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Nursing Homes with Residents Positive for COVID-19, April - June 2020 - Archive
data.ct.gov | Last Updated 2023-08-02T15:47:30.000ZNursing homes with residents positive for COVID-19 from 4/22/2020 to 6/19/2020. Starting in July 2020, this dataset will no longer be updated and will be replaced by the CMS COVID-19 Nursing Home Dataset, available at the following link: https://data.ct.gov/Health-and-Human-Services/CMS-COVID-19-Nursing-Home-Dataset/w8wc-65i5. Methods: 1) Laboratory-confirmed case counts are based upon data reported via the FLIS web portal. Nursing homes were asked to provide cumulative totals of residents with laboratory confirmed covid. This includes residents currently in-house, in the hospital, or who are deceased. Residents were excluded if they tested positive prior to initial admission to the nursing home. 2) The cumulative number of deaths among nursing home residents is based upon data reported by the Office of the Chief Medical Examiner. For public health surveillance, COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death (laboratory-confirmed) and persons whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death (probable). Limitations: 1) As of the week of 5/10/20, Point Prevalence Survey testing is being offered to all asymptomatic nursing home residents to inform infection prevention efforts. Point prevalence surveys will be conducted over a period of several weeks. Some nursing homes had adequate testing resources available to conduct surveys prior to this date. Differences in survey timing will impact the number of positive results that a nursing home reports. 2) Cumulative totals of residents testing positive are being collected rather than individual resident data. Thus we cannot verify the counts, de-duplicate, and/or verify whether there is a record of a positive lab test. This may result in either under- or over-counting. 3) The number of COVID-19 positive residents and the number of confirmed deaths among residents are tabulated from different data sources. Due to the timing of availability of test results for deceased residents, it is not appropriate to calculate the percent of cases who died due to COVID-19 at any particular facility based upon this data. 4) The count of deaths reported for 4/14 are not included in this dataset, as they were not broken out by laboratory-confirmed or probable. They can be viewed in the DPH Report here: https://portal.ct.gov/-/media/Coronavirus/CTDPHCOVID19summary4162020.pdf?la=en
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COVID-19 Vaccinations by Race/Ethnicity - ARCHIVE
data.ct.gov | Last Updated 2023-08-02T16:14:25.000ZNOTE: After 5/20/2021, this dataset will no longer be updated and will be replaced by the new dataset: "COVID-19 Vaccinations by Race/Ethnicity" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Race-Ethnicity/4z97-pa4q). Cumulative number and percent of people who initiated COVID-19 vaccination and who are fully vaccinated by race/ethnicity for select age groups (ages 16+, ages 65-74, and ages 75+) as reported by providers. Population estimates are based on 2019 CT population estimates. The 2019 CT population data which is the most recent year available. The tables that show the percent vaccinated by town and age group are an exception. These tables use 2014 CT population estimates. This the most recent year for which reliable estimates by town and age are available. A person who has received one dose of any vaccine is considered to have received at least one dose. A person is considered fully vaccinated if they have received 2 doses of the Pfizer or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. The number with At Least One Dose and the number Fully Vaccinated add up to more than the total number of doses because people who received the Johnson & Johnson vaccine fit into both categories. In this data, a person with reported Hispanic or Latino ethnicity is considered Hispanic regardless of reported race. The category Unknown includes unknown race and/or ethnicity. The percent of people classified as Other race (not specified) and Multiple race in CT WiZ (for COVID-19 vaccine records and all other vaccine records) are higher than would be expected based on census data. Other race, Multiple race and Unknown include people who should be classified as Asian, Black, Hispanic and White. Therefore, the coverage of these groups may be underestimated and should be interpreted with caution. The estimates for the category Multiple Races are considered unreliable All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Note: As part of continuous data quality improvement efforts, duplicate records were removed from the COVID-19 vaccination data during the weeks of 4/19/2021 and 4/26/2021.
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DCF Children in Placement: Annual Point-in-Time Trend By Gender
data.ct.gov | Last Updated 2023-09-12T18:03:43.000ZThis dataset contains aggregate data concerning the number of unique children placed in open DCF placements on the observation date (July 1st each year). These figures are broken out by the DCF Region and Office responsible for the child's care, the child's Gender, whether the placement setting is in or out-of-state, and by the categorical Placement Type in which the child is residing on the observation date.
