Reporting of new Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

Aggregate Data Collection Process Since the start of the COVID-19 pandemic, data have been gathered through a robust process with the following steps:

• A CDC data team reviews and validates the information obtained from jurisdictions’ state and local websites via an overnight data review process.
• If more than one official county data source exists, CDC uses a comprehensive data selection process comparing each official county data source, and takes the highest case and death counts respectively, unless otherwise specified by the state.
• CDC compiles these data and posts the finalized information on COVID Data Tracker.
• County level data is aggregated to obtain state and territory specific totals.

This process is collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provide the most up-to-date numbers on cases and deaths by report date. CDC may retrospectively update counts to correct data quality issues.

Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version:

• Source: The current Weekly-Updated Version is based on county-level aggregate count data, while the Archived Version is based on State-level aggregate count data.
• Confirmed/Probable Cases/Death breakdown:  While the probable cases and deaths are included in the total case and total death counts in both versions (if applicable), they were reported separately from the confirmed cases and deaths by jurisdiction in the Archived Version.  In the current Weekly-Updated Version, the counts by jurisdiction are not reported by confirmed or probable status (See Confirmed and Probable Counts section for more detail).
• Time Series Frequency: The current Weekly-Updated Version contains weekly time series data (i.e., one record per week per jurisdiction), while the Archived Version contains daily time series data (i.e., one record per day per jurisdiction).
• Update Frequency: The current Weekly-Updated Version is updated weekly, while the Archived Version was updated twice daily up to October 20, 2022.

Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report probable cases and deaths to CDC.* Confirmed and probable case definition criteria are described here:

Council of State and Territorial Epidemiologists (ymaws.com).

Deaths CDC reports death data on other sections of the website: CDC COVID Data Tracker: Home, CDC COVID Data Tracker: Cases, Deaths, and Testing, and NCHS Provisional Death Counts. Information presented on the COVID Data Tracker pages is based on the same source (total case counts) as the present dataset; however, NCHS Death Counts are based on death certificates that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Data from each of these pages are considered provisional (not complete and pending verification) and are therefore subject to change. Counts from previous weeks are continually revised as more records are received and processed.

Number of Jurisdictions Reporting There are currently 60 public health jurisdictions reporting cases of COVID-19. This includes the 50 states, the District of Columbia, New York City, the U.S. territories of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S Virgin Islands as well as three independent countries in compacts of free association with the United States, Federated States of Micronesia, Republic of the Marshall Islands, and Republic of Palau. New York State’s reported case and death counts do not include New York City’s counts as they separately report nationally notifiable conditions to CDC.

CDC COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths, available by state and by county. These and other data on COVID-19 are available from multiple public locations, such as:

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html

https://www.cdc.gov/covid-data-tracker/index.html

https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html

https://www.cdc.gov/coronavirus/2019-ncov/php/open-america/surveillance-data-analytics.html

Additional COVID-19 public use datasets, include line-level (patient-level) data, are available at: https://data.cdc.gov/browse?tags=covid-19.

Archived Data Notes:

November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 3, 2022, instead of the customary 7 days’ worth of data.

November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 10, 2022, instead of the customary 7 days’ worth of data.

November 10, 2022: Per the request of the jurisdiction, cases and deaths among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case and death counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases and deaths. 

November 17, 2022: Two new columns, weekly historic cases and weekly historic deaths, were added to this dataset on November 17, 2022. These columns reflect case and death counts that were reported that week but were historical in nature and not reflective of the current burden within the jurisdiction. These historical cases and deaths are not included in the new weekly case and new weekly death columns; however, they are reflected in the cumulative totals provided for each jurisdiction. These data are used to account for artificial increases in case and death totals due to batched reporting of historical data.

December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the data released on December 1, 2022.

January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case and death data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case and death metrics will appear higher than expected in the January 5, 2023, weekly release.

January 12, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0. As a result, case and death metrics will appear lower than expected in the January 12, 2023, weekly release.

January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case and death data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release.

January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties (Livingston and Washtenaw) were higher than expected in the January 19, 2023 weekly release.

