental cases admitted primarily for reasons other than their viral infections. To date, however, there are no prospective longitudinal studies of a representative panel of hospitals based on pre-established criteria for determining whether a patient was, in fact, admitted as a result of the disease. 2. Materials and Methods: To fill this gap, we developed a formula to estimate the fraction of incidental COVID-19 hospitalizations that relies on measurable, population-based parameters. We applied our approach to a longitudinal panel of 164 counties throughout the United States, covering a 4-week interval ending in the first week of January 2022. 3. Results: Within this panel, we estimated that COVID-19 incidence was rising exponentially at a rate of 9.34% per day (95% CI, 8.93–9.87). Assuming that only one-quarter of all Omicron BA.1 infections had been reported by public authorities, we further estimated the aggregate prevalence of active SARS-CoV-2 infection during the first week of January to be 3.45%. During the same week, among 250 high-COVID-volume hospitals within our 164-county panel, an estimated one in four inpatients was COVID-positive. Based upon these estimates, we computed that 10.6% of such COVID-19-positive hospitalized patients were incidental infections. Across individual counties, the median fraction of incidental COVID-19 hospitalizations was 9.5%, with an interquartile range of 6.7 to 12.7%. 4. Conclusion: Incidental COVID-19 infections appear to have been a nontrivial fraction of all COVID-19-positive hospitalized patients during the Omicron BA.1 wave. In the aggregate, however, the burden of patients admitted for complications of their viral infections was far greater. [ FROM AUTHOR] Copyright of COVID is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

2.
Int J Infect Dis ; 112: 25-34, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1654527

ABSTRACT

BACKGROUND: The lower than expected COVID-19 morbidity and mortality in Africa has been attributed to multiple factors, including weak surveillance. This study estimated the burden of SARS-CoV-2 infections eight months into the epidemic in Nairobi, Kenya. METHODS: A population-based, cross-sectional survey was conducted using multi-stage random sampling to select households within Nairobi in November 2020. Sera from consenting household members were tested for antibodies to SARS-CoV-2. Seroprevalence was estimated after adjusting for population structure and test performance. Infection fatality ratios (IFRs) were calculated by comparing study estimates with reported cases and deaths. RESULTS: Among 1,164 individuals, the adjusted seroprevalence was 34.7% (95% CI 31.8-37.6). Half of the enrolled households had at least one positive participant. Seropositivity increased in more densely populated areas (spearman's r=0.63; p=0.009). Individuals aged 20-59 years had at least two-fold higher seropositivity than those aged 0-9 years. The IFR was 40 per 100,000 infections, with individuals ≥60 years old having higher IFRs. CONCLUSION: Over one-third of Nairobi residents had been exposed to SARS-CoV-2 by November 2020, indicating extensive transmission. However, the IFR was >10-fold lower than that reported in Europe and the USA, supporting the perceived lower morbidity and mortality in sub-Saharan Africa.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Cross-Sectional Studies , Humans , Kenya/epidemiology , Middle Aged , Seroepidemiologic Studies
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