COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5–September 30, 2020

Author:

Gold Jeremy A.W.12,DeCuir Jennifer123,Coyle Jayme P.1,Duca Lindsey M.12,Adjemian Jennifer34,Anderson Kayla N.1,Baack Brittney N.1,Bhattarai Achuyt1,Dee Deborah13,Durant Tonji M.1,Ewetola Raimi1,Finlayson Teresa1,Roush Sandra W.5,Yin Shaoman1,Jackson Brendan R.13,Fullerton Kathleen E.1

Affiliation:

1. COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA

2. Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA

3. US Public Health Service, Rockville, MD, USA

4. Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA

5. National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA

Abstract

Objectives To obtain timely and detailed data on COVID-19 cases in the United States, the Centers for Disease Control and Prevention (CDC) uses 2 data sources: (1) aggregate counts for daily situational awareness and (2) person-level data for each case (case surveillance). The objective of this study was to describe the sensitivity of case ascertainment and the completeness of person-level data received by CDC through national COVID-19 case surveillance. Methods We compared case and death counts from case surveillance data with aggregate counts received by CDC during April 5–September 30, 2020. We analyzed case surveillance data to describe geographic and temporal trends in data completeness for selected variables, including demographic characteristics, underlying medical conditions, and outcomes. Results As of November 18, 2020, national COVID-19 case surveillance data received by CDC during April 5–September 30, 2020, included 4 990 629 cases and 141 935 deaths, representing 72.7% of the volume of cases (n = 6 863 251) and 71.8% of the volume of deaths (n = 197 756) in aggregate counts. Nationally, completeness in case surveillance records was highest for age (99.9%) and sex (98.8%). Data on race/ethnicity were complete for 56.9% of cases; completeness varied by region. Data completeness for each underlying medical condition assessed was <25% and generally declined during the study period. About half of case records had complete data on hospitalization and death status. Conclusions Incompleteness in national COVID-19 case surveillance data might limit their usefulness. Streamlining and automating surveillance processes would decrease reporting burdens on jurisdictions and likely improve completeness of national COVID-19 case surveillance data.

Publisher

SAGE Publications

Subject

Public Health, Environmental and Occupational Health

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