Last data update: Sep 30, 2024. (Total: 47785 publications since 2009)
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Query Trace: Roush SW[original query] |
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COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5-September 30, 2020.
Gold JAW , DeCuir J , Coyle JP , Duca LM , Adjemian J , Anderson KN , Baack BN , Bhattarai A , Dee D , Durant TM , Ewetola R , Finlayson T , Roush SW , Yin S , Jackson BR , Fullerton KE . Public Health Rep 2021 136 (4) 466-474 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. |
Public health surveillance workforce of the future
Drehobl PA , Roush SW , Stover BH , Koo D . MMWR Suppl 2012 61 (3) 25-9 Although electronic data systems that monitor for health threats are becoming increasingly automated, human expertise is, and always will be, critical to recognizing potential cases of disease, diagnosing disease, reporting diseases or conditions, analyzing and interpreting data, and communicating results to all stakeholders. For this reason, the nation's health professionals from all disciplines and at all levels are fundamental to sustaining and enhancing public health surveillance capacity. |
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