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Data, Politics and Public Health: COVID-19 Data-Driven Decision Making in Public Discourse

Published: 03 December 2020 Publication History

Abstract

In spring 2020, New York City became the acknowledged epicenter of the COVID-19 pandemic in the United States. To keep residents informed, Governor Cuomo conducted a streak of 111 daily press briefings reporting critical information about the status of the pandemic in the State at large, and New York City in particular. We show that through these briefings Governor Cuomo introduced an audience of New Yorkers and others to concepts basic to data-driven decision making such as data, science, models, and projections, and in so doing claimed that his decisions were unrelated to politics or whim. But we further suggest that data-driven decision making is not always immune from politics and human frailty in government. We conclude that basing policy decisions on data requires that policymakers insure the creation of a resilient and trustworthy health care data infrastructure to function as the scaffolding upon which policy making takes place.

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Published In

cover image Digital Government: Research and Practice
Digital Government: Research and Practice  Volume 2, Issue 1
COVID-19 Commentaries
January 2021
116 pages
EISSN:2639-0175
DOI:10.1145/3434277
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 December 2020
Online AM: 13 November 2020
Accepted: 01 October 2020
Revised: 01 September 2020
Received: 01 August 2020
Published in DGOV Volume 2, Issue 1

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Author Tags

  1. COVID-19
  2. Data-driven decision making
  3. data models
  4. data science
  5. health care data
  6. health data infrastructure
  7. policymaking

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Cited By

View all
  • (2024)Strategic Analysis in the Public Sector Using Semantic Web TechnologiesDigital Government: Research and Practice10.1145/36565875:3(1-20)Online publication date: 13-Sep-2024
  • (2024) Reviving Storage Systems Education in the 21 st Century — An experience report 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid59990.2024.00074(616-625)Online publication date: 6-May-2024
  • (2023)Data sharing: A Long COVID perspective, challenges, and road map for the futureSouth African Journal of Science10.17159/sajs.2023/14719119:5/6Online publication date: 30-May-2023
  • (2023)Engineering Data Assets for Public Health Applications: A Covid-19 Case Study2023 IEEE International Conference on Big Data (BigData)10.1109/BigData59044.2023.10386435(1853-1862)Online publication date: 15-Dec-2023
  • (2023)Responding to the coronavirus disease-2019 pandemic with innovative data use: The role of data challengesData & Policy10.1017/dap.2023.65Online publication date: 27-Mar-2023
  • (2022)The Open Data Canvas–Analyzing Value Creation from Open DataDigital Government: Research and Practice10.1145/35111023:1(1-15)Online publication date: 26-Mar-2022
  • (2021)Rigorous Policy-Making Amid COVID-19 and Beyond: Literature Review and Critical InsightsInternational Journal of Environmental Research and Public Health10.3390/ijerph18231244718:23(12447)Online publication date: 26-Nov-2021
  • (2021)In sickness and in health: The politics of public health and their implications during the COVID‐19 pandemicSociology Compass10.1111/soc4.1294916:1Online publication date: 3-Dec-2021

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