This dataset includes all Motor Vehicle Collision (MVC) occurrences by their occurrence date and related offences. The MVC categories include property damage (PD) collisions, Fail to Remain (FTR) collisions, injury collisions and fatalities. This data is provided at the occurrence level, therefore multiple offences and/or victims can be associated with each record. Traffic Collisions Dashboard Download Documentation In this dataset, a collision is defined as the contact resulting from the motion of a motor vehicle or streetcar or its load, which produces property damage, injury or death. The term collision indicates that the initial point of contact involved at least one motor vehicle or streetcar. Definitions: Fatal Collisions occur when an individual’s injuries from a MVC result in a fatality within 30 days. Please note this category excludes: (i) Occurrences on private property (ii) Occurrences related to sudden death prior to collision (suicide or medical episode) (iii) Occurrences where the individual has died more than 30 days after the collision Personal Injury Collisions occur when an individual involved in a MVC suffers personal injuries. Fail to Remain Collisions occur when an individual involved in a MVC fails to stop and provide their information at the scene of a collision. Property Damage Collisions occur when an individual’s property has been damaged in a MVC or the value of damages is less than $2,000 for all involved parties. This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).** ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

The Toronto’s Police Service Annual Statistical Report (ASR) is a comprehensive overview of police related statistics including reported crimes, victims of crime, search of persons, firearms, traffic collisions, personnel, budget, communications, public complaints, regulated interactions and other administrative information. This dataset includes all shooting occurrences from 2014 to 2019 by occurred date aggregated by Division. This data includes all shooting-related events reported to the Toronto Police Service, including, but not limited to, those that may have been deemed unfounded after investigation. Data is accurate as of the date and time of reporting. In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. The data has been aggregated by year, category, subtype and geographic division. As there is no criminal offence code for shootings, a shooting occurrence number may also be present in other data sets including, but not limited to, assault and robbery. Note: The further breakdown of this information at the event level will be made available in the future releases of the Shootings open data. Shootings in this data set include both firearm discharges and shooting events, which are defined as follows: Shooting Event/Occurrence: Any incident in which a projectile is discharged from a firearm (as defined under the Criminal Code of Canada) and injures a person. This excludes events such as suicide and police involved firearm discharges. Firearm Discharge: Any incident where evidence exists that a projectile was discharged from a firearm (as defined under the Criminal Code of Canada) including accidental discharge (non-police), celebratory fire, drive-by etc. Persons Injured (previously classified as “victims”): A person who was struck by a bullet(s) as a result of the discharge of a firearm (as defined under the Criminal Code of Canada). This excludes events such as suicide, police-involved event or where the weapon used was not a real firearm (such as pellet gun, air pistol, “sim-munition” etc.) Injury Levels Death: Where the injured person (as defined above) has died as a result of injuries sustained from a bullet(s). Injuries: Where the injured person (as defined above) has non-fatal physical injuries as a result of a bullet(s). This data is related to table (ASR-SH-TBL-001) in The Annual Statistical Report. Additional information can be found here.

This dataset contains counts of offences recorded by the NT Police, categorised by offence type, time period (month), location and (for assault offences) alcohol and domestic violence involvement. Certain types of offences show strong seasonal impacts and numbers show considerable monthly variation, particularly at the regional level. In April 2025, a new version of the Australian-New Zealand Standard Offence Classification (ANZSOC) was implemented in the Northern Territory, which is the standard to be used by all Australian and New Zealand jurisdictions. Key offence categories in the crime statistics, such as homicide, assault, sexual offences, robbery, burglary, theft, and property damage, are included in the new classification. No recorded offences have been deleted or created as a result of this process, but they may be reclassified, meaning they are reported in a different category. Thus, care must be taken when comparing the crime statistics in this time series with previously published time series. Since implementation of the SerPro data system in November 2023, it has been identified that entry of the data used for crime statistics generally happens later in the investigation process when compared to the previous PROMIS system. This means that monthly data takes longer to settle and may take several months to reflect the actual numbers of offences recorded by police. For this reason, the monthly crime statistics should be reviewed with caution and will be marked as provisional until data collection is substantially complete. There has been a break in the crime statistics time series following November 2023, due to the implementation of SerPro. This means that the statistics from December 2023 onwards should not be compared directly to earlier statistics.