January 26, 2023: Due to a backlog of historic COVID-19 cases being reported this week, aggregate case and death counts in Charlotte County and Sarasota County, Florida, will appear higher than expected in the January 26, 2023 weekly release.

January 26, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0 in the weekly release posted on January 26, 2023.

February 2, 2023: As of the data collection deadline, CDC observed an abnormally large increase in aggregate COVID-19 cases and deaths reported for Washington State. In response, totals for new cases and new deaths released on February 2, 2023, have been displayed as zero at the state level until the issue is addressed with state officials. CDC is working with state officials to address the issue.

February 2, 2023: Due to a decrease reported in cumulative case counts by Wyoming, case rates will be reported as 0 in the February 2, 2023, weekly release. CDC is working with state officials to verify the data submitted.

February 16, 2023: Due to data processing delays, Utah’s aggregate case and death data will be reported as 0 in the weekly release posted on February 16, 2023. As a result, case and death metrics will appear lower than expected and should be interpreted with caution.

February 16, 2023: Due to a reporting cadence change, Maine’s

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

Note: 11/1/2023: Publication of the COVID data will be delayed because of technical difficulties. Note: 9/20/2023: With the end of the federal emergency and reporting requirements continuing to evolve, the Indiana Department of Health will no longer publish and refresh the COVID-19 datasets after November 15, 2023 - one final dataset publication will continue to be available. Note: 5/10/2023: Due to a technical issue updates are delayed for COVID data. New files will be published as soon as they are available. Note: 3/22/2023: Due to a technical issue updates are delayed for COVID data. New files will be published as soon as they are available. Note: 3/15/2023 test data will be removed from the COVID dashboards and HUB files in recognition of the fact that widespread use of at-home tests and a decrease in lab testing no longer provides an accurate representation of COVID-19 spread. Number of Indiana COVID-19 cases and deaths by age group, gender, race and ethnicity by day. All data displayed is preliminary and subject to change as more information is reported to IDOH. Expect historical data to change as data is reported to IDOH. Historical Changes: 1/11/2023: Due to a technical issue updates are delayed for COVID data. New files will be published as soon as they are available. 1/5/2023: Due to a technical issue the COVID datasets were not updated on 1/4/23. Updates will be published as soon as they are available. 9/29/22: Due to a technical difficulty, the weekly COVID datasets were not generated yesterday. They will be updated with current data today - 9/29 - and may result in a temporary discrepancy with the numbers published on the dashboard until the normal weekly refresh resumes 10/5. 9/27/2022: As of 9/28, the Indiana Department of Health (IDOH) is moving to a weekly COVID update for the dashboard and all associated datasets to continue to provide trend data that is applicable and usable for our partners and the public. This is to maintain alignment across the nation as states move to weekly updates. 2/10/2022: Data was not published on 2/9/2022 due to a technical issue, but updated data was released 2/10/2022. 12/30/21: This dataset has been updated, and should continue to receive daily updates. 12/15/21: The file has been adjusted with data through 12/13, and regular updates will resume to it today. 11/12/2021: Historical re-infections have been added to the case counts for all pertinent COVID datasets back to 9/1/2021 and new re-infections will be added to the total case counts as they are reported in accordance with CDC guidance. 06/23/2021: COVID Hub files will no longer be updated on Saturdays. The normal refresh of these files has been changed to Mon-Fri. 06/10/2021: COVID Hub files will no longer be updated on Sundays. The normal refresh of these files has been changed to Mon-Sat. 6/03/2021 : A batch of historical negative and positive test results added 16,492 historical tests administered, 7,082 tested individuals, and 765 historical cases to today's counts. These cases are not included in the new positive counts but have been added to the total positive cases. Today’s total case counts include historical cases received from other states. 2/4/2021 : Today’s dataset now includes 1,507 historical deaths identified through an audit of 2020 and 2021 COVID death records and test results.

Daily count of NYC residents who tested positive for SARS-CoV-2, who were hospitalized with COVID-19, and deaths among COVID-19 patients.

Note that this dataset currently pulls from https://raw.githubusercontent.com/nychealth/coronavirus-data/master/case-hosp-death.csv on a daily basis.

