This is an original dataset of stringency of public health policy measures that were adopted in response to COVID-19 worldwide by governments at national and sub-national levels. The data set covers governments' policy responses between January 24, 2020 and December 31, 2020.
Developed by SUNY Binghamton COVID-19 Policy Response Lab.
- Olga Shvetsova scientific director, shvetso@binghamton.edu
- Mert Can Bayar, mbayar1@binghamton.edu
- Onsel Gurel Bayrali, obayral1@binghamton.edu
- Michael Catalano, mcatala4@binghamton.edu
- Hyoungrohk Chu, hchu13@binghamton.edu
- Ezgi Muftuoglu, emuftuo1@binghamton.edu
- Bradley Skopyk, bskopyk@binghamton.edu
- Didem Seyis, dseyis1@binghamton.edu
- Tianyi Zhao, tzhao19@binghamton.edu
- Abdul Basit Adeel, axa6372@psu.edu
- Olivia Catalano, olivia.catalano15@gmail.com
- Frank Giannelli, Rutgers, The State University of New Jersey, giannefr@shp.rutgers.edu
- Dina Rosenberg, Higher School of Economics, drosenberg@hse.ru
- Julie VanDusky-Allen, Boise State University, julievanduskyallen@boisestate.edu
- Ruohao Zhang, ruohao.zhang@law.northwestern.edu
- Andrei Zhirnov, University of Exeter, A.Zhirnov@exeter.ac.uk
- Garrett DuMond, Binghamton University
- Georgian-Marius Ghincea, European University Institute
- Jason Means, University of Vienna
- Hasan Ozutemiz, Binghamton University
- Tara Riggs, Binghamton University
- Almira Sadykova, Binghamton University
- Mehmet Halit Sezgin, Binghamton University
- Naveed Tahir, Syracuse University
To measure COVID-19 mitigation policy responses, data is gathered on policies that national and sub-national policymakers adopted within fifteen public health categories. National and subnational public health policies are regionally and nationally identified and coded in 74 countries, including countries in North America, Central America, South America, Europe, the Middle East, and Asia.
The fifteen public health categories include:
- introduction of the state of emergency
- self-isolation and quarantine
- border closures
- limits on social gatherings
- school closings
- closure of entertainment venues
- closure of restaurants
- closure of non-essential businesses
- closure of government offices
- work from home requirements
- lockdowns and curfews
- public transportation closure
- mandatory wearing of masks and other personal protective equipment.
The primary resources used during the data collection process include government resources, press releases, and news sources. We record the date of the first announcement and the date when the policies were in effect. Note that between and within the policy categories, there is variation on stringency, with some policy adoptions being more stringent than others (i.e. self-isolation versus lockdowns, partial school closings versus full school closings). To this end, more stringent policies are weighted more in each category and in the index: the information about the weights of different categories can be found in the codebook.
Based on the recoded public health policy responses to COVID-19, we produce three types of the Public Health Protective Policy Index (PPI):
- Regional PPI for each subnational unit on each day
- National PPI for each subnational unit on each day (based on national level policies)
- Total PPI for each subnational unit on each day
The Total PPI is based on the national and subnational policies and uses the highest values in each category for that unit for that day. The indices are scaled to range between 0 and 1. The Average Total PPI for each country-day is computed by weighing the different units' Total PPI values by the units' population shares. Maps with these three indices can be viewed on the policy dashboard of the lab .
The published data descriptor can be found here. Please cite it as:
Shvetsova, Olga, Andrei Zhirnov, Abdul Basit Adeel, Mert Can Bayar, Onsel Gurel Bayrali, Michael Catalano, Olivia Catalano, Hyoungrohk Chu, Frank Giannelli, Ezgi Muftuoglu, Dina Rosenberg, Didem Seyis, Bradley Skopyk, Julie VanDusky-Allen, and Tianyi Zhao. 2022. "Protective Policy Index (PPI) global dataset of origins and stringency of COVID-19 mitigation policies." Nature Scientific Data 9: 319. doi:10.1038/s41597-022-01437-9.