This dataset includes all Major Crime Indicators (MCI) occurrences by reported date and related offences since 2014. Major Crime Indicators Dashboard Download Documentation The Major Crime Indicators categories include Assault, Break and Enter, Auto Theft, Robbery and Theft Over (Excludes Sexual Violations). This data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence. The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone. This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).** The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual. NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data. By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario. In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This dataset includes all Theft from Motor Vehicle occurrences by reported date and related offences since 2014. The Theft from Motor Vehicle offences include Theft from Motor Vehicle Under and Theft from Motor Vehicle Over.Theft from Motor Vehicle DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various offences used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This dataset includes all auto theft occurrences by reported date and related offences since 2014.Auto Theft DashboardDownload DocumentationThis data is provided at the offence and/or vehicle level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This dataset contains occurrences related to bicycle thefts since 2014. These occurrences are related to a variety of offences where the theft of a bicycle was included. Bicycle Thefts Dashboard Download Bicycle Theft Code Sheet Download Documentation The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone. This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).** The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual. NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data. By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario. In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This is the second in a series of papers presenting VLBI observations of the 293 Caltech-Jodrell Bank Flat-spectrum (hereafter CJF) sources and their analysis. We obtain a consistent motion dataset large enough to allow the systematic properties of the population to be studied. We present detailed kinematic analysis of the complete flux-density limited CJF survey. We computed 2-D kinematic models based on the optimal model-fitting parameters of multi-epoch VLBA observations. This allows us to calculate not only radial, but also orthogonal motions, and thus to study curvature and acceleration. Statistical tests of the motions measured and their reliability were performed. A correlation analysis between the derived apparent motions, luminosities, spectral indices, and core dominance and the resulting consequences is described. With at least one velocity in each of the 237 sources, this sample is much larger than any available before, so it allows a meaning ful statistical investigation of apparent motions and any possible correlations with other parameters in AGN jets. The main results to emerge are as follows: * In general motions are not consistent with a single uniform velocity applicable to all components along a jet. * We find a slight trend towards a positive outward acceleration and also adduce some evidence for greater acceleration in the innermost regions. * We find a lack of fast components at physical distances less than a few pc from the reference feature. * Only ~4% of the components from galaxies and <2% of those from quasars undergo large bends i.e. within 15{deg} of +/-90{deg}. * The distribution of radial velocities shows a broad distribution of velocities (apparent velocities up to 30c). Fifteen percent of the best-sampled jet components exhibit low velocities that may need to be explained in a different manner to the fast motions. * Some negative superluminal motions are seen, and in 15 cases (6%) these are definitely significant. * We find a strong correlation between the 5 GHz luminosity and the apparent velocity. * The CJF galaxies, on average, show slower apparent jet-component velocities than the quasars. * The mean velocity in the VLBA 2cm survey (Kellermann et al. 2004) is substantially higher than in the CJF survey, the ratio could be roughly a factor of 1.5-2. This supports the observed trend toward increasing apparent velocity with in creasing observing frequency. This AGN survey provides the basis for any statistical analysis of jet and jet-component properties. Cone search capability for table J/A+A/484/119/sources (Source list)

This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Headings of the semantic annotation scheme.

This dataset includes all break and enter occurrences by reported date and related offences since 2014.Break and Enter DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This data contains provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. Counts for the most recent final annual data are provided for comparison. National provisional counts include deaths occurring within the 50 states and the District of Columbia as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation (see Technical notes) resulting in an underestimate relative to final counts. To address this, methods were developed to adjust provisional counts for reporting delays by generating a set of predicted provisional counts (see Technical notes). Starting in June 2018, this monthly data release will include both reported and predicted provisional counts.

The provisional data include: (a) the reported and predicted provisional counts of deaths due to drug overdose occurring nationally and in each jurisdiction; (b) the percentage changes in provisional drug overdose deaths for the current 12 month-ending period compared with the 12-month period ending in the same month of the previous year, by jurisdiction; and (c) the reported and predicted provisional counts of drug overdose deaths involving specific drugs or drug classes occurring nationally and in selected jurisdictions. The reported and predicted provisional counts represent the numbers of deaths due to drug overdose occurring in the 12-month periods ending in the month indicated. These counts include all seasons of the year and are insensitive to variations by seasonality. Deaths are reported by the jurisdiction in which the death occurred.