United States recorded 1127152 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, United States reported 103436829 Coronavirus Cases. This dataset includes a chart with historical data for the United States Coronavirus Deaths.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

This archived public use dataset contains historical case and percent positivity data updated weekly for all available counties and jurisdictions. Each week, the dataset was refreshed to capture any historical updates. Please note, percent positivity data may be incomplete for the most recent time period.

Related data CDC provides the public with two active versions of COVID-19 county-level community transmission level data: this dataset with historical case and percent positivity data for each county from January 22, 2020 (Weekly Historical Changes dataset) and a dataset with the levels as originally posted (Weekly Originally Posted dataset) since October 20, 2022. Please navigate to the Weekly Originally Posted dataset for the Community Transmission Levels published weekly on Thursdays.

Methods for calculating county level of community transmission indicator The County Level of Community Transmission indicator uses two metrics: (1) total new COVID-19 cases per 100,000 persons in the last 7 days and (2) percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests (NAAT) in the last 7 days. For each of these metrics, CDC classifies transmission values as low, moderate, substantial, or high (below and here). If the values for each of these two metrics differ (e.g., one indicates moderate and the other low), then the higher of the two should be used for decision-making.

CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2 Total New Case Rate Metric: "New cases per 100,000 persons in the past 7 days" is calculated by adding the number of new cases in the county (or other administrative level) in the last 7 days divided by the population in the county (or other administrative level) and multiplying by 100,000. "New cases per 100,000 persons in the past 7 days" is considered to have transmission level of Low (0-9.99); Moderate (10.00-49.99); Substantial (50.00-99.99); and High (greater than or equal to 100.00).

Test Percent Positivity Metric: "Percentage of positive NAAT in the past 7 days" is calculated by dividing the number of positive tests in the county (or other administrative level) during the last 7 days by the total number of tests resulted over the last 7 days. "Percentage of positive NAAT in the past 7 days" is considered to have transmission level of Low (less than 5.00); Moderate (5.00-7.99); Substantial (8.00-9.99); and High (greater than or equal to 10.00).

The data in this dataset are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.

This dataset is created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access.

Archived data CDC has archived two prior versions of these datasets. Both versions contain the same 7 data elements reflecting community transmission levels for all available counties and jurisdictions; however, the datasets updated daily. The archived datasets can be found here:

Archived Originally Posted dataset

Archived Historical Changes dataset

Archived Data Notes:

October 27, 2022: Due to a processing issue this dataset will not be posted this week. CDC is currently working to address the issue and will publish the data when able.

November 10, 2022: As of 11/10/2022, this dataset will continue to incorporate historical updates made to case and percent positivity data; however, community transmission level will only be published in the corresponding Weekly COVID-19 County Level of Community Transmission as Originally Posted dataset (Weekly Originally Posted dataset).

Note:

October 20, 2022: Due to a data reporting error, the case rate for Philadelphia County, Pennsylvania is lower than expected in the COVID-19 Community Transmission Level data released on October 20, 2022. This could lead to the COVID-19 Community Transmission Level for Philadelphia County being underestimated; therefore, it should be interpreted with caution.

November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the COVID-19 Community Transmission Level data released on November 3, 2022, instead of the customary 7 days’ worth of data. This could lead to the COVID-19 Community Transmission Levels metrics for Missouri counties being overestimated; therefore, they should be interpreted with caution.

November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the COVID-19 Community Transmission Level data released on November 10, 2022, instead of the customary 7 days’ worth of data. This could lead to the COVID-19 Community Transmission Levels metrics for Alabama counties being overestimated; therefore, they should be interpreted with caution.

November 10, 2022: Per the request of the jurisdiction, cases among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases. 

November 10, 2022: In the COVID-19 Community Transmission Level data released on November 10, 2022, multiple municipalities in Puerto Rico are reporting higher than expected increases in case counts. CDC is working with territory officials to verify the data submitted. 

December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the COVID-19 Community Transmission Level data released on December 1, 2022. Therefore, the COVID-19 Community Transmission Levels may be underestimated and should be interpreted with caution. 

December 22, 2022: Due to an internal revision process, case rates for some Tennessee counties may appear higher than expected in the December 22, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for some Tennessee counties may be overestimated and should be interpreted with caution.

