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TwitterNote: After May 3, 2024, this dataset will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, hospital capacity, or occupancy data to HHS through CDC’s National Healthcare Safety Network (NHSN). The related CDC COVID Data Tracker site was revised or retired on May 10, 2023.
This dataset represents weekly COVID-19 hospitalization data and metrics aggregated to national, state/territory, and regional levels. COVID-19 hospitalization data are reported to CDC’s National Healthcare Safety Network, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN and included in this dataset represent aggregated counts and include metrics capturing information specific to COVID-19 hospital admissions, and inpatient and ICU bed capacity occupancy.
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Metric details:
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TwitterThis dataset is not being updated as hospitals are no longer mandated to report COVID Hospitalizations to CDPH.
Data is from the California COVID-19 State Dashboard at https://covid19.ca.gov/state-dashboard/
Note: Hospitalization counts include all patients diagnosed with COVID-19 during their stay. This does not necessarily mean they were hospitalized because of COVID-19 complications or that they experienced COVID-19 symptoms.
Note: Cumulative totals are not available due to the fact that hospitals report the total number of patients each day (as opposed to new patients).
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TwitterNote: After May 3, 2024, this dataset will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. The related CDC COVID Data Tracker site was revised or retired on May 10, 2023.
This dataset represents daily COVID-19 hospitalization data and metrics aggregated to national, state/territory, and regional levels. COVID-19 hospitalization data are reported to CDC’s National Healthcare Safety Network, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN and included in this dataset represent aggregated counts and include metrics capturing information specific to COVID-19 hospital admissions, and inpatient and ICU bed capacity occupancy.
Reporting information:
Metric details:
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TwitterAs of May 2022, these datasets moved from daily updates to weekly updates every Monday. A break down by census categories of the hospitalizations to date within the city limits.
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TwitterIn the United States between February 12 and March 16, 2020, the percentage of COVID-19 patients hospitalized with the disease increased with age. Findings estimated that up to 70 percent of adults aged 85 years and older were hospitalized.
Who is at higher risk from COVID-19? The same study also found that coronavirus patients aged 85 and older were at the highest risk of death. There are other risk factors besides age that can lead to serious illness. People with pre-existing medical conditions, such as diabetes, heart disease, and lung disease, can develop more severe symptoms. In the U.S. between January and May 2020, case fatality rates among confirmed COVID-19 patients were higher for those with underlying health conditions.
How long should you self-isolate? As of August 24, 2020, more than 16 million people worldwide had recovered from COVID-19 disease, which includes patients in health care settings and those isolating at home. The criteria for discharging patients from isolation varies by country, but asymptomatic carriers of the virus can generally be released ten days after their positive case was confirmed. For patients showing signs of the illness, they must isolate for at least ten days after symptom onset and also remain in isolation for a short period after the symptoms have disappeared.
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TwitterNote: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, hospitalizations, and associated deaths that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Hospitalization data were collected by the Connecticut Hospital Association and reflect the number of patients currently hospitalized with laboratory-confirmed COVID-19. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported d
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TwitterAs of September 26, the hospitalization rate in the United States due to COVID-19 was highest for those aged 85 years and older. This statistic shows the cumulative rate of laboratory-confirmed COVID-19-associated hospitalizations in the U.S. as of September 26, 2020, by age group.
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TwitterThe dashboard is updated each Friday.
Laboratory surveillance data: California laboratories report SARS-CoV-2 test results to CDPH through electronic laboratory reporting. Los Angeles County SARS-CoV-2 lab data has a 7-day reporting lag. Test positivity is calculated using SARS-CoV-2 lab tests that has a specimen collection date reported during a given week. Specimens for testing are collected from patients in healthcare settings and do not reflect all testing for COVID-19 in California. Test positivity for a given week is calculated by dividing the number of positive COVID-19 results by the total number of specimens tested for that virus. Weekly laboratory surveillance data are defined as Sunday through Saturday.
Hospitalization data: Data on COVID-19 and influenza hospital admissions are from Centers for Disease Control and Prevention’s (CDC) National Healthcare Safety Network (NHSN) Hospitalization dataset. The requirement to report COVID-19-associated hospitalizations was effective November 1, 2024. CDPH pulls NHSN data from the CDC on the Wednesday prior to the publication of the report. Results may differ depending on which day data are pulled. Admission rates are calculated using population estimates from the P-3: Complete State and County Projections Dataset (https://dof.ca.gov/forecasting/demographics/projections/) provided by the State of California Department of Finance. Reported weekly admission rates for the entire season use the population estimates for the year the season started. For more information on NHSN data including the protocol and data collection information, see the CDC NHSN webpage (https://www.cdc.gov/nhsn/index.html). Weekly hospitalization data are defined as Sunday through Saturday.
