Report

The ZPID lockdown measures dataset for Germany

Author(s) / Creator(s)

Steinmetz, Holger
Batzdorfer, Veronika
Bosnjak, Michael

Abstract / Description

The outbreak of the COVID-19 pandemic has prompted the German government and the 16 German federal states to announce a variety of public health measures in order to suppress the spread of the coronavirus. These non-pharmaceutical measures intended to curb transmission rates by increasing social distancing (i.e., diminishing interpersonal contacts) which restricts a range of individual behaviors. These measures span moderate recommendations such as physical distancing, up to the closures of shops and bans of gatherings and demonstrations. The implementation of these measures are not only a research goal for themselves but have implications for behavioral research conducted in this time (e.g., in form of potential confounder biases). Hence, longitudinal data that represent the measures can be a fruitful data source. The presented data set contains data on 14 governmental measures across the 16 German federal states. In comparison to existing datasets, the dataset at hand is a fine-grained daily time series tracking the effective calendar date, introduction, extension, or phase-out of each respective measure. Based on self-regulation theory, measures were coded whether they did not restrict, partially restricted or fully restricted the respective behavioral pattern. The time frame comprises March 08, 2020 until May 15, 2020. The project is an open-source, ongoing project with planned continued updates in regular (approximately monthly) intervals. This release note presents the background, dataset structure and coding rules of the dataset.
Beitrag aus der Reihe "ZPID Science Information Online

Persistent Identifier

Date of first publication

2020-06

Is part of series

ZPID Science Information Online 20(1)

Publisher

ZPID (Leibniz Institute for Psychology Information)

Citation

Steinmetz, H., Batzdorfer, V., & Bosnjak, M. (June, 2020). The ZPID lockdown measures dataset. ZPID Science Information Online, 20(1). http://dx.doi.org/10.23668/psycharchives.3019
  • Author(s) / Creator(s)
    Steinmetz, Holger
  • Author(s) / Creator(s)
    Batzdorfer, Veronika
  • Author(s) / Creator(s)
    Bosnjak, Michael
  • Accession date
    2020-06-04T10:22:45Z
  • Made available on
    2020-06-04T10:22:45Z
  • Date of first publication
    2020-06
  • Abstract / Description
    The outbreak of the COVID-19 pandemic has prompted the German government and the 16 German federal states to announce a variety of public health measures in order to suppress the spread of the coronavirus. These non-pharmaceutical measures intended to curb transmission rates by increasing social distancing (i.e., diminishing interpersonal contacts) which restricts a range of individual behaviors. These measures span moderate recommendations such as physical distancing, up to the closures of shops and bans of gatherings and demonstrations. The implementation of these measures are not only a research goal for themselves but have implications for behavioral research conducted in this time (e.g., in form of potential confounder biases). Hence, longitudinal data that represent the measures can be a fruitful data source. The presented data set contains data on 14 governmental measures across the 16 German federal states. In comparison to existing datasets, the dataset at hand is a fine-grained daily time series tracking the effective calendar date, introduction, extension, or phase-out of each respective measure. Based on self-regulation theory, measures were coded whether they did not restrict, partially restricted or fully restricted the respective behavioral pattern. The time frame comprises March 08, 2020 until May 15, 2020. The project is an open-source, ongoing project with planned continued updates in regular (approximately monthly) intervals. This release note presents the background, dataset structure and coding rules of the dataset.
    en
  • Abstract / Description
    Beitrag aus der Reihe "ZPID Science Information Online
    de_DE
  • Citation
    Steinmetz, H., Batzdorfer, V., & Bosnjak, M. (June, 2020). The ZPID lockdown measures dataset. ZPID Science Information Online, 20(1). http://dx.doi.org/10.23668/psycharchives.3019
    en
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/2638
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.3019
  • Language of content
    eng
  • Publisher
    ZPID (Leibniz Institute for Psychology Information)
    en
  • Is part of series
    ZPID Science Information Online 20(1)
    en
  • Is related to
    https://doi.org/10.23668/psycharchives.4485
  • Dewey Decimal Classification number(s)
    150
  • Title
    The ZPID lockdown measures dataset for Germany
    en
  • DRO type
    report
    en
  • Leibniz institute name(s) / abbreviation(s)
    ZPID
    de_DE