Comparing Patient-reported Impact of COVID-19 Shelter-in-place Policies and Access to Containment and Mitigation Strategies Overall and in Vulnerable Populations, United States, 2020-2022 (ICPSR 39218)

Version Date: Aug 5, 2025 View help for published

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Mark Pletcher, University of California-San Francisco; Thomas Carton, Louisiana Public Health Institute

https://doi.org/10.3886/ICPSR39218.v1

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The COVID-19 Citizen Science (CCS) Study was launched early in the pandemic to collect patient-reported information about exposures, risk behaviors and outcomes relevant to the pandemic. The Patient-Centered Outcomes Research Institute (PCORI) funded the research team to expand recruitment into CCS using PCORnet, the National Patient-Centered Clinical Research Network, and to use the resulting data to compare the patient-reported impact of pandemic associated policies. The research team systematically collected pandemic-associated policies enacted by counties across the United States (focusing in areas where there were many CCS participants), and to do so on a weekly basis from the beginning of the pandemic using publicly available sources.

Researchers combined data from various sources to answer two primary research questions (RQ):

  1. What is the comparative impact of different shelter-in-place/reopening policies, overall and in vulnerable populations, on patient-reported financial insecurity, mental health, and other subjective outcomes important to patients?
  2. What is the comparative effectiveness of county-level containment and mitigation strategies at achieving timely access to COVID-19 vaccination, testing, healthcare, information and contact tracing?

The research team collected patient-reported data from the CCS study and policy data from the U.S COVID-19 County Policy (UCCP) database. Electronic health record (EHR) data were also available from some participants recruited from health systems located across 7 U.S. states who consented and authorized use of these data for the study. Data for these participants were extracted from the PCORnet Common Data Model (CDM). Additional county-level contextual variables were included in analysis.

This collection contains CCS survey data on patient-reported anxiety with county-level policies data (DS1), respondent demographics (DS2), baseline survey results (DS3), daily (DS4) and weekly (DS5) COVID-19 symptoms reports, COVID-19 vaccination surveys repeated monthly (DS6) as well as a one-time vaccination survey (DS7), and pandemic impacts check-in surveys (DS8). CDM datasets include logistic regression model outcomes to predict study enrollment among all invited participants (DS9), codes for immunizations (DS10), laboratory tests (DS11), and procedures (DS12). County-level variables are also available for years 2021 (DS13) and 2023 (DS14).

Pletcher, Mark, and Carton, Thomas. Comparing Patient-reported Impact of COVID-19 Shelter-in-place Policies and Access to Containment and Mitigation Strategies Overall and in Vulnerable Populations, United States, 2020-2022. Inter-university Consortium for Political and Social Research [distributor], 2025-08-05. https://doi.org/10.3886/ICPSR39218.v1

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Patient-Centered Outcomes Research Institute (COVID-2020C2-10761)

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Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reason for the request, and obtain IRB approval or notice of exemption for their research.

Inter-university Consortium for Political and Social Research
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2020-04-22 -- 2021-12-31 (Policy-Anxiety data), 2020-03-26 -- 2023-10-26 (All other CCS data)
2020-04-22 -- 2023-01-24 (Policy-Anxiety data), 2020-03-26 -- 2022-12-31 (All other CCS data)
  1. This collection is related to United States COVID-19 County Policy Database, 2020-2021 (ICPSR 39109). Please refer to this study for methodological details on data collected on COVID-19 state- and county-level policies.
  2. For results and other media materials from the COVID-19 Citizen Science (CSS) study, please visit the CCS study updates webpage.
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The purpose of the study was to understand the impact of COVID-19 pandemic policies (i.e., shelter-in-place orders, social distances, non-essential business closures) on patient-reported outcomes and on access to containment and mitigation strategies, with the goal to help policymakers reduce harms sustained by the pandemic.

The COVID-19 Citizen Science (CSS) study used a multi-center cohort design with digital engagement of participants - i.e., an "eCohort" study. The CCS study was launched on March 26, 2020 and was hosted on the Eureka research platform, which required participants to be 18 years of age or older, register for a Eureka account, have a smartphone and a cell phone number (a web version of the study was also launched on January 21, 2021), and agree to participate in English. CCS recruited participants globally through press release, word-of-mouth, and partner organizations. The bulk of participants were recruited through U.S. health systems, with invitations delivered to adult patients at the University of California, San Francisco, the University of Utah, Montefiore, New York University, Baylor, Scott and White, Ochsner, and Advocate Aurora Health.

After consenting to the CCS study, participants completed a baseline survey with demographics, medical conditions, medications, behaviors, and past COVID-19 test results. Throughout the study period, participants were prompted to complete daily, weekly, and monthly surveys through the research platform.

Some participants recruited from health systems had the option of authorizing release of electronic health records (EHR) to examine clinical outcomes. Records were queried and extracted from the PCORnet Common Data Model (CDM). Patient-reported outcomes from the CCS were linked to the CDM via a "golden ticket number", which functions as a study ID.