Death certificate data: CDPH receives weekly year-to-date dynamic data on deaths occurring in California from the CDPH Center for Health Statistics and Informatics. These data are limited to deaths occurring among California residents and are analyzed to identify COVID-19-coded deaths. These deaths are not necessarily laboratory-confirmed and are an underestimate of all COVID-19-associated deaths in California. Weekly death data are defined as Sunday through Saturday.
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TwitterDaily 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/trends/data-by-day.csv on a daily basis.
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TwitterAs of June 10, 2023, the cumulative hospitalization rate in the United States due to COVID-19 was lowest for Non-Hispanic Asian or Pacific Islanders and highest among Non-Hispanic American Indian or Alaska Natives. This statistic shows the cumulative rate of laboratory-confirmed COVID-19-associated hospitalizations in the U.S. as of June 10, 2023, by race and ethnicity.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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This dataset details the percentage of COVID-19 positive patients in hospitals and ICUs for COVID-19 related reasons, and for reasons other than COVID-19. Data includes: * reporting date * percentage of COVID-19 positive patients in hospital admitted for COVID-19 * percentage of COVID-19 positive patients in hospital admitted for other reasons * percentage of COVID-19 positive patients in ICU admitted for COVID-19 * percentage of COVID-19 positive patients in ICU admitted for other reasons **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 ** Due to incomplete weekend and holiday reporting, data for hospital and ICU admissions are not updated on Sundays, Mondays and the day after holidays. This dataset is subject to change.
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TwitterView metadata for key information about this dataset. This data is for public consumption. To protect the confidentiality of residents, PDPH suppresses the exact data for any categories that have fewer than 6 counts (i.e. of tests or fatalities). For greatest accuracy, please use the latest dataset for all analysis and reporting as opposed to any data you downloaded prior to September 29, 2020. All datasets now reflect counts from test collection dates instead of the previously displayed result dates. These changes will adjust, for example, the count of cases for each day. PDPH has also added 376 confirmed COVID-19 cases (positive tests) that were previously missing from the data. See also the following related datasets:COVID Hospitalizations by AgeCOVID Hospitalizations by DateCOVID Hospitalizations by RaceCOVID Hospitalizations by SexCOVID Hospitalizations by ZIP CodeFor questions about this dataset, contact publichealthinfo@phila.gov. For technical assistance, email maps@phila.gov.
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TwitterNOTE: This dataset has been retired and marked as historical-only.
Only Chicago residents are included based on the home ZIP Code, as provided by the medical provider, or the address, as provided by the Cook County Medical Examiner.
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted on the date the test specimen was collected. Deaths are those occurring among cases based on the day of death. Hospitalizations are based on the date of first hospitalization. Only one hospitalization is counted for each case. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.
Because of the nature of data reporting to CDPH, hospitalizations will be blank for recent dates They will fill in on later updates when the data are received, although, as for cases and deaths, may continue to be updated as further data are received.
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH.
Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases, deaths, and hospitalizations, sources used, how cases, deaths and hospitalizations are associated to a specific date, and similar factors.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office
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TwitterView metadata for key information about this dataset. This data is for public consumption. To protect the confidentiality of residents, PDPH suppresses the exact data for any categories that have fewer than 6 counts (i.e. of tests or fatalities). For greatest accuracy, please use the latest dataset for all analysis and reporting as opposed to any data you downloaded prior to September 29, 2020. All datasets now reflect counts from test collection dates instead of the previously displayed result dates. These changes will adjust, for example, the count of cases for each day. PDPH has also added 376 confirmed COVID-19 cases (positive tests) that were previously missing from the data. See also the following related datasets:COVID Hospitalizations by AgeCOVID Hospitalizations by RaceCOVID Hospitalizations by SexCOVID Hospitalizations by WeekCOVID Hospitalizations by ZIP CodeFor questions about this dataset, contact publichealthinfo@phila.gov. For technical assistance, email maps@phila.gov.
