All United States: COVID-19 Government Responses
& Standardized All-Cause Mortality Statistics
Daily COVID Response Graphs "The Oxford Covid-19 Government Response Tracker (OxCGRT) collects systematic information on which governments have taken which measures, and when. This can help decision-makers and citizens understand governmental responses in a consistent way, aiding efforts to fight the pandemic. The OxCGRT systematically collects information on several different common policy responses governments have taken, records these policies on a scale to reflect the extent of government action, and aggregates these scores into a suite of policy indices.
This is a project from the Blavatnik School of Government. More information on the OxCGRT is available on the school's website: https://www.bsg.ox.ac.uk/covidtracker. This README contains information about using the database."
"To help make sense of the data, we have produced four indices that aggregate the data into a single number. Each of these indices report a number between 0 to 100 that reflects the level of the governments response along certain dimensions. This is a measure of how many of the relevant indicators a government has acted upon, and to what degree. The index cannot say whether a government's policy has been implemented effectively."
Variation in US states' responses to COVID-19
"For US states, the indicators described above are aggregated into four policy indices, each of which measures a different set of government responses (the indicators that make up each index are listed in Table 2):
- A containment and health index, showing how many and how forceful the measures to contain the virus and protect citizen health are (this combines 'lockdown' restrictions and closures with health measures such as testing policy and contact tracing) *
- An economic support index, showing how much economic support has been made available (such as income support and debt relief)
- A stringency index, which records the strictness of 'lockdown style' closure and containment policies that primarily restrict people’s behavior
- An overall government response index which records how the response of states has varied over all indicators, capturing the full range of government responses
* Because the term "lockdown" is used in many different ways, we do not define this term here but instead refer to the number and restrictiveness of closure and containment policies."
Bucky Stats last imported the OxCGRT data on March 1, 2020. (I do hope to automate regular updates in the future.) Juxtaposed data lines based on all-cause mortality are from the weekly CDC datasets broken down by age groups — not the estimates included with the daily OxCGRT datasets.
Data Table
CSV ExcelState / Jurisdiction: |
Deaths per Million of U.S. 2019 Standardized Population | Overall Government Response Index | Containment and Health Index | Stringency Index | Economic Support Index | |||||
---|---|---|---|---|---|---|---|---|---|---|
Daily |
Daily Maximum | Daily Average | Daily Maximum | Daily Average | Daily Maximum | Daily Average | Daily Maximum | |||
New York | 9,752 | 28.3% | 59 | 78 | 56 | 74 | 58 | 80 | 78 | 100 |
Rhode Island | 9,887 | 15.5% | 55 | 73 | 52 | 71 | 55 | 80 | 69 | 88 |
California | 8,710 | 17.2% | 53 | 70 | 50 | 67 | 51 | 77 | 70 | 88 |
New Mexico | 10,498 | 20.6% | 51 | 72 | 55 | 78 | 60 | 84 | 29 | 38 |
Connecticut | 9,595 | 22.5% | 50 | 70 | 50 | 70 | 50 | 70 | 53 | 75 |
Vermont | 8,167 | 1.05% | 50 | 73 | 49 | 70 | 49 | 74 | 58 | 88 |
Hawaii | 7,056 | 2.53% | 49 | 75 | 52 | 77 | 58 | 80 | 32 | 63 |
Maine | 9,161 | 2.88% | 49 | 70 | 51 | 71 | 54 | 85 | 39 | 63 |
Delaware | 9,878 | 13.1% | 48 | 72 | 48 | 73 | 49 | 79 | 44 | 63 |
Kentucky | 12,680 | 14.1% | 46 | 73 | 48 | 74 | 49 | 88 | 37 | 63 |
Ohio | 11,797 | 17.1% | 45 | 60 | 47 | 63 | 47 | 71 | 28 | 38 |
Maryland | 10,065 | 17.5% | 45 | 69 | 45 | 72 | 48 | 88 | 39 | 50 |
Massachusetts | 9,316 | 14.2% | 45 | 64 | 48 | 74 | 48 | 69 | 20 | 38 |
New Jersey | 10,275 | 28.5% | 43 | 61 | 43 | 60 | 42 | 65 | 47 | 63 |
Illinois | 10,185 | 18.9% | 43 | 67 | 43 | 64 | 44 | 74 | 46 | 88 |
