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Tracking COVID-19 in the United States With Surveillance of Aggregate Cases and Deaths

Authors :
Diba Khan
Meeyoung Park
Jacqueline Burkholder
Sorie Dumbuya
Matthew D. Ritchey
Paula Yoon
Amanda Galante
Joseph L. Duva
Jeffrey Freeman
William Duck
Stephen Soroka
Lyndsay Bottichio
Michael Wellman
Samuel Lerma
B. Casey Lyons
Deborah Dee
Seghen Haile
Denise M. Gaughan
Adam Langer
Adi V. Gundlapalli
Amitabh B. Suthar
Source :
Public Health Reports. :003335492311635
Publication Year :
2023
Publisher :
SAGE Publications, 2023.

Abstract

Early during the COVID-19 pandemic, the Centers for Disease Control and Prevention (CDC) leveraged an existing surveillance system infrastructure to monitor COVID-19 cases and deaths in the United States. Given the time needed to report individual-level (also called line-level) COVID-19 case and death data containing detailed information from individual case reports, CDC designed and implemented a new aggregate case surveillance system to inform emergency response decisions more efficiently, with timelier indicators of emerging areas of concern. We describe the processes implemented by CDC to operationalize this novel, multifaceted aggregate surveillance system for collecting COVID-19 case and death data to track the spread and impact of the SARS-CoV-2 virus at national, state, and county levels. We also review the processes established to acquire, process, and validate the aggregate number of cases and deaths due to COVID-19 in the United States at the county and jurisdiction levels during the pandemic. These processes include time-saving tools and strategies implemented to collect and validate authoritative COVID-19 case and death data from jurisdictions, such as web scraping to automate data collection and algorithms to identify and correct data anomalies. This topical review highlights the need to prepare for future emergencies, such as novel disease outbreaks, by having an event-agnostic aggregate surveillance system infrastructure in place to supplement line-level case reporting for near–real-time situational awareness and timely data.

Details

ISSN :
14682877 and 00333549
Database :
OpenAIRE
Journal :
Public Health Reports
Accession number :
edsair.doi...........2049518bffd1fbb2e5b502465c17114f
Full Text :
https://doi.org/10.1177/00333549231163531