December 22, 2022: Due to reporting of a backlog of historic COVID-19 cases, case rates for some Louisiana counties will appear higher than expected in the December 22, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for some Louisiana counties may be overestimated and should be interpreted with caution.

December 29, 2022: Due to technical difficulties, county data from Alabama could not be incorporated via standard practices. As a result, case and death metrics will be reported as 0 in the December 29, 2022, weekly release. Therefore, the COVID-19 Community Transmission Levels metrics for Alabama counties will be underestimated and should be interpreted with caution.

January 5, 2023: Due to a reporting cadence issue, case rates for all Alabama counties will be calculated based on 14 days’ worth of case count data in the COVID-19 Community Transmission Level information released on January 5, 2023, instead of the customary 7 days’ worth of case count data. Therefore, the weekly case rates will be overestimated, which could affect counties’ COVID-19 Community Transmission Level classification and should be interpreted with caution.

January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case metrics will appear higher than expected in the January 5, 2023, weekly release. COVID-19 Community Transmission metrics may be overestimated and should be interpreted with caution.

January 12, 2023: Due to data processing delays, Mississippi’s aggregate case data will be reported as 0. As a result, case metrics will appear lower than expected in the January 12, 2023, weekly release. COVID-19 Community Transmission metrics may be underestimated and should be interpreted with caution. 

January 13, 2023: Aggregate case data released for Los Angeles County, California for the week of December 22nd, 2022, and December 29th, 2022, have been corrected for a data processing error.

January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release. Therefore, COVID-19 Community Transmission metrics may be overestimated and should be interpreted with caution.

January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties

Introducing national lockdowns is an effective strategy to contain the Covid-19 pandemic. In Austria, the first Covid-19-related lockdown was introduced on 15 March 2020 with most restrictions being lifted one month later. Seven months later, in November 2020, the second hard lockdown was implemented. The presented dataset contains data from the two waves of an online survey which aimed at comparing the perceptions and experiences of the general population related to the first two Covid-19 lockdowns in Austria. The first wave of data collection was conducted between 27 May and 16 June 2020, with all questions referring to the one-month lockdown period in Austria between 15 March and 15 April 2020. The second wave of data collection was conducted between 2 December and 9 December 2020 with questions referring to the second national lockdown in Austria between 17 November and 6 December 2020. In total 560 respondents were included in the first wave of the survey. Of these 560 participants, 228 provided their e-mail addresses and agreed to be contacted in the future. From the 228 persons who were re-contacted during the second wave of the survey, 141 responded among which 134 provided valid answers and were included in the dataset. Download and use of the data is conditional upon citation of the documents in any resulting work/publication as follows: Simon, J, Łaszewska, A, Helter, T (2021) Perceptions of Covid-19 lockdowns and related public health measures in Austria: Dataset, Version 10-03-2021, Department of Health Economics, Center for Public Health, Medical University of Vienna, Vienna. doi: 10.5281/zenodo.4598821 and Simon, J., Helter, T.M., White, R.G. et al. Impacts of the Covid-19 lockdown and relevant vulnerabilities on capability well-being, mental health and social support: an Austrian survey study. BMC Public Health 21, 314 (2021). https://doi.org/10.1186/s12889-021-10351-5 License: Creative Commons Attribution-NonCommercial 4.0 International Variables included in the dataset: 1. Demographic characteristics 2. Covid-19-related questions - Tested positive for Covid-19 or experienced Covid-19 symptoms - Indirect Covid-19 experience defined as having a friend and/or family member infected or knowing someone who died of Covid-19 - Quarantine or self-isolation in the past months - Concern about infection with SARS-CoV-2 - Concern about family member infected with SARS-CoV-2 3. Lockdown-related questions - Personal experiences of the Covid-19 lockdowns: threat to livelihood/income, more difficult than usual for to focus on work or normal, daily activities, being less busy than usual, feeling more isolated than usual, the lockdown restrictions are necessary to limit spread of the virus, understanding better what is really important in life, greater sense of appreciation for the healthcare workers, communicating with relatives more often, feeling that people have become more friendly towards other people, feeling more connected to the members of the local community - Perceptions of the necessity of public health measures during the first lockdown: commuting to and from work only when absolutely necessary, walks only with people living in the same household, closure of all non-essential business premises, only necessary purchases, no physical contact with family members outside the same household, mouth and nose protection in public spaces - Perceptions of the necessity of public health measures during the second lockdown: restrictions on leaving private living space, school closing and distance learning, closure of all non-essential shops and businesses, mouth and nose protection in public spaces, ban on events or restrictions in the event area, distance of one meter in public space for people from different households, physical contact only with closest relatives or individual caregivers, switch to homeoffice wherever possible, visits in nursing homes and hospitals once a week, commuting to and from work only when absolutely necessary - Complying with the public health measures during the first lockdown: walks only with people from the same household, only necessary purchases e.g. groceries, medication, no physical contact with family members outside the same household, mouth and nose protection in public spaces - Complying with the public health measures during the second lockdown: restrictions on leaving private living space, mouth and nose protection in public spaces, distance of one meter in public spaces for people from different households, physical contact only with closest relatives or individual caregivers, switch to homeoffice wherever possible - Impact of the lockdowns on different life domains: marriage, parenting, friendships, work, education, leisure activities, spirituality, community life, physical self-care {"references": ["Simon, J., Helter, T.M., White, R.G. et al. Impacts of the Covid-19 lockdown and relevant vulnerabilities on capability well-being, mental health and social suppo...