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Twitterhttps://www.usa.gov/government-workshttps://www.usa.gov/government-works
The Coronavirus Disease 2019 (COVID-19) Hospitalization Surveillance Network (COVID-NET) a network that conducts active, population-based surveillance for laboratory-confirmed COVID-19-associated hospitalizations among children and adults. COVID-NET, along with the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET) and the Influenza Hospitalization Surveillance Network (FluSurv-NET), comprise the Respiratory Virus Hospitalization Surveillance Network (RESP-NET). The RESP-NET platforms have overlapping surveillance areas and use similar methods to collect data. COVID-NET is CDC’s source for important data on rates of hospitalizations associated with COVID-19. Hospitalization rates show how many people in the surveillance area are hospitalized with COVID-19, compared to the total number of people residing in that area.
Data are preliminary and subject to change as more data become available. Data will be updated weekly.
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TwitterView metadata for key information about this dataset. This data is for public consumption. To protect the confidentiality of residents, PDPH suppresses the exact data for any categories that have fewer than 6 counts (i.e. of tests or fatalities). For greatest accuracy, please use the latest dataset for all analysis and reporting as opposed to any data you downloaded prior to September 29, 2020. All datasets now reflect counts from test collection dates instead of the previously displayed result dates. These changes will adjust, for example, the count of cases for each day. PDPH has also added 376 confirmed COVID-19 cases (positive tests) that were previously missing from the data. See also the following related datasets:COVID Hospitalizations by DateCOVID Hospitalizations by RaceCOVID Hospitalizations by SexCOVID Hospitalizations by WeekCOVID Hospitalizations by ZIP CodeFor questions about this dataset, contact publichealthinfo@phila.gov. For technical assistance, email maps@phila.gov.
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TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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As of 9/12/2024, we will begin reporting on hospitalization data again using a new San Francisco specific dataset. Updated data can be accessed here.
On 5/1/2024, hospitalization data reporting will change from mandatory to optional for all hospitals nationwide. We will be pausing the refresh of the underlying data beginning 5/2/2024.
A. SUMMARY Count of COVID+ patients admitted to the hospital. Patients who are hospitalized and test positive for COVID-19 may be admitted to an acute care bed (a regular hospital bed), or an intensive care unit (ICU) bed. This data shows the daily total count of COVID+ patients in these two bed types, and the data reflects totals from all San Francisco Hospitals.
B. HOW THE DATASET IS CREATED Hospital information is based on admission data reported to the National Healthcare Safety Network (NHSN) and provided by the California Department of Public Health (CDPH).
C. UPDATE PROCESS Updates automatically every week.
D. HOW TO USE THIS DATASET Each record represents how many people were hospitalized on the date recorded in either an ICU bed or acute care bed (shown as Med/Surg under DPHCategory field).
The dataset shown here includes all San Francisco hospitals and updates weekly with data for the past Sunday-Saturday as information is collected and verified. Data may change as more current information becomes available.
E. CHANGE LOG
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
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NOTE: This layer is deprecated (last updated 3/14/2022). This was formerly a daily update.
Summary The cumulative number of COVID-19 positive Maryland residents who have been hospitalized.
Description The MD COVID-19 - Total Hospitalizations data layer is a collection of the statewide cumulative total of individuals who tested positive for COVID-19 that have been reported each day by each local health department as having been hospitalized. As published to coronavirus.maryland.gov, this is the "Ever Hospitalized" number. "Ever Hospitalized" refers to the cumulative number of individuals who were admitted to the hospital at some point during their COVID-19 illness.
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.
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TwitterNOTE: This dataset has been retired and marked as historical-only.
This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.
All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.
Only Chicago residents are included based on the home address as provided by the medical provider.
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.
Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.
Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey
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TwitterFrom March to December 2020, around 50 percent of adults hospitalized for COVID-19 in the U.S. were obese with a BMI of 30 kg/m2 or greater. This statistic illustrates the distribution of hospitalizations among adults with COVID-19 in the United States from March to December 2020, by body mass index.
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TwitterNote: After May 3, 2024, this dataset will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, hospital capacity, or occupancy data to HHS through CDC’s National Healthcare Safety Network (NHSN). The related CDC COVID Data Tracker site was revised or retired on May 10, 2023.
This dataset represents weekly COVID-19 hospitalization data and metrics aggregated to national, state/territory, and regional levels. COVID-19 hospitalization data are reported to CDC’s National Healthcare Safety Network, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN and included in this dataset represent aggregated counts and include metrics capturing information specific to COVID-19 hospital admissions, and inpatient and ICU bed capacity occupancy.
Reporting information:
Metric details: