Your browser doesn't support javascript.
Open government data, uncertainty and coronavirus: An infodemiological case study.
Yiannakoulias, Nikolaos; Slavik, Catherine E; Sturrock, Shelby L; Darlington, J Connor.
  • Yiannakoulias N; School of Earth, Environment and Society, McMaster University, Hamilton, Ontario, Canada. Electronic address: yiannan@mcmaster.ca.
  • Slavik CE; School of Earth, Environment and Society, McMaster University, Canada.
  • Sturrock SL; Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Canada.
  • Darlington JC; Department of Geography and Environmental Management, University of Waterloo, Canada.
Soc Sci Med ; 265: 113549, 2020 11.
Article in English | MEDLINE | ID: covidwho-970135
ABSTRACT
Governments around the world have made data on COVID-19 testing, case numbers, hospitalizations and deaths openly available, and a breadth of researchers, media sources and data scientists have curated and used these data to inform the public about the state of the coronavirus pandemic. However, it is unclear if all data being released convey anything useful beyond the reputational benefits of governments wishing to appear open and transparent. In this analysis we use Ontario, Canada as a case study to assess the value of publicly available SARS-CoV-2 positive case numbers. Using a combination of real data and simulations, we find that daily publicly available test results probably contain considerable error about individual risk (measured as proportion of tests that are positive, population based incidence and prevalence of active cases) and that short term variations are very unlikely to provide useful information for any plausible decision making on the part of individual citizens. Open government data can increase the transparency and accountability of government, however it is essential that all publication, use and re-use of these data highlight their weaknesses to ensure that the public is properly informed about the uncertainty associated with SARS-CoV-2 information.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Uncertainty / Health Communication / COVID-19 / Government Type of study: Case report / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: Soc Sci Med Year: 2020 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Uncertainty / Health Communication / COVID-19 / Government Type of study: Case report / Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: Soc Sci Med Year: 2020 Document Type: Article