Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

NOTE: This dataset is no longer being updated as of 4/27/2023. It is retired and no longer included in public COVID-19 data dissemination. See this link for more information https://imap.maryland.gov/pages/covid-data Summary The cumulative number of positive COVID-19 cases among Maryland residents within a single Maryland ZIP code. Description The MD COVID-19 - Cases by ZIP data layer is a collection of positive COVID-19 test results that have been reported each day by the local health department via the NEDSS system. Upon reaching a limit to the Socrata Platform, we decided to break the data into two parts. We now have "MD COVID-19 - Cases by ZIP Code Archive (2022)", "MD COVID-19 - Cases by ZIP Code Archive (2021)", and "MD COVID-19 - Cases by ZIP Code Archive (2020)". Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata. Case data aggregates to ZIP Codes do not reflect cases with missing, out of state, or incorrect ZIP Codes. Therefore, statewide totals of aggregate ZIP Code data may not match other statewide aggregate totals.

From 20 October 2023, COVID-19 datasets will no longer be updated. Detailed information is available in the fortnightly NSW Respiratory Surveillance Report: https://www.health.nsw.gov.au/Infectious/covid-19/Pages/reports.aspx.
Latest national COVID-19 spread, vaccination and treatment metrics are available on the Australian Government Health website: https://www.health.gov.au/topics/covid-19/reporting?language=und

COVID-19 cases by notification date and postcode, local health district, and local government area. The dataset is updated weekly on Fridays.

The data is for confirmed COVID-19 cases only based on location of usual residence, not necessarily where the virus was contracted.

Case counts reported by NSW Health for a particular notification date may vary over time due to ongoing investigations and the outcome of cases under review thus this dataset and any historical data contained within is subject to change on a daily basis.

The underlying dataset was assessed to measure the risk of identifying an individual and the level of sensitivity of the information gained if it was known that an individual was in the dataset. The dataset was then treated to mitigate these risks, including suppressing and aggregating data.

This dataset does not include cases with missing location information.

COVID-19 cases by notification date and postcode, local health district, local government area and likely source of infection. The dataset is updated daily, except on weekends. The data is for …Show full descriptionCOVID-19 cases by notification date and postcode, local health district, local government area and likely source of infection. The dataset is updated daily, except on weekends. The data is for confirmed COVID-19 cases only based on location of usual residence, not necessarily where the virus was contracted. The case definition of a confirmed case is a person who tests positive to a validated specific SARS-CoV-2 nucleic acid test or has the virus identified by electron microscopy or viral culture, at a reference laboratory. Data reported at 8pm daily. Case counts reported by NSW Health for a particular notification date may vary over time due to ongoing investigations and the outcome of cases under review thus this dataset and any historical data contained within is subject to change on a daily basis. The underlying dataset was assessed to measure the risk of identifying an individual and the level of sensitivity of the information gained if it was known that an individual was in the dataset. The dataset was then treated to mitigate these risks, including suppressing and aggregating data.

From 20 October 2023, COVID-19 datasets will no longer be updated. Detailed information is available in the fortnightly NSW Respiratory Surveillance Report: https://www.health.nsw.gov.au/Infectious/covid-19/Pages/reports.aspx. Latest national COVID-19 spread, vaccination and treatment metrics are available on the Australian Government Health website: https://www.health.gov.au/topics/covid-19/reporting?language=und

COVID-19 tests by date and postcode, local health district, local government area and result.

The data is for people tested for COVID-19 and is based on location of residence reported at the time of the test. A surge in total number of tests performed on a particular day may occur as the test results are updated in batches and new laboratories gain testing capacity.

The underlying dataset was assessed to measure the risk of identifying an individual and the level of sensitivity of the information gained if it was known that an individual was in the dataset. The dataset was then treated to mitigate these risks, including suppressing and aggregating data.

Background Rural U.S. communities are at risk from COVID-19 due to advanced age and limited access to acute care. Recognizing this, the Vashon Medical Reserve Corps (VMRC) in King County, Washington, implemented an all-volunteer, community-based COVID-19 response program. This program integrated public engagement, SARS-CoV-2 testing, contact tracing, vaccination, and material community support, and was associated with the lowest cumulative COVID-19 case rate in King County. This study aimed to investigate the contributions of demographics, geography and public health interventions to Vashon’s low COVID-19 rates. Methods This observational cross-sectional study compares cumulative COVID-19 rates and success of public health interventions from February 2020 through November 2021 for Vashon Island with King County (including metropolitan Seattle) and Whidbey Island, located ~50 km north of Vashon. To evaluate the role of demography, we developed multiple linear regression models of COVID-19 rates using metrics of age, race/ethnicity, wealth and educational attainment across 77 King County zip codes. To investigate the role of remote geography we expanded the regression models to include North, Central and South Whidbey, similarly remote island communities with varying demographic features. To evaluate the effectiveness of VMRC’s community-based public health measures, we directly compared Vashon’s success of vaccination and contact tracing with that of King County and South Whidbey, the Whidbey community most similar to Vashon. Results Vashon’s cumulative COVID-19 case rate was 29% that of King County overall (22.2 vs 76.8 cases/K). A multiple linear regression model based on King County demographics found educational attainment to be a major correlate of COVID-19 rates, and Vashon’s cumulative case rate was just 38% of predicted (p<.05), so demographics alone do not explain Vashon’s low COVID-19 case rate. Inclusion of Whidbey communities in the model identified a major effect of remote geography (-49 cases/K, p<.001), such that observed COVID-19 rates for all remote communities fell within the model’s 95% prediction interval. VMRC’s vaccination effort was highly effective, reaching a vaccination rate of 1500 doses/K four months before South Whidbey and King County and maintaining a cumulative vaccination rate 200 doses/K higher throughout the latter half of 2021 (p<.001). Including vaccination rates in the model reduced the effect of remote geography to -41 cases/K (p<.001). VMRC case investigation was also highly effective, interviewing 96% of referred cases in an average of 1.7 days compared with 69% in 3.7 days for Washington Department of Health investigating South Whidbey cases and 80% in 3.4 days for Public Health–Seattle & King County (both p<0.001). VMRC’s public health interventions were associated with a 30% lower case rate (p<0.001) and 55% lower hospitalization rate (p=0.056) than South Whidbey. Conclusion While the overall magnitude of the pre-Omicron COVID-19 pandemic in rural and urban U.S. communities was similar, we show that island communities in the Puget Sound region were substantially protected from COVID-19 by their geography. We further show that a volunteer community-based COVID-19 response program was highly effective in the Vashon community, augmenting the protective effect of geography. We suggest that Medical Reserve Corps should be an important element of future pandemic planning. Methods The study period extended from the pandemic onset in February 2020 through November 2021. Daily COVID-19 cases, hospitalizations, deaths and test numbers for King County as a whole and by zip code were downloaded from the King County COVID-19 dashboard (Feb 22, 2022 update). Population data for King County and Vashon are from the April 2020 US Census. Zip code level population data are the average of two zip code tabulation area estimates from the WA Office of Financial Management and Cubit (a commercial data vendor providing access to US Census information). The Asset Limited, Income Constrained, and Employed (ALICE) metric, a measure of the working poor, was obtained from United Way.