Alaska | 8,516 | 7.28% | 43 | 74 | 43 | 76 | 44 | 88 | 43 | 63 |
North Carolina | 8,266 | -12.4% | 43 | 59 | 43 | 61 | 46 | 72 | 38 | 63 |
Washington | 8,776 | 6.95% | 43 | 63 | 42 | 61 | 46 | 69 | 44 | 75 |
Pennsylvania | 10,674 | 15% | 42 | 64 | 43 | 67 | 42 | 77 | 38 | 50 |
Colorado | 9,339 | 16.8% | 42 | 63 | 40 | 60 | 42 | 74 | 52 | 88 |
Oregon | 9,051 | 5.74% | 41 | 59 | 40 | 59 | 43 | 70 | 48 | 63 |
Minnesota | 9,248 | 16.8% | 40 | 61 | 42 | 64 | 46 | 77 | 29 | 38 |
Virginia | 9,634 | 12.6% | 40 | 60 | 41 | 61 | 41 | 74 | 33 | 63 |
Michigan | 11,009 | 17.7% | 40 | 60 | 41 | 64 | 42 | 70 | 29 | 38 |
Arizona | 10,307 | 26.1% | 40 | 61 | 38 | 61 | 35 | 70 | 47 | 63 |
Montana | 10,126 | 15.6% | 39 | 66 | 41 | 66 | 40 | 77 | 28 | 63 |
New Hampshire | 8,770 | 5.76% | 39 | 68 | 41 | 69 | 40 | 77 | 25 | 63 |
Indiana | 11,885 | 17.6% | 38 | 57 | 39 | 56 | 37 | 71 | 38 | 63 |
South Carolina | 11,438 | 16.4% | 38 | 60 | 39 | 60 | 37 | 77 | 32 | 63 |
West Virginia | 12,129 | 9.52% | 37 | 60 | 41 | 63 | 43 | 74 | 14 | 38 |
Georgia | 11,183 | 16.3% | 37 | 56 | 37 | 57 | 39 | 60 | 37 | 50 |
Louisiana | 12,945 | 22.4% | 37 | 50 | 39 | 53 | 41 | 62 | 27 | 50 |
Wisconsin | 10,133 | 16.8% | 37 | 59 | 38 | 58 | 36 | 71 | 32 | 63 |
Florida | 9,192 | 14.5% | 37 | 61 | 38 | 62 | 40 | 74 | 32 | 50 |
Texas | 10,737 | 20.3% | 37 | 59 | 40 | 64 | 42 | 73 | 19 | 25 |
Wyoming | 9,347 | 14.8% | 37 | 59 | 39 | 65 | 38 | 75 | 25 | 50 |
Nevada | 10,847 | 17.7% | 37 | 57 | 38 | 56 | 38 | 69 | 29 | 63 |
Nebraska | 10,021 | 15.2% | 37 | 56 | 37 | 57 | 35 | 67 | 36 | 75 |
Arkansas | 12,253 | 15.3% | 36 | 58 | 38 | 57 | 36 | 63 | 24 | 63 |
Tennessee | 13,128 | 18.7% | 35 | 56 | 38 | 58 | 38 | 68 | 16 | 38 |
Alabama | 12,861 | 17.5% | 34 | 56 | 35 | 58 | 30 | 66 | 23 | 38 |
Kansas | 10,519 | 16% | 33 | 54 | 36 | 58 | 38 | 77 | 15 | 38 |
Iowa | 10,314 | 17.6% | 33 | 58 | 28 | 53 | 26 | 58 | 60 | 88 |
Mississippi | 13,475 | 19.3% | 32 | 51 | 34 | 53 | 36 | 65 | 20 | 63 |
Missouri | 12,128 | 20.3% | 32 | 50 | 35 | 54 | 36 | 69 | 12 | 25 |
Idaho | 9,742 | 13.3% | 31 | 57 | 34 | 62 | 38 | 85 | 8.22 | 25 |
Oklahoma | 12,058 | 13.6% | 30 | 55 | 32 | 59 | 30 | 71 | 14 | 25 |
United States | 10,248 | 16.6% | 30 | 41 | 30 | 38 | 32 | 42 | 31 | 63 |
Utah | 9,795 | 13.6% | 29 | 44 | 33 | 47 | 32 | 56 | 3.01 | 25 |
North Dakota | 11,000 | 27.3% | 27 | 46 | 29 | 48 | 28 | 55 | 12 | 38 |
South Dakota | 10,555 | 24.9% | 21 | 49 | 21 | 50 | 18 | 59 | 20 | 38 |
District of Columbia | 12,357 | 26.6% | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Graph #1
X: Overall Government Response Index: 2020 Daily Average
Y: 2020 Deaths per Million of U.S. 2019 Standardized Population
Graph #2
X: Overall Government Response Index: 2020 Daily Average
Y: Percent Increase of 2020 Standardized Mortality Over 2015-2019 Average
Graph #3
X: Overall Government Response Index: 2020 Daily Maximum
Y: 2020 Deaths per Million of U.S. 2019 Standardized Population
Graph #4
X: Overall Government Response Index: 2020 Daily Maximum
Y: Percent Increase of 2020 Standardized Mortality Over 2015-2019 Average
Graph #5
X: Containment and Health Index: 2020 Daily Average
Y: 2020 Deaths per Million of U.S. 2019 Standardized Population
Graph #6
X: Containment and Health Index: 2020 Daily Average
Y: Percent Increase of 2020 Standardized Mortality Over 2015-2019 Average
Graph #7
X: Stringency Index: 2020 Daily Average
Y: 2020 Deaths per Million of U.S. 2019 Standardized Population
Graph #8
X: Stringency Index: 2020 Daily Average
Y: Percent Increase of 2020 Standardized Mortality Over 2015-2019 Average
Graph #9
X: Economic Support Index: 2020 Daily Average
Y: 2020 Deaths per Million of U.S. 2019 Standardized Population
Graph #10
X: Economic Support Index: 2020 Daily Average
Y: Percent Increase of 2020 Standardized Mortality Over 2015-2019 Average
Example of Scaling Mortality to a Standard Age Group Distribution
The goal here is to somewhat control for changes in this population's demographics over time. This is just one big variable in the mix, but it is very important as there are many more people are living longer. A person's age range is not always known for every death. 10,000 per million equals 1%.