This dataset has been retired as of February 17, 2023. This dataset will be kept for historical purposes, but will no longer be updated. Similar data are available on the state’s open data portal: https://data.chhs.ca.gov/dataset/covid-19-time-series-metrics-by-county-and-state/resource/e2c6a86b-d269-4ce1-b484-570353265183. This dataset provides the daily & cumulative number of COVID-19 new confirmed cases, hospitalizations, and deaths among Marin County residents (does not include San Quentin inmates). Event Date corresponds to date that each status type occurred. For Confirmed Case this is Test Date, for Hospitalized this is Hospital Admit Date, and for Death it is the Date of Death. If a person first tested positive for COVID-19 on 11/1/2020, was admitted to the hospital on 11/15/2020, and died on 11/20/2020, their data would be contained in three rows for each status and event date. Note: as of 11/2/2021 hospitalization counts no longer includes in-patient hospitalizations with a COVID-19 positive test when the patient was in the hospital for a reason other than COVID-19. This can include in-patient stays due to labor/delivery, trauma, or emergency surgery. The previous definition of COVID-19 hospitalizations, counting all in-patient hospitalizations with a COVID-19 positive test, measured the burden of disease on hospital resources, while this updated definition is a more appropriate measure of disease severity among Marin County residents.

Cases are lab-confirmed COVID-19 cases reported to Marin County Public Health by providers, commercial laboratories, and academic laboratories, including reporting results through the California Reportable Disease Information Exchange. A lab-confirmed case is defined as detection of SARS-CoV-2 RNA in a clinical specimen using a molecular amplification detection test. For more information about data sources and methods please reference the FAQs.

This dataset reports the daily reported number of deaths involving COVID-19 by fatality type. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Total number of deaths involving COVID-19 * Number of deaths with “COVID-19 as the underlying cause of death” * Number of deaths with “COVID-19 contributed but not underlying cause” * Number of deaths where the “Cause of death unknown” or “Cause of death missing” ##Additional Notes The method used to count COVID-19 deaths has changed, effective December 1, 2022. Prior to December 1 2022, deaths were counted based on the date the death was updated in the public health unit’s system. Going forward, deaths are counted on the date they occurred. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. As of December 1, 2022, data are based on the date on which the death occurred. This reporting method differs from the prior method which is based on net change in COVID-19 deaths reported day over day. Data are based on net change in COVID-19 deaths for which COVID-19 caused the death reported day over day. Deaths are not reported by the date on which death happened as reporting may include deaths that happened on previous dates. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the number of deaths involving COVID-19 reported. "_Cause of death unknown_" is the category of death for COVID-19 positive individuals with cause of death still under investigation, or for which the public health unit was unable to determine cause of death. The category may change later when the cause of death is confirmed either as “COVID-19 as the underlying cause of death”, “COVID-19 contributed but not underlying cause,” or “COVID-19 unrelated”. "_Cause of death missing_" is the category of death for COVID-19 positive individuals with the cause of death missing in CCM. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

