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DSS Program Participation by Month CY 2012-2024
data.ct.gov | Last Updated 2024-07-12T14:10:11.000ZIn order to facilitate public review and access, enrollment data published on the Open Data Portal is provided as promptly as possible after the end of each month or year, as applicable to the data set. Due to eligibility policies and operational processes, enrollment can vary slightly after publication. Please be aware of the point-in-time nature of the published data when comparing to other data published or shared by the Department of Social Services, as this data may vary slightly. As a general practice, for monthly data sets published on the Open Data Portal, DSS will continue to refresh the monthly enrollment data for three months, after which time it will remain static. For example, when March data is published the data in January and February will be refreshed. When April data is published, February and March data will be refreshed, but January will not change. This allows the Department to account for the most common enrollment variations in published data while also ensuring that data remains as stable as possible over time. In the event of a significant change in enrollment data, the Department may republish reports and will notate such republication dates and reasons accordingly. In March 2020, Connecticut opted to add a new Medicaid coverage group: the COVID-19 Testing Coverage for the Uninsured. Enrollment data on this limited-benefit Medicaid coverage group is being incorporated into Medicaid data effective January 1, 2021. Enrollment data for this coverage group prior to January 1, 2021, was listed under State Funded Medical. Effective January 1, 2021, this coverage group have been separated: (1) the COVID-19 Testing Coverage for the Uninsured is now G06-I and is now listed as a limited benefit plan that rolls up into “Program Name” of Medicaid and “Medical Benefit Plan” of HUSKY Limited Benefit; (2) the emergency medical coverage has been separated into G06-II as a limited benefit plan that rolls up into “Program Name” of Emergency Medical and “Medical Benefit Plan” of Other Medical. An historical accounting of enrollment of the specific coverage group starting in calendar year 2020 will also be published separately. This data represents number of active recipients who received benefits under a program in that calendar year and month. A recipient may have received benefits from multiple programs in the same month; if so that recipient will be included in multiple categories in this dataset (counted more than once.) 2021 is a partial year. For privacy considerations, a count of zero is used for counts less than five. NOTE: On April 22, 2019 the methodology for determining HUSKY A Newborn recipients changed, which caused an increase of recipients for that benefit starting in October 2016. We now count recipients recorded in the ImpaCT system as well as in the HIX system for that assistance type, instead using HIX exclusively. Also, corrections in the ImpaCT system for January and February 2019 caused the addition of around 2000 and 3000 recipients respectively, and the counts for many types of assistance (e.g. SNAP) were adjusted upward for those 2 months. Also, the methodology for determining the address of the recipients changed: 1. The address of a recipient in the ImpaCT system is now correctly determined specific to that month instead of using the address of the most recent month. This resulted in some shuffling of the recipients among townships starting in October 2016. 2. If, in a given month, a recipient has benefit records in both the HIX system and in the ImpaCT system, the address of the recipient is now calculated as follows to resolve conflicts: Use the residential address in ImpaCT if it exists, else use the mailing address in ImpaCT if it exists, else use the address in HIX. This resulted in a reduction in counts for most townships starting in March 2017 because a single address is now used instead of two when the systems do not agree. NOTE: On February 14 2019, the enrollment counts for
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Monthly Slot Revenue from Casinos for Current Year (displayed in $)
data.ct.gov | Last Updated 2024-07-16T18:24:52.000ZMohegan Sun Footnotes: (1) Monthly contributions are due to the State by the 15th of the following month. (2) Mohegan Sun did not include the value of eBonus credits redeemed by patrons at slot machines in its video facsimile devices Win amounts; however, the value of eBonus credits wagered was included in the reported Handle. In addition, please be advised that the Casino Hold % column amounts may be understated and the Payout % column amounts may be overstated as a result of this. (3) From July 1, 2009 to June 30, 2012, if the aggregate amount of eBonus coupons or credits actually played on the Mohegan Tribe's Video Facsimiles during a particular month exceeded 5.5% of “gross operating revenues” for that month, the Mohegan Tribe paid to the State an amount equal to twenty-five percent (25%) of such excess face amount of eBonus coupons or credits used in such calendar month (the "eBonus Contribution"). Beginning on July 1, 2012, and for all months thereafter, the aggregate amount threshold for determining the eBonus Contribution increased from 5.5% to 11% of "gross operating revenues." (4) The value of eBonus free slot play credits redeemed during February 2009 totaled $1,910,268; however, it was determined that eBonus credits redeemed were overstated by $1,460,390 for January 2008 though January 2009. February 2009 is adjusted by this amount. March 2009 was was adjusted by an additional $8,139. (5) During fiscal year 2010 the Mohegan Tribe and the State of Connecticut settled a dispute regarding the proper treatment of eBonus for the period November 2007 through June 2009. As a result of this settlement, the State of Connecticut received $5,727,731, including interest. (6) For fiscal years 2007/2008 and 2008/2009, Poker Pro Electronic Table Rake Amounts of $401,309 and $42,188, respectively, were included in the calculation to determine the amount of Slot Machine Contributions to the State of Connecticut. (7) The Mohegan Sun Casino officially opened on Saturday, October 12, 1996. On October 8-10, video facsimile/slot machines were available for actual play during pre-opening charitable gaming nights. (8) Beginning with the month of May 2001, Mohegan Sun Casino reports video facsimile/slot machine win on an accrual basis, reflecting data captured and reported by an on-line slot accounting system. Reports were previously prepared on a cash basis, based on the coin and currency removed from the machines on each gaming day. (9) Cumulative Win amount total should be reduced by $1,452,341.21 to correct for an over reporting of slot revenues for prior periods related to errors in the accrual carry forward of estimated cash on floor. Foxwoods Footnotes: (1) Monthly contributions are due to the State by the 15th of the following month. (2) The operation of the video facsimile/slot machines began at Foxwoods on January 16, 1993. (3) Foxwoods did not include the value of Free Play coupons redeemed by patrons at slot machines in its video facsimile devices Win amounts; however, the value of Free Play coupons wagered was included in the reported Handle. In addition, please be advised that the Casino Hold % column amounts may be understated and the Payout % column amounts may be overstated as a result of this. (4) From July 1, 2009 to June 30, 2012, if the aggregate amount of Free Play coupons or credits actually played on the Mashantucket Pequot Tribe's Video Facsimiles during a particular month exceeded 5.5% of “gross operating revenues” for that month, the Mashantucket Pequot Tribe paid to the State an amount equal to twenty-five percent (25%) of such excess face amount of Free Play coupons or credits used in such calendar month (the "Free Play Contribution"). Beginning on July 1, 2012, and for all months thereafter, the aggregate amount threshold for determining the Free Play Contribution increased from 5.5% to 11% of "gross operating revenues." (5) During fiscal year 2010 the Mashantucket Pequot T
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COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE
data.ct.gov | Last Updated 2023-08-02T16:13:35.000ZNote: 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 and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. 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
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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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COVID-19 Reported Patient Impact and Hospital Capacity by Facility
data.ct.gov | Last Updated 2024-07-18T10:36:18.000ZThe "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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DSS Medical Benefit Plan Participation by Month CY 2012-2024
data.ct.gov | Last Updated 2024-07-12T14:05:34.000ZIn order to facilitate public review and access, enrollment data published on the Open Data Portal is provided as promptly as possible after the end of each month or year, as applicable to the data set. Due to eligibility policies and operational processes, enrollment can vary slightly after publication. Please be aware of the point-in-time nature of the published data when comparing to other data published or shared by the Department of Social Services, as this data may vary slightly. As a general practice, for monthly data sets published on the Open Data Portal, DSS will continue to refresh the monthly enrollment data for three months, after which time it will remain static. For example, when March data is published the data in January and February will be refreshed. When April data is published, February and March data will be refreshed, but January will not change. This allows the Department to account for the most common enrollment variations in published data while also ensuring that data remains as stable as possible over time. In the event of a significant change in enrollment data, the Department may republish reports and will notate such republication dates and reasons accordingly. In March 2020, Connecticut opted to add a new Medicaid coverage group: the COVID-19 Testing Coverage for the Uninsured. Enrollment data on this limited-benefit Medicaid coverage group is being incorporated into Medicaid data effective January 1, 2021. Enrollment data for this coverage group