In 2000, United States had an estimated 2,403,196 deaths, or 8,557 per million.
2000 United States Estimated Population | 2000 United States Estimated Deaths | 2000 United States Crude | U.S. 2019 |
Estimated 2000 United States Deaths per
U.S. 2019 | |||
---|---|---|---|---|---|---|---|
98,951,074 | 71,650 | 0.07241% | x | 314,834 | = | 228 | |
25-44 | 85,006,908 | 130,249 | 0.1532% | x | 266,553 | = | 408 |
45-64 | 61,923,065 | 401,187 | 0.6479% | x | 253,873 | = | 1,645 |
65-74 | 18,383,891 | 441,209 | 2.4% | x | 96,197 | = | 2,309 |
75-84 | 12,356,498 | 700,445 | 5.669% | x | 49,172 | = | 2,787 |
85+ | 4,236,788 | 658,171 | 15.53% | x | 19,371 | = | 3,009 |
Total | 280,858,224 | 2,402,911 | 1,000,000 | 10,386 |
Data Sources
Population Statistics
2017-2019 — Population by United States Jurisdictions
United States Census Bureau. American Community Survey. ACS Demographic and Housing Estimates.
Available from:
data.census.gov/cedsci/table?q=United%20States&g=0100000US&tid=ACSDP1Y2019.DP05
1968-2016 — Population by United States Jurisdictions
National Center for Health Statistics. Mortality Data on CDC WONDER.
Available from: wonder.cdc.gov/mortSQL.html
1999-2016: wonder.cdc.gov/cmf-icd10.html
1979-1998: wonder.cdc.gov/cmf-icd9.html
1968-1978: wonder.cdc.gov/cmf-icd8.html
Vital Statistics
2015-2020 — All-Cause Mortality for United States Jurisdictions
Used for 2015-2020 weekly data, but only for 2017-2020 annual data.
National Center for Health Statistics. Weekly counts of deaths by jurisdiction and age group.
Available from:
data.cdc.gov/NCHS/Weekly-counts-of-deaths-by-jurisdiction-and-age-gr/y5bj-9g5w/
Weighted (predicted) provisional counts are used in these graphs. Data imported 3/1/21.
"Both unweighted and weighted (predicted) provisional counts are provided. Weighting of provisional counts is done to account for potential underreporting in the most recent weeks. However, data for the most recent week(s) are still likely to be incomplete. Only about 60% of deaths are reported within 10 days of the date of death, and there is considerable variation by jurisdiction and age. The completeness of provisional data varies by cause of death and by age group. However, the weights applied do not account for this variability. Therefore, the predicted numbers of deaths may be too low for some age groups and causes of death. For example, provisional data on deaths among younger age groups is typically less complete than among older age groups. Predicted counts may therefore be too low among the younger age groups. More detail about the methods, weighting, data, and limitations can be found in the Technical Notes."
1968-2016 — All-Cause Mortality for United States Jurisdictions
National Center for Health Statistics.
Compressed Mortality Data on CDC WONDER.
Available from: wonder.cdc.gov/mortSQL.html
1999-2016: wonder.cdc.gov/cmf-icd10.html
1979-1998: wonder.cdc.gov/cmf-icd9.html
1968-1978: wonder.cdc.gov/cmf-icd8.html
Government Policy Trackers
2020 — Oxford Covid-19 Government Response Tracker (OxCGRT) United States Data
Oxford University. Blavatnik School of Government.
Latest Data.
Available from:
github.com/OxCGRT/covid-policy-tracker
Data imported 3/1/21.
Variation in US states' responses to COVID-19
"For US states, the indicators described above are aggregated into four policy indices, each of which measures a different set of government responses (the indicators that make up each index are listed in Table 2):
- A containment and health index, showing how many and how forceful the measures to contain the virus and protect citizen health are (this combines 'lockdown' restrictions and closures with health measures such as testing policy and contact tracing) *
- An economic support index, showing how much economic support has been made available (such as income support and debt relief)
- A stringency index, which records the strictness of 'lockdown style' closure and containment policies that primarily restrict people’s behavior
- An overall government response index which records how the response of states has varied over all indicators, capturing the full range of government responses
* Because the term "lockdown" is used in many different ways, we do not define this term here but instead refer to the number and restrictiveness of closure and containment policies."