Several data quality metrics, including the percent completeness in overall death reporting, percentage of deaths with cause of death pending further investigation, and the percentage of drug overdose deaths with specific drugs or drug classes reported are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical notes). Reporting of the specific drugs and drug classes involved in drug overdose deaths varies by jurisdiction, and comparisons of death rates involving specific drugs across selected jurisdictions should not be made (see Technical notes). Provisional data will be updated on a monthly basis as additional records are received.

Technical notes

Nature and sources of data

Provisional drug overdose death counts are based on death records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. The cutoff date is generally the first Sunday of each month. National provisional estimates include deaths occurring within the 50 states and the District of Columbia. NCHS receives the death records from state vital registration offices through the Vital Statistics Cooperative Program (VSCP).

The timeliness of provisional mortality surveillance data in the National Vital Statistics System (NVSS) database varies by cause of death. The lag time (i.e., the time between when the death occurred and when the data are available for analysis) is longer for drug overdose deaths compared with other causes of death (1). Thus, provisional estimates of drug overdose deaths are reported 6 months after the date of death.

Provisional death counts presented in this data visualization are for “12-month ending periods,” defined as the number of deaths occurring in the 12-month period ending in the month indicated. For example, the 12-month ending period in June 2017 would include deaths occurring from July 1, 2016, through June 30, 2017. The 12-month ending period counts include all seasons of the year and are insensitive to reporting variations by seasonality. Counts for the 12-month period ending in the same month of the previous year are shown for comparison. These provisional counts of drug overdose deaths and related data quality metrics are provided for public health surveillance and monitoring of emerging trends. Provisional drug overdose death data are often incomplete, and the degree of completeness varies by jurisdiction and 12-month ending period. Consequently, the numbers of drug overdose deaths are underestimated based on provisional data relative to final data and are subject to random variation. Methods to adjust provisional counts have been developed to provide predicted provisional counts of drug overdose deaths, accounting for delayed reporting (see Percentage of records pending investigation and Adjustments for delayed reporting).

Provisional data are based on available records that meet certain data quality criteria at the time of analysis and may not include all deaths that occurred during a given time period. Therefore, they should not be considered comparable with final data and are subject to change.

Cause-of-death classification and definition of drug deaths
Mortality statistics are compiled in accordance with World Health Organization (WHO) regulations specifying that WHO member nations classify and code causes of death with the current revision of the International Statistical Classification of Diseases and Related Health Problems (ICD). ICD provides the basic guidance used in virtually all countries to code and classify causes of death. It provides not only disease, injury, and poisoning categories but also the rules used to select the single underlying cause of death for tabulation from the several diagnoses that may be reported on a single death certificate, as well as definitions, tabulation lists, the format of the death certificate, and regulations on use of the classification. Causes of death for data presented in this report were coded according to ICD guidelines described in annual issues of Part 2a of the NCHS Instruction Manual (2).

Drug overdose deaths are identified using underlying cause-of-death codes from the Tenth Revision of ICD (ICD–10): X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), and Y10–Y14 (undetermined). Drug overdose deaths involving selected drug categories are identified by specific multiple cause-of-death codes. Drug categories presented include: heroin (T40.1); natural opioid analgesics, including morphine and codeine, and semisynthetic opioids, including drugs such as oxycodone, hydrocodone, hydromorphone, and oxymorphone (T40.2); methadone, a synthetic opioid (T40.3); synthetic opioid analgesics other than methadone, including drugs such as fentanyl and tramadol (T40.4); cocaine (T40.5); and psychostimulants with abuse potential, which includes methamphetamine (T43.6). Opioid overdose deaths are identified by the presence of any of the following MCOD codes: opium (T40.0); heroin (T40.1); natural opioid analgesics (T40.2); methadone (T40.3); synthetic opioid analgesics other than methadone (T40.4); or other and unspecified narcotics (T40.6). This latter category includes drug overdose deaths where ‘opioid’ is reported without more specific information to assign a more specific ICD–10 code (T40.0–T40.4) (3,4). Among deaths with an underlying cause of drug overdose, the percentage with at least one drug or drug class specified is defined as that with at least one ICD–10 multiple cause-of-death code in the range T36–T50.8.