Status of COVID-19 cases in Ontario This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective April 13, 2023, this dataset will be discontinued. The public can continue to access the data within this dataset in the following locations updated weekly on the Ontario Data Catalogue: * Ontario COVID-19 testing percent positive by age group * Confirmed positive cases of COVID-19 in Ontario * Ontario COVID-19 testing metrics by Public Health Unit (PHU) * Ontario COVID-19 testing percent positive by age group * COVID-19 cases in hospital and ICU, by Ontario Health (OH) region * Cumulative deaths (new methodology) * Deaths Involving COVID-19 by Fatality Type For information on Long-Term Care Home COVID-19 Data, please visit: Long-Term Care Home COVID-19 Data. Data includes: * reporting date * daily tests completed * total tests completed * test outcomes * total case outcomes (resolutions and deaths) * current tests under investigation * current hospitalizations * current patients in Intensive Care Units (ICUs) due to COVID-related critical Illness * current patients in Intensive Care Units (ICUs) testing positive for COVID-19 * current patients in Intensive Care Units (ICUs) no longer testing positive for COVID-19 * current patients in Intensive Care Units (ICUs) on ventilators due to COVID-related critical illness * current patients in Intensive Care Units (ICUs) on ventilators testing positive for COVID-19 * current patients in Intensive Care Units (ICUs) on ventilators no longer testing positive for COVID-19 * Long-Term Care (LTC) resident and worker COVID-19 case and death totals * Variants of Concern case totals * number of new deaths reported (occurred in the last month) * number of historical deaths reported (occurred more than one month ago) * change in number of cases from previous day by Public Health Unit (PHU). This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations. ##Cumulative Deaths **Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool ** The methodology used to count COVID-19 deaths has changed to exclude deaths not caused by COVID. This impacts data captured in the columns “Deaths”, “Deaths_Data_Cleaning” and “newly_reported_deaths” starting with data for March 11, 2022. A new column has been added to the file “Deaths_New_Methodology” which represents the methodological change. The method used to count COVID-19 deaths has changed, effective December 1, 2022. Prior to December 1, 2022, deaths were counted based on the date the death was updated in the public health unit’s system. Going forward, deaths are counted on the date they occurred. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. A small number of COVID deaths (less than 20) do not have recorded death date and will be excluded from this file. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. ##Related dataset(s) * Confirmed positive cases of COVID-19 in Ontario

We collected county-level cumulative COVID-19 confirmed cases and death from Mar 25 to Nov 12, 2020, across the contiguous United States from USAFacts (usafacts.org). We considered Mar 25 to Jun 3 as the “1st wave”, Jun 4 to Sep 2 as the “2nd wave”, and Sep 3 to Nov 12 as the “3rd wave” of COVID-19. For the 2nd and 3rd waves, we analyzed the targeted counties in the sunbelt region (including AL, AZ, AR, CA, FL, GA, KS, LA, MS, NV, NM, NC, OK, SC, TX, TN, and UT states) and great plains region (including IA, IL, IN, KS, MI, MO, MN, ND, NE, OH, SD, and WI states), respectively. MIR, as a proxy for survival rate, is calculated by dividing the number of confirmed deaths in each county by the confirmed cases in the same county at the same time-period multiplied by 100. MIR ranges from 0%-100%, 100% indicating the worst situation where all confirmed cases have died.

Thirty-eight potential risk factors (covariates), including county-level MR of comorbidities & disorders, demographics & social factors, and environmental factors, were retrieved from the University of Washington Global Health Data Exchange (http://ghdx.healthdata.org/us-data). Comorbidities and disorders include CVD, cardiomyopathy and myocarditis and myocarditis, hypertensive heart disease, peripheral vascular disease, atrial fibrillation, cerebrovascular disease, diabetes, hepatitis, HIV/AIDS, tuberculosis (TB), lower respiratory infection, interstitial lung disease and pulmonary sarcoidosis, asthma, COPD, ischemia, mesothelioma, tracheal cancer, leukemia, pancreatic cancer, rheumatic disease, drug use disorder, and alcohol use disorder. Demographics & social factors include age, female African American%, female white American%, male African American%, male white American%, Asian%, smokers%, unemployed%, income rate, food insecurity, fair/poor health, and uninsured%. Environmental factors include county population density, air quality index (AQI), temperature, and PM. A descriptive table, including all potential risk factors, is provided in Table S1).