Other data sources for analysis include retrospective COVID-19 policy data from the U.S. COVID-19 County Policy Database (UCCP), COVID-19 death counts from the New York Times, CDC Social Vulnerability Index (SVI) markers, and county-level contextual variables (e.g., GDP, racial group proportions, political leanings, employment, population density, etc.)

Sample size and enrollment targets were not prespecified for this study. Different subsets of study participants were included for different analyses.

For Research Question 1 (RQ1), analysis was limited to participants who completed the demographics survey, reported their zip code, and submitted at least one anxiety survey (n=56,292 participants), and then further limited to those living in a county where COVID-19 policy data was available from the U.S. COVID-19 County Database (UCCP). In all, 33,756 participants were included in the RQ1 analysis.

For Research Question 2 (RQ2), 96,226 total participants (out of 106,251 consented) reported a zip code that could be linked to a U.S. county to enable a positive deviance analysis, and were considered for inclusion for each of the RQ2 outcome analyses.

Longitudinal: Cohort / Event-based

Adults in the United States.

Event/Process (Clinic Visit), Individual, Geographic Unit (State, County, Zip Code), Time Unit (Day, Week)

U.S. Department of Commerce, Bureau of Economic Analysis

U.S. COVID-19 County Policies (UCCP) Database

Centers for Disease Control and Prevention (CDC)

New York Times

Bureau of Labor Statistics

Johns Hopkins University Center for Civic Impact, Coronavirus Resource Center

Federal Reserve

National Oceanic and Atmospheric Administration, National Centers for Environmental Information

MIT Election Data and Science Lab, 2018, "County Presidential Election Returns 2000-2020"

National Conference of State Legislatures

Robert Wood Johnson Foundation County Health Rankings

U.S. Census Bureau

  • Individual demographics: age, gender, sex, race, Hispanic ethnicity, education level, employment industry (including essential worker indicator) (DS1, DS2)
  • Geography: County FIPS code and name, state, region (Census Bureau definition) (DS1, DS2, DS6, DS13, DS14)
  • COVID-19 policy and cases items: comprehensiveness indices based on restrictions and closures of public spaces (bars, restaurants, daycare, religious gatherings, etc.), sources of support (food, income, housing, utilities, sick leave, etc.), and public health containment/mitigation efforts (testing, contact tracing, face coverings, vaccinations, etc.); rolling averages of COVID-19 cases per 100,000 (DS1)
  • COVID-19 symptoms reports: if respondent experienced symptoms and which symptoms (fever, coughing, runny nose, shortness of breath, inability to taste/smell, muscle aches, sore or scratchy throat, nausea), start date of symptoms (DS3, DS4, DS5)
  • COVID-19 testing: if respondent was tested, type of test (active or past infection), how many tests performed (DS3, DS5)
  • Vaccinations: if respondent planned to get a COVID-19 vaccine, date of vaccine receipt (DS3, DS6, DS7)
  • Pandemic impact and outcome items: General Anxiety Disorder-7 (GAD-7) score; financial anxieties (e.g., difficulty making ends meet); perceived impact on respondent's and respondent's children's physical health, mental/emotional health, social relationships, work/education, and finances; perceived return to "normal" (DS1, DS8)
  • Items derived from electronic health records: average number of hospitalizations and healthcare encounters (including telehealth); codes for immunizations, laboratory tests, and procedures (DS9, DS10, DS11, DS12)
  • County-level contextual variables: poverty rate, primary care physicians per 100,000 population, gross domestic product (2012 dollars), number of jobs by industry, unemployment rate, average temperature and precipitation levels, racial group proportions, high school graduate proportions, political party affiliation, and COVID-19/healthcare related aggregates (deaths, cases, PCR tests, adult inpatient and ICU beds for COVID-19 patients, vaccinations) (DS13, DS14)

Of the 106,514 participants registered for COVID-19 Citizen Science (CCS), 103,251 consented. For the anxiety surveys, 36,711 individuals were included in the dataset and a total of 189,148 responses were received (44.4% of total possible).

  • Adler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol. 2000;19(6):586-92. pmid:11129362.
  • Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092-7. Epub 2006/05/24. pmid:16717171.
  • Charleson Comorbidity Index (CCI)
  • CDC Social Vulnerability Index (SVI)
  • MacArthur Scale of Subjective Social Status

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2025-08-05

2025-08-05 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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The policies and anxiety dataset (DS1) includes an inverse probability weight variable, IPW, which can be used to examine expected sampling bias. Electronic health record data from the full sampling frame at each participating health system was used to develop the sampling weight.

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Notes

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • One or more files in this data collection have special restrictions. Restricted data files are not available for direct download from the website; click on the Restricted Data button to learn more.

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This study is maintained and distributed by the Patient-Centered Outcomes Data Repository (PCODR). PCODR is the official data repository of the Patient-Centered Outcomes Research Initiative (PCORI).