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The challenges of data usage for the United States' COVID-19 response.
Galaitsi, S E; Cegan, Jeffrey C; Volk, Kaitlin; Joyner, Matthew; Trump, Benjamin D; Linkov, Igor.
  • Galaitsi SE; U.S. Army Corps of Engineers, Vicksburg, MS, United States.
  • Cegan JC; U.S. Army Corps of Engineers, Vicksburg, MS, United States.
  • Volk K; U.S. Army Corps of Engineers, Vicksburg, MS, United States.
  • Joyner M; U.S. Army Corps of Engineers, Vicksburg, MS, United States.
  • Trump BD; U.S. Army Corps of Engineers, Vicksburg, MS, United States.
  • Linkov I; U.S. Army Corps of Engineers, Vicksburg, MS, United States.
Int J Inf Manage ; 59: 102352, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1345355
ABSTRACT
During the coronavirus pandemic, policy makers need to interpret available public health data to make decisions affecting public health. However, the United States' coronavirus response faced data gaps, inadequate and inconsistent definitions of data across different governmental jurisdictions, ambiguous timing in reporting, problems in accessing data, and changing interpretations from scientific institutions. These present numerous problems for the decision makers relying on this information. This paper documents some of the data pitfalls in coronavirus public health data reporting, as identified by the authors in the course of supporting data management for New England's coronavirus response. We provide recommendations for individuals to collect data more effectively during emergency situations such as a COVID-19 surge, as well as recommendations for institutions to provide more meaningful data for various users to access. Through this, we hope to motivate action to avoid data pitfalls during public health responses in the future.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Int J Inf Manage Year: 2021 Document Type: Article Affiliation country: J.ijinfomgt.2021.102352

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Int J Inf Manage Year: 2021 Document Type: Article Affiliation country: J.ijinfomgt.2021.102352