Drug overdose deaths may involve multiple drugs; therefore, a single death might be included in more than one category when describing the number of drug overdose deaths involving specific drugs. For example, a death that involved both heroin and fentanyl would be included in both the number of drug overdose deaths involving heroin and the number of drug overdose deaths involving synthetic opioids other than methadone.

Selection of specific states and other jurisdictions to report
Provisional counts are presented by the jurisdiction in which the death occurred (i.e., the reporting jurisdiction). Data quality and timeliness for drug overdose deaths vary by reporting jurisdiction. Provisional counts are presented for reporting jurisdictions based on measures of data quality: the percentage of records where the manner of death is listed as “pending investigation,” the overall completeness of the data, and the percentage of drug overdose death records with specific drugs or drug classes recorded. These criteria are defined below.

Percentage of records pending investigation

Drug overdose deaths often require lengthy investigations, and death certificates may be initially filed with a manner of death “pending investigation” and/or with a preliminary or unknown cause of death. When the percentage of records reported as “pending investigation” is high for a given jurisdiction, the number of drug overdose deaths is likely to be underestimated. For jurisdictions reporting fewer than 1% of records as “pending investigation”, the provisional number of drug overdose deaths occurring in the fourth quarter of 2015 was approximately 5% lower than the final count of drug overdose deaths occurring in that same time period. For jurisdictions reporting greater than 1% of records as “pending investigation” the provisional counts of drug overdose deaths may underestimate the final count of drug overdose deaths by as much as 30%. Thus, jurisdictions are included in Table 2 if 1% or fewer of their records in NVSS are reported as “pending investigation,” following a 6-month lag for the 12-month ending periods included in the dashboard. Values for records pending investigation are updated with each monthly release and reflect the most current data available.

Percent completeness

NCHS receives monthly counts of the estimated number of deaths from each jurisdictional vital registration offices (referred to as “control counts”). This number represents the best estimate of how many

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, tests, and associated deaths from COVID-19 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. 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.

The case rate per 100,000 includes probable and confirmed cases. Probable and confirmed are defined using the CSTE case definition, which is available online: https://cdn.ymaws.com/www.cste.org/resource/resmgr/2020ps/Interim-20-ID-01_COVID-19.pdf

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.

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 daily, with timestamps indicated in the daily briefings posted at: portal.ct.gov/coronavirus. Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: Due to an issue with the town-level data dated 1/17/2021, the data was temporarily unavailable; as of 11:19 AM on 1/19/2021 the data has been restored.

As of 11/5/2020, CT DPH has added antigen testing for SARS-CoV-2 to reported test counts in this dataset. The tests included in this dataset include both molecular and antigen datasets. Molecular tests reported include polymerase chain reaction (PCR) and nucleic acid amplicfication (NAAT) tests.

A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

On 5/16/2022, 8,622 historical cases were included in the data. The date range for these cases were from August 2021 – April 2022.”

