dc.contributor.author | Harris, Jeffrey E. | |
dc.date.accessioned | 2023-05-12T15:30:44Z | |
dc.date.available | 2023-05-12T15:30:44Z | |
dc.date.issued | 2023-05-08 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/150671 | |
dc.description.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. | en_US |
dc.publisher | Multidisciplinary Digital Publishing Institute | en_US |
dc.relation.isversionof | http://dx.doi.org/10.3390/covid3050054 | en_US |
dc.rights | Creative Commons Attribution | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_US |
dc.source | Multidisciplinary Digital Publishing Institute | en_US |
dc.title | Population-Based Model of the Fraction of Incidental COVID-19 Hospitalizations during the Omicron BA.1 Wave in the United States | en_US |
dc.type | Article | en_US |
dc.identifier.citation | COVID 3 (5): 728-743 (2023) | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Economics | |
dc.identifier.mitlicense | PUBLISHER_CC | |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2023-05-12T12:36:28Z | |
dspace.date.submission | 2023-05-12T12:36:28Z | |
mit.license | PUBLISHER_CC | |
mit.metadata.status | Authority Work and Publication Information Needed | en_US |