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COVID-19 Reported Patient Impact and Hospital Capacity by Facility
data.ct.gov | Last Updated 2024-10-08T10:44:29.000ZThe "COVID-19 Reported Patient Impact and Hospital Capacity by Facility" dataset from the U.S. Department of Health & Human Services, filtered for Connecticut. View the full dataset and detailed metadata here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u The following dataset provides facility-level data for hospital utilization aggregated on a weekly basis (Friday to Thursday). These are derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities. The hospital population includes all hospitals registered with Centers for Medicare & Medicaid Services (CMS) as of June 1, 2020. It includes non-CMS hospitals that have reported since July 15, 2020. It does not include psychiatric, rehabilitation, Indian Health Service (IHS) facilities, U.S. Department of Veterans Affairs (VA) facilities, Defense Health Agency (DHA) facilities, and religious non-medical facilities. For a given entry, the term “collection_week” signifies the start of the period that is aggregated. For example, a “collection_week” of 2020-11-20 means the average/sum/coverage of the elements captured from that given facility starting and including Friday, November 20, 2020, and ending and including reports for Thursday, November 26, 2020. Reported elements include an append of either “_coverage”, “_sum”, or “_avg”. A “_coverage” append denotes how many times the facility reported that element during that collection week. A “_sum” append denotes the sum of the reports provided for that facility for that element during that collection week. A “_avg” append is the average of the reports provided for that facility for that element during that collection week. The file will be updated weekly. No statistical analysis is applied to impute non-response. For averages, calculations are based on the number of values collected for a given hospital in that collection week. Suppression is applied to the file for sums and averages less than four (4). In these cases, the field will be replaced with “-999,999”. This data is preliminary and subject to change as more data become available. Data is available starting on July 31, 2020. Sometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied according to prioritization rules within HHS Protect. For influenza fields listed in the file, the current HHS guidance marks these fields as optional. As a result, coverage of these elements are varied. On May 3, 2021, the following fields have been added to this data set. hhs_ids previous_day_admission_adult_covid_confirmed_7_day_coverage previous_day_admission_pediatric_covid_confirmed_7_day_coverage previous_day_admission_adult_covid_suspected_7_day_coverage previous_day_admission_pediatric_covid_suspected_7_day_coverage previous_week_personnel_covid_vaccinated_doses_administered_7_day_sum total_personnel_covid_vaccinated_doses_none_7_day_sum total_personnel_covid_vaccinated_doses_one_7_day_sum total_personnel_covid_vaccinated_doses_all_7_day_sum previous_week_patients_covid_vaccinated_doses_one_7_day_sum previous_week_patients_covid_vaccinated_doses_all_7_day_sum On May 8, 2021, this data set has been converted to a corrected data set. The corrections applied to this data set are to smooth out data anomalies caused by keyed in data errors. To help determine which records have had corrections made to it. An additional Boolean field called is_corrected has been added. To see the numbers as reported by the facilities, go to: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb On May 13, 2021 Changed vaccination fields from sum to max or min fields. This reflects the maximum or minimum number report
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COVID-19 case rate per 100,000 population and percent test positivity in the last 7 days by town - ARCHIVE
data.ct.gov | Last Updated 2023-08-02T16:11:04.000ZDPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2 As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well. With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county). This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity). A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case. These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities. These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020. Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.
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State of CT: Open Expenditures - Ledger
data.ct.gov | Last Updated 2024-10-09T06:56:26.000ZThis data allows citizens to view who received payments from the state for goods or services and how much they received. The data can be explored by searching for specific payee names or by browsing by Government Function. <a href="http://opencheckbook.ct.gov">The Open Checkbook app</a> allows the user to drill down from aggregated spending accounts all the way down to each individual payment to a payee. The data is updated nightly and therefore reflects current spending activities more accurately than any other publicly available source. In general the data reflects all payments made up to 24 to 48 hours prior to view. Certain payee names have been removed in order to protect the privacy of individuals, in accordance with Health Insurance Portability and Accountability Act (HIPAA) regulations or where the information is otherwise protected by law. Redacted information includes: •Payees who are statutorily protected •Information that would lead to violating HIPAA laws •Information of Minors
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DCF Children in Placement: Annual Point-in-Time Trend By Race/Ethnicity
data.ct.gov | Last Updated 2023-09-12T18:01:54.000ZThis dataset contains aggregate data concerning the number of unique children placed in open DCF placements on the observation date (July 1st each year). These figures are broken out by the DCF Region and Office responsible for the child's care, the child's Race/Ethnicity, whether the placement setting is in or out-of-state, and by the categorical Placement Type in which the child is residing on the observation date.
