A Certificate of Convenience and Necessity (CCN) is issued by the Public Utility Commission of Texas (PUCT), and authorizes a utility to provide water and/or sewer service to a specific service area. The CCN obligates the water or sewer retail public utility to provide continuous and adequate service to every customer who requests service in that area. The maps and digital data provided in the Water and Sewer CCN Viewer delineate the official CCN service areas and CCN facility lines issued by the PUCT and its predecessor agencies. This dataset is a Texas statewide polygon layer of sewer CCN service areas. The CCNs were digitized from Texas Department of Transportation (TxDOT) county mylar maps. The mylar maps were the base maps on which the CCNs were originally drawn and maintained. CCNs are currently created and maintained using digitizing methods, coordinate geography or imported from digital files submitted by the applicant. TxDOT digital county urban road files are used as the base maps on which the CCNs are geo-referenced. It is best to view the sewer CCN service area data in conjunction with the sewer CCN facility line data, since these two layers together represent all of the retail public sewer utilities in Texas.*Important Notes: The CCN spatial dataset and metadata were last updated on: October 4, 2022The official state-wide CCN spatial dataset includes all types of CCN services areas: water and sewer CCN service areas; water and sewer CCN facility lines. This CCN spatial dataset is updated on a quarterly, or as needed basis using Geographic Information System (GIS) software called ArcGIS 10.8.2.The complete state-wide CCN spatial dataset is available for download from the following website: http://www.puc.texas.gov/industry/water/utilities/gis.aspxThe Water and Sewer CCN Viewer may be accessed from the following web site: http://www.puc.texas.gov/industry/water/utilities/map.htmlIf you have questions about this CCN spatial dataset or about CCN mapping requirements, please e-mail CCN Mapping Staff: water@puc.texas.govTYPE - Indicates whether a CCN is considered a water or a sewer system. If the CCN number begins with a '"1", the CCN is considered a water system (utility). If a CCN number begins with a "2", the CCN is considered a sewer system (utility).CCN_NO - A unique five-digit number assigned to each CCN when it is created and approved by the Commission. *CCN number starting with an ‘N’ indicates an exempt utility.UTILITY - The name of the utility which owns the CCN.COUNTY - The name(s) of the county(ies) in which the CCN exist.CCN_TYPE –One of three types:Bounded Service Area: A certificated service area with closed boundaries that often follow identifiable physical and cultural features such as roads, rivers, streams and political boundaries. Facilities +200 Feet: A certificated service area represented by lines. They include a buffer of a specified number of feet (usually 200 feet). The lines normally follow along roads and may or may not correspond to distribution lines or facilities in the ground.Facilities Only: A certificated service area represented by lines. They are granted for a "point of use" that covers only the customer connections at the time the CCN is granted. Facility only service lines normally follow along roads and may or may not correspond to distribution lines or facilities in the ground.STATUS – For pending dockets check the PUC Interchange Filing Search

A Certificate of Convenience and Necessity (CCN) is issued by the PUCT, and authorizes a utility to provide water and/or sewer service to a specific service area. The CCN obligates the water or sewer retail public utility to provide continuous and adequate service to every customer who requests service in that area. The maps and digital data provided in the Water and Sewer CCN Viewer delineate the official CCN service areas and CCN facility lines issued by the PUCT and its predecessor agencies.This dataset is a Texas statewide polyline layer of water CCN facility lines. The CCNs were digitized from Texas Department of Transportation (TxDOT) county mylar maps. The mylar maps were the base maps on which the CCNs were originally drawn and maintained. CCNs are currently created and maintained using digitizing methods, coordinate geography or imported from digital files submitted by the applicant. TxDOT digital county urban road files are used as the base maps on which the CCNs are geo-referenced.This dataset is a Texas statewide polyline layer of water Certificates of Convenience and Necessity (CCN) facility lines. This type of CCN may either be a Facilities Only (F0), a CCN Facility line (point of use) service area that covers only the customer connections at the time the CCN was granted, or Facilities plus a specified number of feet (usually 200 feet buffer) around the facility line. It is best to view the water CCN facility lines in conjunction with the water CCN service areas, since these two layers together represent all of the retail public water utilities in Texas.*Important Notes: The CCN spatial dataset and metadata were last updated on: October 4, 2022The official state-wide CCN spatial dataset includes all types of CCN services areas: water and sewer CCN service areas; water and sewer CCN facility lines. This CCN spatial dataset is updated on a quarterly, or as needed basis using Geographic Information System (GIS) software called ArcGIS 10.8.2.The complete state-wide CCN spatial dataset is available for download from the following website: http://www.puc.texas.gov/industry/water/utilities/gis.aspxThe Water and Sewer CCN Viewer may be accessed from the following web site: http://www.puc.texas.gov/industry/water/utilities/map.htmlIf you have questions about this CCN spatial dataset or about CCN mapping requirements, please e-mail CCN Mapping Staff: water@puc.texas.govTYPE - Indicates whether a CCN is considered a water or a sewer system. If the CCN number begins with a '"1", the CCN is considered a water system (utility). If a CCN number begins with a "2", the CCN is considered a sewer system (utility).CCN_NO - A unique five-digit number assigned to each CCN when it is created and approved by the Commission. *CCN number starting with an ‘N’ indicates an exempt utility.UTILITY - The name of the utility which owns the CCN.COUNTY - The name(s) of the county(ies) in which the CCN exist.CCN_TYPE –One of three types:Bounded Service Area: A certificated service area with closed boundaries that often follow identifiable physical and cultural features such as roads, rivers, streams and political boundaries. Facilities +200 Feet: A certificated service area represented by lines. They include a buffer of a specified number of feet (usually 200 feet). The lines normally follow along roads and may or may not correspond to distribution lines or facilities in the ground.Facilities Only: A certificated service area represented by lines. They are granted for a "point of use" that covers only the customer connections at the time the CCN is granted. Facility only service lines normally follow along roads and may or may not correspond to distribution lines or facilities in the ground.STATUS – For pending dockets check the PUC Interchange Filing Search

Cloud Condensation Nuclei (CCN) data: A Droplet Measurement Technologies (DMT) single-column continuous-flow streamwise thermal gradient chamber (CFSTGC; Roberts and Nenes, 2005) was deployed at the measurement site Weissfluhjoch (2700 m a.s.l., LON: 9.806475, LAT: 46.832964) to record the in-situ CCN number concentrations between February 24 and March 8 2019 for different supersaturations (SS). To account for the difference between the ambient (~735 mbar) and the calibration pressure (~800 mbar), the SS reported by the instrument is adjusted by a factor of 0.92. The CFSTGC was cycled between 6 discrete SS values ranging from 0.09% to 0.74%, producing a full CCN spectrum every hour. The raw CCN measurements are filtered to discount periods of transient operation and whenever the room temperature housing the instrument changed sufficiently to induce a reset in column temperature. Additional information can be found in Section 2.1.2 here. Hygroscopicity data: The CCN number concentration measurements were directly related to the size distribution and total aerosol concentration data measured by the Scanning Mobility Particle Size Spectrometer (SMPS) instrument at the same station (https://www.envidat.ch/dataset/aerosol-data-weissfluhjoch) to infer the particles hygroscopicity parameter (kappa). For each SMPS scan, the particles critical dry diameter (Dcr) is estimated by integrating backward the SMPS size distribution, until the aerosol number matches the CCN concentration observed for the same time period as the SMPS scan. Assuming the particle chemical composition is internally mixed, the kappa is determined from Dcr and SS, applying Köhler theory. Additional information can be found in Section 2.2 here. Predicted cloud droplet numbers: Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from the SMPS instrument deployed at Weissfluhjoch. The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at Davos Wolfgang and are extracted for the altitude of interest, being 1100 m above ground level for Weissfluhjoch. Additional information can be found in Section 2.3 here.

After May 3, 2024, this dataset and webpage 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. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations.

This file helps define the HHS_ID column that is published in both the

'COVID-19 Reported Patient Impact and Hospital Capacity by Facility' found here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u

COVID-19 Reported Patient Impact and 'Hospital Capacity by Facility -- RAW' found here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb

As a part of an effort to improve the granularity of spatial data, unique identifiers (named “HHS IDs” in the datasets) have been assigned to each individual facility. These unique identifiers are provided so data users can reference each individual “brick and mortar” facility that is reporting data to HHS, even in cases when multiple facilities report under the same CMS Certification Number (CCN). Additional datasets and further details related to HHS IDs will be released at a later date.

With this file, you can associate the reporting facility with its physical location(s).

On October 8, 2021, this file will now include the HHS IDs for Psychiatric, Rehabilitation and Behavioral hospitals, as well as Ambulatory Surgical Centers and Free Standing Emergency departments wherever these institutions are reporting under https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf

Starting on January 6, 2023, this dataset will no longer be posted on weekends.

As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRA, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000. JRA worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties. A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights. Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.

Note: This web page provides data on health facilities only. To file a complaint against a facility, please see: https://www.cdph.ca.gov/Programs/CHCQ/LCP/Pages/FileAComplaint.aspx

The California Department of Public Health (CDPH), Center for Health Care Quality, Licensing and Certification (L&C) Program licenses and certifies more than 30 types of healthcare facilities. The Electronic Licensing Management System (ELMS) is a CDPH data system created to manage state licensing-related data and enforcement actions. This file includes California healthcare facilities that are operational and have a current license issued by the CDPH and/or a current U.S. Department of Health and Human Services’ Centers for Medicare and Medicaid Services (CMS) certification.

To link the CDPH facility IDs with those from other Departments, like HCAI, please reference the "Licensed Facility Cross-Walk" Open Data table at https://data.chhs.ca.gov/dataset/licensed-facility-crosswalk. Facility geographic variables are updated monthly, if latitude/longitude information is missing at any point in time, it should be available when the next time the Open Data facility file is refreshed.

Please note that the file contains the data from ELMS as of the 11th business day of the month. See DATA_DATE variable for the specific date of when the data was extracted.

Map of all Health Care Facilities in California: https://go.cdii.ca.gov/cdph-facilities

ASCOS was an interdisciplinary expedition to the central Arctic on the icebreaker Oden from 1 August to 9 September 2008. The expedition focused on processes relating to cloud formation in the summer Arctic and included observations of marine biology and chemistry, atmospheric chemistry, physical oceanography, aerosol chemistry and physics, and meteorology. CCN data of two CCN counters as well as Activation Ratios calculated using total Particle Concentrations from a Condensation Particle Counter. One counter was scanning through five different supersaturations (around 0.1%,0.15%,0.2%,0.4%,0.7%), changing between them in 30 minute intervals. The other counter was constant at one supersaturation, which got changed once (on August 15th) from 0.15% to 0.2%. The values for the corrected supersaturations is given in the Supersaturations.xls file. All the data is in one minute average time, from :00s to :59s, the given time is in the middle of the average (:29s). Each file consists of four columns: date, number of CCN, activation ratio (number of CCN/total aerosol number from the CPC), flag. The CCN counters as well as the CPC measured in 1s resolution. This data can be provided if necessary.

The California Department of Public Health (CDPH), Center for Health Care Quality, Licensing and Certification (L&C) Program licenses and certifies more than 30 types of healthcare facilities. The Electronic Licensing Management System (ELMS) is a CDPH data system created to manage state licensing-related data and enforcement actions.

This dataset provides a California healthcare facilities interdepartmental crosswalk using the Department of Health Care Access and Information (HCAI) assigned licensed facility identification numbers linked with matched California Department of Public Health (CDPH), Licensing and Certification facility lists based on license number housed in the Electronic Licensing Management System (ELMS) and/or the CMS Certification Number (CCN) from the Federal Automated Survey Process Environment (ASPEN) databases. This is not a comprehensive matched list, facility identification numbers that did not match are also included from both the HCAI and CDPH lists. Facility Status or Facility Level designations may explain some HCAI non-matches, for additional information contact HCAI directly. Please contact CDPH directly for more information regarding un-matched facility identifiers that do not have corresponding OSHPD identifiers.

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns, ACTIVATE, NAAMES, CAMP2EX, ORACLES, SOCRATES, MARCUS, and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements are collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, representing a range of clean to polluted conditions in various climate regimes. With the large range of environmental conditions sampled, this collection of data is ideal for testing satellite remote detection methods of CDNC and CCN in marine environment. Remote measurement methods are key to expanding the available data, in these difficult to reach regions of the Earth, and improving our understanding of aerosol-cloud interactions. Additional particle composition and continental tracers are included to identify potential contributing CCN sou..., This is an aggregated dataset, consisting of timeseries with in-situ aircraft or ship campaign measurements from ACTIVATE, NAAMES, CAMP2EX, ORACLES, SOCRATES, MARCUS, and CAPRICORN2. CCN, CCN proxies and measurements necessary to identify particle physical and chemical properties and non-marine contributions to particle concentrations are included. All missing or invalid data flags are converted to ‘Na’. Some datasets have already been filtered for inlet shattering in-cloud, and measurement contamination from ship exhausts; however, methods of filtering ship exhaust vary by campaign. For the NAAMES ship campaigns, the research ship exhaust was identified and filtered out based on the wind direction relative to the ship exhaust and total particle counts. For CAPRICORN2, wind direction, total particle counts, black carbon particle concentration, and CO and CO2 measurements were also utilized in filtering ship exhaust. Finally, the MARCUS ship exhaust contamination periods are identified a..., The data files are in a .csv format and can be opened with many open-source softwares. The data from each campaign deployment is in a seprate .csv file. Some of the data files are stored on the Zenodo data repository due to licensing requirements (CC BY 4.0) and must be downloaded from https://doi.org/10.5281/zenodo.8135766.

These files provide statistics of CCN activation characteristics per leg from HI-SCALE campaign. The file naming convention is as follows. ... [20160425]Closure_stats_[ColumnA]_[Case_C]_[K_{org}=0.08]subplots3 ... (1) The numbers within first square bracket (from left) indicate the day in yyyymmdd. (2) The second square bracket. Column A is SS = 0.24% and Column B is SS = 0.46%. (3) The third square bracket. This represents mixing state case (A or B or C). (4) The fourth square bracket. This represent the kappa_org value. This is constant for all the files uploaded here.

Dataset abstract

Cloud Condensation Nuclei (CCN) are a subclass of atmospheric aerosol particles, which can be activated to cloud droplets at a certain supersaturation, with respect to water. Due to their abundance, these particles can affect micro-physical properties of clouds, while acting as CCN. It was found that CCN are relevant for the Earth’s radiation budget, by affecting cloud albedo and lifetime. When giving a number concentration of CCN, also the supersaturation at which it was measured has to be given.

With additional information on particle number size distribution, the hypothetical diameter of particle activation (critical diameter) was derived. Further, the particle hygroscopicity parameter (kappa) was calculated using the critical diameter. Values of kappa can be a proxy for bulk chemical composition of the sampled CCN population.

Our dataset gives CCN number concentrations measured by a CCN counter (type CCN-100 by DMT, Boulder, US) operated at five different levels of supersaturation (0.15%, 0.2%, 0.3%, 0.5%, 1%) during the Antarctic Circumnavigation Expedition (ACE) cruise over the Southern Ocean, as part of the ACE-SPACE project. Temporal coverage is from December 20, 2016 to March 19, 2017. We give 5-minute averaged and quality controlled CCN number concentrations, critical diameter and kappa values.

Dataset contents

• ACESPACE_cloud_condensation_nuclei_number_concentration_SS015.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_number_concentration_SS020.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_number_concentration_SS030.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_number_concentration_SS050.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_number_concentration_SS100.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_critical_diameter_SS015.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_critical_diameter_SS020.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_critical_diameter_SS030.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_critical_diameter_SS050.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_critical_diameter_SS100.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS015.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS020.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS030.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS050.csv, data file, comma-separated values
• ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS100.csv, data file, comma-separated values
• data_file_header_number_concentration.txt, metadata, text
• data_file_header_critical_diameter.txt, metadata, text
• data_file_header_hygroscopicity_parameter.txt, metadata, text
• change_log.txt, metadata, text
• README.txt, metadata, text

The files listed above contain Cloud Condensation Nuclei (CCN) number concentration (N_CCN), critical diameter (D_crit) and particle hygroscopicity parameter (KAPPA) values for the Antarctic Circumnavigation Expedition from in-situ measurements. Each file contains only N_CCN, D_crit or KAPPA values for one of the five measured levels of supersaturation (SS), e.g., N_CCN at SS=0.15% in ACESPACE_cloud_condensation_nuclei_number_concentration_SS015.csv or N_CCN at SS=0.2% in ACESPACE_cloud_condensation_nuclei_number_concentration_SS020.csv etc. In addition, for each N_CCN value the respective temperature of the CCNCs measurement column (T_col) is given. Values are from 1 Hz measurements and averaged to represent 5-minute intervals.

For every given value of CCN number concentration, the respective supersaturation level is given, although files only contain values for one level only. Additionally, longitude and latitude for the ship’s position at the start time of the averaging period are given.

For latitude and longitude nan values are given, in cases where positioning data was not available for the given time period. There are no nan values for CCN number concentration included, in a way that only quality assured data is given.

Change log

v1.1 - data files updated

• change dataset title to specify ACE cruise
• change time resolution to 5 minutes
• addition of critical diameter data
• addition of hygroscopicity parameter data
• create separate data_file_headers
• add change log

v1.0 - initial release of dataset

No description is available. Visit https://dataone.org/datasets/a23f915bfbaf02c9f0000fe5989226ca for complete metadata about this dataset.

Model output from "A model intercomparison of CCN-limited tenuous clouds in the high Arctic", accepted for publication in Atmospheric Chemistry and Physics, 2018, same authors. The intercomparison includes output from three large-eddy simulation models (UCLALES-SALSA, MIMICA, and COSMO-LES) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM) for a case study of high-Arctic tenuous cloud based on observations from the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign. See publication for details. The discussion preprint for peer review can be found at https://doi.org/10.5194/acp-2017-1128.

Note: 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.

Note: May 3,2024: Due to incomplete or missing hospital data received for the April 21,2024 through April 27, 2024 reporting period, the COVID-19 Hospital Admissions Level could not be calculated for CNMI and will be reported as “NA” or “Not Available” in the COVID-19 Hospital Admissions Level data released on May 3, 2024.

This dataset represents COVID-19 hospitalization data and metrics aggregated to county or county-equivalent, for all counties or county-equivalents (including territories) in the United States as of the initial date of reporting for each weekly metric. 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:

• As of December 15, 2022, COVID-19 hospital data are required to be reported to NHSN, 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 represent aggregated counts and include metrics capturing information specific to hospital capacity, occupancy, hospitalizations, and admissions. Prior to December 15, 2022, hospitals reported data directly to the U.S. Department of Health and Human Services (HHS) or via a state submission for collection in the HHS Unified Hospital Data Surveillance System (UHDSS).
• While CDC reviews these data for errors and corrects those found, some reporting errors might still exist within the data. To minimize errors and inconsistencies in data reported, CDC removes outliers before calculating the metrics. CDC and partners work with reporters to correct these errors and update the data in subsequent weeks.
• Many hospital subtypes, including acute care and critical access hospitals, as well as Veterans Administration, Defense Health Agency, and Indian Health Service hospitals, are included in the metric calculations provided in this report. Psychiatric, rehabilitation, and religious non-medical hospital types are excluded from calculations.
• Data are aggregated and displayed for hospitals with the same Centers for Medicare and Medicaid Services (CMS) Certification Number (CCN), which are assigned by CMS to counties based on the CMS Provider of Services files.
• Full details on COVID-19 hospital data reporting guidance can be found here: https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf

• County-level hospital data are derived using calculations performed at the Health Service Area (HSA) level. An HSA is defined by CDC’s National Center for Health Statistics as a geographic area containing at least one county which is self-contained with respect to the population’s provision of routine hospital care. Every county in the United States is assigned to an HSA, and each HSA must contain at least one hospital. Therefore, use of HSAs in the calculation of local hospital metrics allows for more accurate characterization of the relationship between health care utilization and health status at the local level.
• Data presented at the county-level represent admissions, hospital inpatient and ICU bed capacity and occupancy among hospitals within the selected HSA. Therefore, admissions, capacity, and occupancy are not limited to residents of the selected HSA.
• For all county-level hospital metrics listed below the values are calculated first for the entire HSA, and then the HSA-level value is then applied to each county within the HSA.
• For all county-level hospital metrics listed below the values are calculated first for the entire HSA, and then the HSA-level value is then applied to each county within the HSA.

• Time period: data for the previous MMWR week (Sunday-Saturday) will update weekly on Mondays as soon as they are reviewed and verified, usually before 8 pm ET. Updates will occur the following day when reporting coincides with a federal holiday. Note: Weekly updates might be delayed due to delays in reporting. All data are provisional. Because these provisional counts are subject to change, including updates to data reported previously, adjustments can occur. Data may be updated since original publication due to delays in reporting (to account for data received after a given Thursday publication) or data quality corrections.
• New hospital admissions (count): Total number of admissions of patients with laboratory-confirmed COVID-19 in the previous week (including both adult and pediatric admissions) in the entire jurisdiction
• New Hospital Admissions Rate Value (Admissions per 100k): Total number of new admissions of patients with laboratory-confirmed COVID-19 in the past week (including both adult and pediatric admissions) for the entire jurisdiction divided by 2019 intercensal population estimate for that jurisdiction multiplied by 100,000. (Note: This metric is used to determine each county’s COVID-19 Hospital Admissions Level for a given week).
• New COVID-19 Hospital Admissions Rate Level: qualitative value of new COVID-19 hospital admissions rate level [Low, Medium, High, Insufficient Data]
• New hospital admissions percent change from prior week: Percent change in the current weekly total new admissions of patients with laboratory-confirmed COVID-19 per 100,000 population compared with the prior week.
• New hospital admissions percent change from prior week level: Qualitative value of percent change in hospital admissions rate from prior week [Substantial decrease, Moderate decrease, Stable, Moderate increase, Substantial increase, Insufficient data]
• COVID-19 Inpatient Bed Occupancy Value: Percentage of all staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 (including both adult and pediatric patients) within the in the entire jurisdiction is calculated as an average of valid daily values within the past week (e.g., if only three valid values, the average of those three is taken). Averages are separately calculated for the daily numerators (patients hospitalized with confirmed COVID-19) and denominators (staffed inpatient beds). The average percentage can then be taken as the ratio of these two values for the entire jurisdiction.
• COVID-19 Inpatient Bed Occupancy Level: Qualitative value of inpatient beds occupied by COVID-19 patients level [Minimal, Low, Moderate, Substantial, High, Insufficient data]
• COVID-19 Inpatient Bed Occupancy percent change from prior week: The absolute change in the percent of staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 represents the week-over-week absolute difference between the average occupancy of patients with confirmed COVID-19 in staffed inpatient beds in the past week, compared with the prior week, in the entire jurisdiction.
• COVID-19 ICU Bed Occupancy Value: Percentage of all staffed inpatient beds occupied by adult patients with confirmed COVID-19 within the entire jurisdiction is calculated as an average of valid daily values within the past week (e.g., if only three valid values, the average of those three is taken). Averages are separately calculated for the daily numerators (adult patients hospitalized with confirmed COVID-19) and denominators (staffed adult ICU beds). The average percentage can then be taken as the ratio of these two values for the entire jurisdiction.
• COVID-19 ICU Bed Occupancy Level: Qualitative value of ICU beds occupied by COVID-19 patients level [Minimal, Low, Moderate, Substantial, High, Insufficient data]
• COVID-19 ICU Bed Occupancy percent change from prior week: The absolute change in the percent of staffed ICU beds occupied by patients with laboratory-confirmed COVID-19 represents the week-over-week absolute difference between the average occupancy of patients with confirmed COVID-19 in staffed adult ICU beds for the past week, compared with the prior week, in the in the entire jurisdiction.
• For all metrics, if there are no data in the specified locality for a given week, the metric value is displayed as “insufficient data”.

Notes: June 15, 2023: Due to incomplete or missing hospital data received for the June 4, 2023, through June 10, 2023, reporting period, the COVID-19 Hospital Admissions Level could not be calculated for CNMI and AS and will be reported as “NA” or “Not Available” in the COVID-19 Hospital Admissions Level data released on June 15, 2023.

July 10, 2023: Due to incomplete or missing hospital data received for the June 25, 2023, through July 1, 2023, reporting period, the COVID-19 Hospital Admissions Level could not be calculated for CNMI and AS and will be reported as “NA” or “Not Available” in the COVID-19 Hospital Admissions Level data released on July 10, 2023.

July 17, 2023: Due to incomplete or missing hospital data received for the July 2, 2023, through July 8, 2023, reporting