These indicators are designed to accompany the SHMI publication. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. There has been a fall in the number of spells for some trusts due to COVID-19 impacting on activity from March 2020 onwards and this appears to be an accurate reflection of hospital activity rather than a case of missing data. Contextual indicators on the number of provider spells which are excluded from the SHMI due to them being related to COVID-19 and on the number of provider spells as a percentage of pre-pandemic activity (January 2019 – December 2019) are produced to support the interpretation of the SHMI. These indicators are being published as experimental statistics. Experimental statistics are official statistics which are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. Notes: 1. There is a shortfall in the number of records for County Durham and Darlington NHS Foundation Trust (trust code RXP), East Lancashire Hospitals NHS Trust (trust code RXR), Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1), King’s College Hospital NHS Foundation Trust (trust code RJZ) and The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 3. There is a high percentage of invalid diagnosis codes for Barking, Havering and Redbridge University Hospitals NHS Trust (trust code RF4), Chesterfield Royal Hospital NHS Foundation Trust (trust code RFS), Milton Keynes University Hospital NHS Foundation Trust (trust code RD8) and Portsmouth Hospitals University NHS Trust (trust code RHU). Values for these trusts should therefore be interpreted with caution. 4. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 5. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

We collected county-level cumulative COVID-19 confirmed cases and death from Mar 25 to Nov 12, 2020, across the contiguous United States from USAFacts (usafacts.org). We considered Mar 25 to Jun 3 as the “1st wave”, Jun 4 to Sep 2 as the “2nd wave”, and Sep 3 to Nov 12 as the “3rd wave” of COVID-19. For the 2nd and 3rd waves, we analyzed the targeted counties in the sunbelt region (including AL, AZ, AR, CA, FL, GA, KS, LA, MS, NV, NM, NC, OK, SC, TX, TN, and UT states) and great plains region (including IA, IL, IN, KS, MI, MO, MN, ND, NE, OH, SD, and WI states), respectively. MIR, as a proxy for survival rate, is calculated by dividing the number of confirmed deaths in each county by the confirmed cases in the same county at the same time-period multiplied by 100. MIR ranges from 0%-100%, 100% indicating the worst situation where all confirmed cases have died.

Thirty-eight potential risk factors (covariates), including county-level MR of comorbidities & disorders, demographics & social factors, and environmental factors, were retrieved from the University of Washington Global Health Data Exchange (http://ghdx.healthdata.org/us-data). Comorbidities and disorders include CVD, cardiomyopathy and myocarditis and myocarditis, hypertensive heart disease, peripheral vascular disease, atrial fibrillation, cerebrovascular disease, diabetes, hepatitis, HIV/AIDS, tuberculosis (TB), lower respiratory infection, interstitial lung disease and pulmonary sarcoidosis, asthma, COPD, ischemia, mesothelioma, tracheal cancer, leukemia, pancreatic cancer, rheumatic disease, drug use disorder, and alcohol use disorder. Demographics & social factors include age, female African American%, female white American%, male African American%, male white American%, Asian%, smokers%, unemployed%, income rate, food insecurity, fair/poor health, and uninsured%. Environmental factors include county population density, air quality index (AQI), temperature, and PM. A descriptive table, including all potential risk factors, is provided in Table S1).

In low- and middle-income countries where SARS-CoV-2 testing is limited, seroprevalence studies can help describe and characterise the extent of the pandemic, as well as elucidate protection conferred by prior exposure. We conducted repeated cross-sectional serosurveys (July 2020 –November 2021) using residual samples from patients from Cape Town, South Africa, sent for routine laboratory studies for non-COVID-19 conditions. SARS-CoV-2 anti-nucleocapsid antibodies and linked clinical information were used to investigate: (1) seroprevalence over time and risk factors associated with seropositivity, (2) ecological comparison of seroprevalence between subdistricts, (3) case ascertainment rates, and (4) the relative protection against COVID-19 associated with seropositivity and vaccination statuses. Among the subset sampled, seroprevalence of SARS-CoV-2 in Cape Town increased from 39.19% (95% confidence interval [CI] 37.23–41.19) in July 2020 to 67.8% (95%CI 66.31–69.25) in November 2021. Poorer communities had both higher seroprevalence and COVID-19 mortality. Only 10% of seropositive individuals had a recorded positive SARS-CoV-2 test. Using COVID-19 hospital admission and death data at the Provincial Health Data Centre, antibody positivity before the start of the Omicron BA.1 wave (28 November 2021) was strongly protective for severe disease (adjusted odds ratio [aOR] 0.15; 95%CI 0.05–0.46), with additional benefit in those who were also vaccinated (aOR 0.07, 95%CI 0.01–0.35). The high population seroprevalence in Cape Town was attained at the cost of substantial COVID-19 mortality. At the individual level, seropositivity was highly protective against subsequent infections and severe COVID-19 disease. In low-income communities, where diagnostic testing capacity is often limited, surveillance systems dependent on them will underestimate the true extent of an outbreak. Rapidly conducted seroprevalence studies can play an important role in addressing this.

These indicators are designed to accompany the SHMI publication. The SHMI methodology does not make any adjustment for deprivation. This is because adjusting for deprivation might create the impression that a higher death rate for those who are more deprived is acceptable. Patient records are assigned to 1 of 5 deprivation groups (called quintiles) using the Index of Multiple Deprivation (IMD). The deprivation quintile cannot be calculated for some records e.g. because the patient's postcode is unknown or they are not resident in England. Contextual indicators on the percentage of provider spells and deaths reported in the SHMI belonging to each deprivation quintile are produced to support the interpretation of the SHMI. Notes: 1. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for County Durham and Darlington NHS Foundation Trust (trust code RXP), East Lancashire Hospitals NHS Trust (trust code RXR), Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1), King’s College Hospital NHS Foundation Trust (trust code RJZ) and The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 6. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

This indicator is designed to accompany the SHMI publication. The SHMI includes all deaths reported of patients who were admitted to non-specialist acute trusts in England and either died while in hospital or within 30 days of discharge. Deaths related to COVID-19 are excluded from the SHMI. A contextual indicator on the percentage of deaths reported in the SHMI which occurred in hospital and the percentage which occurred outside of hospital is produced to support the interpretation of the SHMI. Notes: 1. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for The Princess Alexandra Hospital NHS Trust (trust code RQW), Guy’s and St Thomas’ NHS Foundation Trust (RJ1), King’s College Hospital NHS Foundation Trust (RJZ), and East Lancashire Hospitals NHS Trust (RXR). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 6. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

These indicators are designed to accompany the SHMI publication. The SHMI methodology includes an adjustment for admission method. This is because crude mortality rates for elective admissions tend to be lower than crude mortality rates for non-elective admissions. Contextual indicators on the crude percentage mortality rates for elective and non-elective admissions where a death occurred either in hospital or within 30 days (inclusive) of being discharged from hospital are produced to support the interpretation of the SHMI. Notes: 1. As of the July 2020 publication, COVID-19 activity has been excluded from the SHMI. The SHMI is not designed for this type of pandemic activity and the statistical modelling used to calculate the SHMI may not be as robust if such activity were included. Activity that is being coded as COVID-19, and therefore excluded, is monitored in the contextual indicator 'Percentage of provider spells with COVID-19 coding' which is part of this publication. 2. Please note that there was a fall in the overall number of spells from March 2020 due to COVID-19 impacting on activity for England and the number has not returned to pre-pandemic levels. Further information at Trust level is available in the contextual indicator ‘Provider spells compared to the pre-pandemic period’ which is part of this publication. 3. There is a shortfall in the number of records for County Durham and Darlington NHS Foundation Trust (trust code RXP), East Lancashire Hospitals NHS Trust (trust code RXR), Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1), King’s College Hospital NHS Foundation Trust (trust code RJZ) and The Princess Alexandra Hospital NHS Trust (trust code RQW). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 4. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 5. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 6. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.