Developing a sampling methodology for timely reporting of population-based COVID-19-associated hospitalization surveillance in the United States, COVID-NET 2020-2021.

Autor: O'Halloran A; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Whitaker M; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Patel K; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.; General Dynamics Information Technology, Atlanta, Georgia, USA., Allen AE; NORC, The University of Chicago, Chicago, Illinois, USA., Copeland KR; NORC, The University of Chicago, Chicago, Illinois, USA., Reed C; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Reynolds S; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Taylor CA; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Havers F; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Kim L; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Wolter K; NORC, The University of Chicago, Chicago, Illinois, USA., Garg S; COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Jazyk: angličtina
Zdroj: Influenza and other respiratory viruses [Influenza Other Respir Viruses] 2023 Jan; Vol. 17 (1), pp. e13089. Date of Electronic Publication: 2023 Jan 10.
DOI: 10.1111/irv.13089
Abstrakt: Background: The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) required a sampling methodology that allowed for production of timely population-based clinical estimates to inform the ongoing US COVID-19 pandemic response.
Methods: We developed a flexible sampling approach that considered reporting delays, differential hospitalized case burden across surveillance sites, and changing geographic and demographic trends over time. We incorporated weighting methods to adjust for the probability of selection and non-response, and to calibrate the sampled case distribution to the population distribution on demographics. We additionally developed procedures for variance estimation.
Results: Between March 2020 and June 2021, 19,293 (10.4%) of all adult hospitalized cases were sampled for chart abstraction. Variance estimates for select variables of interest were within desired ranges.
Conclusions: COVID-NET's sampling methodology allowed for reporting of robust and timely, population-based data on the clinical epidemiology of COVID-19-associated hospitalizations and evolving trends over time, while attempting to reduce data collection burden on surveillance sites. Such methods may provide a general framework for other surveillance systems needing to quickly and efficiently collect and disseminate data for public health action.
(© 2023 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje