Keystone's Coronavirus (COVID-19) Intervention Dataset Model

Insufficient data has complicated the rollout of Coronavirus (COVID-19) “Non-Pharmaceutical Interventions” (NPIs) such as the closing of schools. Keystone has partnered with Susan Athey, Stanford Professor of Economics, and Marco Iansiti, Director of Harvard Business School's Digital Initiative, to estimate the effectiveness of NPIs as a guide to policymakers, and to aid firms in developing strategic responses, respectively. We are building a comprehensive, highly localized and freely available data set of city, county and state rollout dates for NPIs. For more information or data access, contact us. NPIs INCLUDE:

• SDO - Social Distancing of vulnerable persons;
• SD - Social Distancing of the general population;
• GS_XX - Gathering Size limitations;
• CPV - Closure of Public Venues;
• PC - Closure of schools and universities;
• NESC - Non-Essential Services Closure;
• LD - Lock Down (pending);

650 US Counties Covered as of 6/18/2020 (additions in progress). A sample of counties below (additions in progress). To see the full list click here. A sample of counties below:

Alameda County, CA Bergen County, NJ Bexar County, TX Contra Costa County, CA Cook County, IL Dallas County, TX Denver County, CO Dupage County, IL Fulton County, GA Hudson County, NJ

Johnson County, KS King County, WA Lake County, IL Las Vegas County, NV Los Angeles County, CA Miami Dade County, FL Middlesex County, Ma Nassau County, NY New York City, NY Norfolk County, MA

Rockland County, NY San Diego County, CA San Francisco County, CA San Mateo County, CA Santa Clara County, CA Snohomish County, WA Suffolk County, MA Washington, DC Wayne, County, MI Westchester County, NY

Please see link to this Shared Google Doc for more information. If you or any of your colleagues would like to expand our dataset to include other countries and/or U.S. cities and counties not yet included, please point them to our links below. With your help sharing these links on social media and via your own networks, we can improve the data set and broaden our initial scope. Request Data: [hubspotform portal_id="6724850" form_id="3655434e-36ed-4659-b7bc-5d7060dfea46" css=""] PUBLISHED PAPERS USING THE KEYSTONE DATASETS FOR NPIs As of November 2, 2021, there have been 19 academic articles published leveraging this dataset. You can find the entire list on Google Scholar here with select articles highlighted below. Scenario analysis of non-pharmaceutical interventions on global COVID-19 transmissions Arvix This paper introduces a dynamic panel SIR (DP-SIR) model to investigate the impact of non-pharmaceutical interventions (NPIs) on the COVID-19 transmission dynamics with panel data from 9 countries across the globe. What works against the spread of COVID-19? Medium With more detailed data on the varying introduction of policies across US counties and over time as well as the resulting spread of the disease we could provide evidence on which measures we should keep and which measures we should lift in order to reactivate the economy. Income Effect and the Private Contribution of Public Goods:Household Mobility and the Economic Impact Payment during the COVID-19 Pandemic Binghamton University This paper studies the public good nature of COVID-19 mitigation effort, and illustrates the relationship between income level and the voluntary contribution to the COVID-19 mitigation effort. Weather, Social Distancing, and the Spread of COVID-19 MedRxiv Using high-frequency panel data for U.S. counties, this paper examines the full dynamic response of COVID-19 cases and deaths to exogenous movements in mobility and weather. Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists CESifo Working Papers A critical review of models of the spread of the coronavirus (SARS-CoV-2) that have been influential in recent policy discussions. It notes potentially important features of the real- world environment that standard models do not incorporate. The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data US Federal Reserve Using monthly credit card data from the Federal Reserve's Y-14M reports to study the early impact of the COVID-19 shock on the use and availability of consumer credit. Staggered Adoption of Nonpharmaceutical Interventions to Contain COVID-19 Across U.S. Counties: Direct and Spillover Effects Johns Hopkins Carey Business School We estimate direct and spillover effects of social distancing measures intended to slow the spread of COVID-19 at the U.S. county level using mobility indicators based on cellphone data. We find that spillover effects range between a third and a half of the direct effect depending on the particular outcome or policy considered. Our results suggest that decentralized NPI decisions, which does not internalize externalities generated on surrounding locations, could result in lower NPI implementation and weaker reduction in mobility, and hence more personal contacts and interactions in leisure and work activities, which are the main driver of the COVID-19 transmission. Tracking the Economic Impact of COVID-19 and Mitigation Policies in Europe and the United States International Monetary Fund Here is a framework to use high-frequency indicators, such as electricity usage, for policymakers to assess the economic impact of COVID-19 in close to real time. We also examine the link between economic activity and mitigation efforts to help policymakers better understand the possible path of economic activity as lockdown measures are relaxed.