Capturing the COVID-19 Crisis through Public Health and Social Measures Data Science

Cheng, Cindy; Desvars-Larrive, Amélie; Ebbinghaus, Bernhard; Hale, Thomas; Howes, Alexandra; Lehner, Lukas; Messerschmidt, Luca; Nika, Angeliki; Penson, Steve; Petherick, Anna; Xu, Hanmeng; Zapf, Alexander; Zhang, Yuxi; Zweig, Sophia Alison

doi:10.1038/s41597-022-01616-8

Cited by 9 publications

(7 citation statements)

References 32 publications

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“…During both conferences though especially the first, trackers discussed common challenges and solutions to their data collection efforts, especially with regards to taxonomy and organization. Both the planning of the conferences and conferences themselves helped increase mutual understanding and collegiality among trackers 1 . For more information, please see https://covid19-conference.org or the shared statement written by conference participants outlining a framework for cooperation and collaboration (PHSM 2021).…”

Section: Resultsmentioning

confidence: 99%

“…the economy, the environment and society, to say nothing of their ostensible function of reducing the spread of the virus itself. Though dozens of research groups have documented COVID-19 PHSM, these individual data tracking efforts provide only an incomplete portrait of COVID-19 PHSM, with many having stopped their efforts entirely, often due to funding constraints 1 .…”

Section: Introductionmentioning

confidence: 99%

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Harmonizing government responses to the COVID-19 pandemic

Cheng,

Messerschmidt,

Bravo

et al. 2024

Sci Data

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Public health and safety measures (PHSM) made in response to the COVID-19 pandemic have been singular, rapid, and profuse compared to the content, speed, and volume of normal policy-making. Not only can they have a profound effect on the spread of the disease, but they may also have multitudinous secondary effects, in both the social and natural worlds. Unfortunately, despite the best efforts by numerous research groups, existing data on COVID-19 PHSM only partially captures their full geographical scale and policy scope for any significant duration of time. This paper introduces our effort to harmonize data from the eight largest such efforts for policies made before September 21, 2021 into the taxonomy developed by the CoronaNet Research Project in order to respond to the need for comprehensive, high quality COVID-19 data. In doing so, we present a comprehensive comparative analysis of existing data from different COVID-19 PHSM datasets, introduce our novel methodology for harmonizing COVID-19 PHSM data, and provide a clear-eyed assessment of the pros and cons of our efforts.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Harmonizing government responses to the COVID-19 pandemic

Cheng,

Messerschmidt,

Bravo

et al. 2024

Sci Data

Self Cite

View full text Add to dashboard Cite

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“…To illustrate the ability of our criteria to provide guidance and context for the feasibility and relative value for pursuing data harmonization over other data generation efforts, we apply them to our efforts to harmonize COVID-19 PHSM data. Comprehensive, high quality and timely COVID-19 PHSM data is crucial for forwarding understanding of the pandemic but unfortunately no single dataset has been able to capture the full scope or scale of such data [99]. Not only can harmonizing this data get us closer to this goal, it can also ensure that the data collected by trackers that have stopped their work are not lost and that the original sources underlying this data are preserved.…”

Section: Harmonizing Covid-19 Phsm Datamentioning

confidence: 99%

“…Since many PHSM trackers have stopped data collection due to funding constraints, data harmonization into the CoronaNet taxonomy also ensures that these data can live on and be used in an active research project [99]. Note that most data from external datasets do not save original PDF sources, leading to the gradual disappearance of the primary sources on which PHSM datasets are built.…”

Section: Harmonizing Covid-19 Phsm Datamentioning

confidence: 99%

“…During both conferences though especially the őrst, trackers discussed common challenges and solutions to their data collection efforts, especially with regards to taxonomy and organization. Both the planning of the conferences and conferences themselves helped increase mutual understanding and collegiality among trackers [99]. For more information, please see https: //covid19-conf erence.org or the shared statement written by conference participants outlining a framework for cooperation and collaboration (PHSM 2021).…”

Section: What Cooperative Resources Are Available For Harmonizing Data?mentioning

confidence: 99%

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A General Guide for Harmonizing Data: Drawing Lessons from Harmonizing COVID-19 PHSM Data

Cheng

Messerschmidt

Bravo

et al. 2023

Preprint

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Data harmonization is an important method for generating the requisite datasets to support big data analyses. To date however, articles about data harmonization are field-specific and highly technical, making it difficult for researchers to derive general principles for how to engage in and contextualize data harmonization efforts. This article provides general guidance and criteria for researchers who are considering undertaking such efforts or seek to evaluate the quality of existing ones. We derive these guidelines from the extant literature and our own experience in harmonizing data for the emergent and important new field of COVID-19 public health and safety measures (PHSM). We further introduce the methodology we employed for engaging in this data harmonization as a blueprint for researchers interested in engaging in manual data harmonization.

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