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Fires in Connecticut
data.ct.gov | Last Updated 2023-05-08T18:56:47.000ZOnly fires are included here. All other incidences, including EMS calls and False Alarms have been excluded. This dataset contains Connecticut Fire Department Incidents as reported to the National Fire Department Incident Reporting System (NFIRS). Note that the 2014 and 2016 data has far more entries than the other years. In particular, they detail "False Alarm and False Calls" and "Rescue and Emergency Medical Service (EMS) Incidents" NFIRS collects details on Fire, HazMat and EMS incidences nationwide, detailing the type of incident, where it occurred, the resources used to mitigate it and more, with a goal of understanding the nature and causes of the incidents. Information is also collected on the number of civilian or firefighter casualties and an estimate of property loss. Participation in NFIRS is voluntary. Data is released yearly, with a considerable delay. Each Incidence is assigned a 3 digit Incidence Type Code. The code describes the situation emergency personnel found when they arrived. Incidence Types are grouped into larger categories, called Series. For example, Series 400, 'Hazardous Condition' category includes incidence types: 411, 'Gasoline or other flammable liquid spill; 412, 'Gas leak and 413, 'Oil or other combustible liquid spill '. Not every Incidence Type is included in the data. In 2012, 2013, 2014 and 2015, the NFIRS data releases contained these Series/Incidence Types: Series 100: Fire Incidences, Series 400: Hazardous Condition (No Fire), Incidence Type 561: Unauthorized burning, under the 'Service Call' Series, Incidence Type 631: Authorized Controlled Burning, under the 'Good Intent Call' series and Incidence Type 632: Prescribed fires also under the 'Good Intent Call' series. The 2014 and 2016 release included these additional series: 200: Overpressure Rupture, Explosion, Overheat (No Fire), 300: Rescue and Emergency Medical Service (EMS) Incidents, 500: Service Calls, 600: Good Intent Call Series, 700: False Alarm and False Call, 800 Severe Weather and Natural Disaster 900: Special Incident Type. The official NFIRS documentation has been attached to this dataset. This dataset does not contain all the detail available in the NFIRS database. If after reviewing the documentation, you find additional information you would like added to the dataset, please let us know.
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Connecticut Fire Department Incidents (2012-2021)
data.ct.gov | Last Updated 2023-09-18T14:19:59.000ZThis dataset contains Connecticut Fire Department Incidents as reported to the National Fire Department Incident Reporting System (NFIRS). Note that some years have far more entries than other years. In particular, they detail "False Alarm and False Calls" and "Rescue and Emergency Medical Service (EMS) Incidents" NFIRS collects details on Fire, HazMat and EMS incidences nationwide, detailing the type of incident, where it occurred, the resources used to mitigate it and more, with a goal of understanding the nature and causes of the incidents. Information is also collected on the number of civilian or firefighter casualties and an estimate of property loss. Participation in NFIRS is voluntary. Data is released yearly, with a considerable delay. Each Incidence is assigned a 3 digit Incidence Type Code. The code describes the situation emergency personnel found when they arrived. Incidence Types are grouped into larger categories, called Series. For example, Series 400, 'Hazardous Condition' category includes incidence types: 411, 'Gasoline or other flammable liquid spill; 412, 'Gas leak and 413, 'Oil or other combustible liquid spill '. Not every Incidence Type is included in the data. In 2012, 2013, 2014 and 2015, the NFIRS data releases contained these Series/Incidence Types: Series 100: Fire Incidences, Series 400: Hazardous Condition (No Fire), Incidence Type 561: Unauthorized burning, under the 'Service Call' Series, Incidence Type 631: Authorized Controlled Burning, under the 'Good Intent Call' series and Incidence Type 632: Prescribed fires also under the 'Good Intent Call' series. The 2014 and 2016 releases included these additional series: 200: Overpressure Rupture, Explosion, Overheat (No Fire), 300: Rescue and Emergency Medical Service (EMS) Incidents, 500: Service Calls, 600: Good Intent Call Series, 700: False Alarm and False Call, 800 Severe Weather and Natural Disaster 900: Special Incident Type. The official NFIRS documentation has been attached to this dataset. This dataset does not contain all the detail available in the NFIRS database. If after reviewing the documentation, you find additional information you would like added to the dataset, please let us know.
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Connecticut Qualified Census Tracts
data.ct.gov | Last Updated 2023-08-02T19:28:36.000ZThis dataset provides access to Qualified Census Tracts (QCTs) in Connecticut to assist in administration of American Rescue Plan (ARP) funds. The Secretary of HUD must designate QCTs, which are areas where either 50 percent or more of the households have an income less than 60 percent of the AMGI for such year or have a poverty rate of at least 25 percent. HUD designates QCTs based on new income and poverty data released in the American Community Survey (ACS). Specifically, HUD relies on the most recent three sets of ACS data to ensure that anomalous estimates, due to sampling, do not affect the QCT status of tracts. QCTs are identified for the purpose of Low-Income Housing Credits under IRC Section 42, with the purpose of increasing the availability of low-income rental housing by providing an income tax credit to certain owners of newly constructed or substantially rehabilitated low-income rental housing projects. Also included are the number of households from the 2010 census (the “p0150001” variable), the average poverty rate using the 2014-2018 ACS data (the “pov_rate_18” variable), and the ratio of Tract Average Household Size Adjusted Income Limit to Tract Median Household Income using the 2014-2018 ACS data (the “inc_factor_18” variable). For the last variable mentioned in the previous paragraph, the income limit is the limit for being considered a very low income household (size-adjusted and based on Area Mean Gross Income). This value is divided by the median household income for the given tract, to get a sense of how the limit and median incomes compare. For example, if ratio>1, it implies that the tract is very low income because the limit income is greater than the median income. This ratio is a compact way to include the separate variables for the household income limit and median household income for each tract.