The U.S. COVID-19 County Policy Database (Preliminary)

Principal Investigator(s): View help for Principal Investigator(s) Rita Hamad, Harvard School of Public Health; Mark Pletcher, University of California San Francisco; Thomas Carton, Louisiana Public Health Institute

Version: View help for Version V3

Name	File Type	Size	Last Modified
Data			10/03/2022 05:40:PM
Documentation			10/03/2022 07:03:PM

Project Citation:

Hamad, Rita, Pletcher, Mark, and Carton, Thomas . The U.S. COVID-19 County Policy Database (Preliminary). Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-07-29. https://doi.org/10.3886/E180482V3

Project Description

Summary: Please note that an updated version of this data set with additional waves of policy data for a larger set of counties has now been released and is available at ICPSR 39109: https://doi.org/10.3886/ICPSR39109.v1. The description of this preliminary data set follows:

It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. Yet there has been limited work to systematically evaluate the substantial variation in local COVID-19-related policies in the U.S. The objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level COVID-19-related policies within 3 policy domains that are likely to affect a variety of health outcomes: (1) containment/closure, (2) economic support, and (3) public health. In ongoing work, we are conducting retrospective longitudinal weekly data collection for the period 2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington D.C. The current database will be updated with new data as it becomes available, in late 2023 or early 2024.

Researchers who use this database for their studies should acknowledge the funders below in all publications.

Funding Sources: Patient-Centered Outcomes Research Institute (COVID-2020C2-10761); National Institute of Mental Health (U01MH129968)

Scope of Project

Subject Terms: COVID-19 pandemic; policy evaluation; economic support; health policy; public health

Geographic Coverage: 1.San Joaquin, CA 2.Sacramento, CA 3. Napa, CA 4.Yolo, CA 5.Lake, CA 6.Merced, CA 7.Mendocino, CA 8.Humboldt, CA 9.Del Norte, CA 10.Shasta, CA 11.Butte, CA 12.Tuolumne, CA 13.Amador, CA 14.El Dorado, CA 15.Placer, CA 16.Nevada, CA 17.Yuba, CA 18.Sutter, CA 19.San Diego, CA 20.San Luis Obispo, CA 21.Tulare, CA 22.Fresno, CA 23.Monterey, CA 24.Santa Cruz, CA 25.Santa Clara, CA 26.San Mateo, CA 27.San Francisco, CA 28.Los Angeles, CA 29.Alameda, CA 30.Contra Costa, CA 31.Marin, CA 32.Solano, CA 33.Sonoma, CA 34.Stanislaus, CA 35.Plaquemines, LA 36.St. Mary, LA 37.Washington, LA 38.Iberville, LA 39.Lafayette, LA 40.Assumption, LA 41.St. James, LA 42.Rapides, LA 43.De Soto, LA 44.Webster, LA 45.Lincoln, LA 46.East Feliciana, LA 47.St. Tammany, LA 48.Orleans, LA 49.East Baton Rouge, LA 50.West Baton Rouge, LA 51.Caddo, LA 52.Lafourche, LA 53.Livingston, LA 54.St. Charles, LA 55.Ascension, LA 56.Terrebonne, LA 57.Tangipahoa, LA 58.Jefferson, LA 59.St. John The Baptist, LA 60.St. Bernard, LA 61.Ouachita, LA 62.Calcasieu, LA 63.Bossier, LA 64.Hancock, MS 65.Pearl River, MS 66.Harrison, MS 67.Jackson, MS 68.Essex, NJ 69.Union, NJ 70.Morris, NJ 71.Ocean, NJ 72.Passaic, NJ 73.Somerset, NJ 74.Mercer, NJ 75.Middlesex, NJ 76.Hudson, NJ 77.Bergen, NJ 78.Monmouth, NJ 79.New York, NY 80.Kings, NY 81.Queens, NY 82.Orange, NY 83.Rockland, NY 84.Nassau, NY 85.Dutchess, NY 86.Bronx, NY 87.Putnam, NY 88.Ulster, NY 89.Essex, NY 90.Suffolk, NY 91.Richmond, NY 92.Westchester, NY 93.Dallas, TX 94.Tarrant, TX 95.Bell, TX 96.Collin, TX 97.Williamson, TX 98.McLennan, TX 99.Denton, TX 100.Travis, TX 101.Ellis, TX 102.Brazos, TX 103.Kaufman, TX 104.Rockwall, TX 105.Coryell, TX 106.Washington, TX 107.Hunt, TX 108.Burnet, TX 109.Hays, TX 110.Llano, TX 111.Milam, TX 112.Parker, TX 113.Grayson, TX 114.Johnson, TX 115.Harris, TX 116.Grimes, TX 117.Lee, TX 118.Navarro, TX 119.Limestone, TX 120.Robertson, TX 121.Austin, TX 122.Leon, TX 123.Hill, TX 124.Falls, TX 125.Cooke, TX 126.Fannin, TX 127.Henderson, TX 128.Bexar, TX 129.Wise, TX 130.Bastrop, TX 131.Van Zandt, TX 132.Bosque, TX 133.Montgomery, TX 134.Lampasas, TX 135.Hood, TX 136.Freestone, TX 137.San Saba, TX 138.Burleson, TX 139.Blanco, TX 140.Waller, TX 141.Hamilton, TX 142.Fayette, TX 143.Salt Lake, UT 144.Daggett, UT 145.Duchesne, UT 146.Morgan, UT 147.Garfield, UT 148.Millard, UT 149.Wayne, UT 150.Cache, UT 151.Kane, UT 152.Sevier, UT 153.Tooele, UT 154.Washington, UT 155.Box Elder, UT 156.Summit, UT 157.Grand, UT 158.Piute, UT 159.Emery, UT 160.Juab, UT 161.Beaver, UT 162.Sanpete, UT 163.Wasatch, UT 164.Utah, UT 165.San Juan, UT 166.Uintah, UT 167.Carbon, UT 168.Davis, UT 169.Weber, UT 170.Rich, UT 171.Iron, UT

Time Period(s): 1/2021 – 3/2021 (January - March 2021)

Collection Date(s): 1/2021 – 3/2021 (January - March 2021)

Universe: 171 counties in 7 states (see above geographic coverage)

Data Type(s): administrative records data; observational data

Collection Notes: In January-March 2021, we collected cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health.

Methodology

Response Rate: N/A

Sampling: N/A

Data Source: Internet searches

Collection Mode(s): other; record abstracts

Scales: N/A

Weights: N/A

Unit(s) of Observation: Counties

Geographic Unit: Counties

Related Publications

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Published Versions

V3 [2024-07-29]

V2 [2023-10-26]

V1 [2022-10-03]

Export Metadata

Dublin Core

DDI 2.5

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