prior to January 1, 2021, was listed under State Funded Medical. Effective January 1, 2021, this coverage group have been separated: (1) the COVID-19 Testing Coverage for the Uninsured is now G06-I and is now listed as a limited benefit plan that rolls up into “Program Name” of Medicaid and “Medical Benefit Plan” of HUSKY Limited Benefit; (2) the emergency medical coverage has been separated into G06-II as a limited benefit plan that rolls up into “Program Name” of Emergency Medical and “Medical Benefit Plan” of Other Medical. An historical accounting of enrollment of the specific coverage group starting in calendar year 2020 will also be published separately. This data represents number of active recipients who received benefits under a medical benefit plan in that calendar year and month. A recipient may have received benefits from multiple plans in the same month; if so that recipient will be included in multiple categories in this dataset (counted more than once.) 2021 is a partial year. For privacy considerations, a count of zero is used for counts less than five. NOTE: On April 22, 2019 the methodology for determining HUSKY A Newborn recipients changed, which caused an increase of recipients for that benefit starting in October 2016. We now count recipients recorded in the ImpaCT system as well as in the HIX system for that assistance type, instead using HIX exclusively. Also, corrections in the ImpaCT system for January and February 2019 caused the addition of around 2000 and 3000 recipients respectively, and the counts for many types of assistance (e.g. SNAP) were adjusted upward for those 2 months. Also, the methodology for determining the address of the recipients changed: 1. The address of a recipient in the ImpaCT system is now correctly determined specific to that month instead of using the address of the most recent month. This resulted in some shuffling of the recipients among townships starting in October 2016. 2. If, in a given month, a recipient has benefit records in both the HIX system and in the ImpaCT system, the address of the recipient is now calculated as follows to resolve conflicts: Use the residential address in ImpaCT if it exists, else use the mailing address in ImpaCT if it exists, else use the address in HIX. This resulted in a reduction in counts for most townships starting in March 2017 because a single address is now used instead of two when the systems do not agree.\ NOTE: On February 14 2019, the enrollment
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Municipal Fiscal Indicators: Bond Ratings, 2019
data.ct.gov | Last Updated 2024-01-30T20:03:26.000ZMunicipal Fiscal Indicators is an annual compendium of information compiled by the Office of Policy and Management, Office of Finance, Municipal Finance Services Unit (MFS). The data contained in Indicators provides key financial and demographic information on municipalities in Connecticut. Municipal Fiscal Indicators contains the most current financial data available for each of Connecticut's 169 municipalities. The majority of this data was compiled from the audited financial statements that are filed annually with the State of Connecticut, Office of Policy and Management, Office of Finance. This database of information includes selected demographic and economic data relating to, or having an impact upon, a municipality’s financial condition. The most recent edition is for the Fiscal Years Ended 2015-2019 published in April 2021. A bond rating is an evaluation by credit-rating agencies of a municipality’s or school district’s credit risk. A municipality's or school district’s bonds may be rated by more than one rating agency. The three major rating agencies are Moody’s Investor Services, Standard and Poor’s Corporation, and Fitch Incorporated. Data on the Municipal Fiscal Indicators is included in the following datasets: Municipal Fiscal Indicators, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-2019/sb4i-6vik Municipal Fiscal Indicators: Pension Funding Information For Defined Benefit Pension Plans, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Pension-Funding-Inform/civu-w22d Municipal Fiscal Indicators: Type and Number of Pension Plans, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Type-and-Number-of-Pen/9f65-c4yr Municipal Fiscal Indicators: Other Post-Employment Benefits (OPEB), 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Other-Post-Employment-/sa26-46h8 Municipal Fiscal Indicators: Economic and Grand List Data, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Economic-and-Grand-Lis/wpbp-b657 Municipal Fiscal Indicators: Bond Ratings, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Bond-Ratings-2019/3w9d-7jbi Municipal Fiscal Indicators: Benchmark Labor Data, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Benchmark-Labor-Data-2/db37-h23r Municipal Fiscal Indicators: Unemployment, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Unemployment-2019/cugp-2za3
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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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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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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.