This data visualization presents county-level provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. County-level provisional counts include deaths occurring within the 50 states and the District of Columbia, as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation resulting in an underestimate relative to final counts (see Technical Notes). The provisional data presented on the dashboard below include reported 12 month-ending provisional counts of death due to drug overdose by the decedent’s county of residence and the month in which death occurred. Percentages of deaths with a cause of death pending further investigation and a note on historical completeness (e.g. if the percent completeness was under 90% after 6 months) are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical Notes). Counts between 1-9 are suppressed in accordance with NCHS confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Technical Notes Nature and Sources of Data Provisional drug overdose death counts are based on death records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. The cutoff date is generally the first Sunday of each month. National provisional estimates include deaths occurring within the 50 states and the District of Columbia. NCHS receives the death records from the state vital registration offices through the Vital Statistics Cooperative Program (VSCP). The timeliness of provisional mortality surveillance data in the National Vital Statistics System (NVSS) database varies by cause of death and jurisdiction in which the death occurred. The lag time (i.e., the time between when the death occurred and when the data are available for analysis) is longer for drug overdose deaths compared with other causes of death due to the time often needed to investigate these deaths (1). Thus, provisional estimates of drug overdose deaths are reported 6 months after the date of death. Provisional death counts presented in this data visualization are for “12 month-ending periods,” defined as the number of deaths occurring in the 12 month period ending in the month indicated. For example, the 12 month-ending period in June 2020 would include deaths occurring from July 1, 2019 through June 30, 2020. The 12 month-ending period counts include all seasons of the year and are insensitive to reporting variations by seasonality. These provisional counts of drug overdose deaths and related data quality metrics are provided for public health surveillance and monitoring of emerging trends. Provisional drug overdose death data are often incomplete, and the degree of completeness varies by jurisdiction and 12 month-ending period. Consequently, the numbers of drug overdose deaths are underestimated based on provisional data relative to final data and are subject to random variation. Cause of Death Classification and Definition of Drug Deaths Mortality statistics are compiled in accordance with the World Health Organizations (WHO) regulations specifying that WHO member nations classify and code causes of death with the current revision of the International Statistical Classification of Diseases and Related Health Problems (ICD). ICD provides the basic guidance used in virtually all countries to code and classify causes of death. It provides not only disease, injury, and poisoning categories but also the rules used to select the single underlying cause of death for tabulation from the several diagnoses that may be reported on a single death certificate, as well as definitions, tabulation lists, the format of the death certificate, and regul

Due to strict secrecy of the statistics of prisoners and criminality on the side of the authorities of the former GDR, it is difficult to estimate the number of political prisoners. Earlier estimates differ significantly from each other depending on the used sources, definition of terms, estimation methods and on the investigation period. As a starting point the term ‘Political Prisoner’ in the DDR was defined and operationalized. Based on this conceptual term definition the explorative study then aims to estimate the number of political investigation proceedings, political crimes, political criminals and convicts between 1945 and 1990 in the SBZ/GDR. These numbers help to evaluate the number of political prisoners also with regard to the total number of prisoners. In the research process not only the number of political prisoners was searched but also social and demographical data for prisoners and statistics on the penal system and so on, in order to give possibilities for further research and to enable a deeper analysis. The upper boundary for potentially political prisoners is estimated with 280000, the lower boundary is estimated with 170000 political cases. Aufgrund der strengen Geheimhaltung der Gefangenen- und Kriminalitätsstatistik von Seiten der Behörden der ehemaligen DDR kann heute die einfache Frage nach der Anzahl politischer Strafgefangener nicht einfach beantwortet werden. Bisherige Schätzungen weichen je nach verwendeten Quellen, Begriffsdefinitionen, Schätzmethoden und Untersuchungszeitraum voneinander ab. Zunächst ist als Ausgangspunkt der Begriff des politischen Gefangenen in der DDR definiert und operationalisiert worden. Die als explorativ verstandene Studie versucht dann auf dieser begrifflichen Grundlage abzuschätzen, wie viele politische Ermittlungsverfahren, politische Straftaten, politische Täter und Verurteilte es ab 1945 bis 1990 in der SBZ/DDR gab, um so die Anzahl der politischen Häftlinge, auch im Verhältnis zu der Anzahl der Häftlinge der allgemeinen Kriminalität, besser bewerten zu können. Bei den Recherchen wurde nicht nur nach der Anzahl der politischen Häftlinge gesucht, sondern auch nach sozialen und demographischen Angaben, nach Statistiken zum inneren Strafvollzug usw., um damit Möglichkeiten für die weitere Forschung und eine tiefere Analyse zu eröffnen. Als obere Anzahl von potentiellen Strafgefangenen mit politischem Einschlag wird von einer Schätzung von 280.000 Fällen ausgegangen; die untere Marge liegt eher bei 170.000 politischen Fällen. The basic sources for this study are the statistics from the respective administration offices and authorities (penal system, public prosecutor and courts) and from the ministries of the DDR (MdJ, MDI). These statistics were kept confidential until 1990. The following main inventories are relevant for the analysis of political prisoners: - Prisoner´s files of the states, - Federal commissioner for the documents of the state security service of the former GDR, - Federal archive (department V, Berlin), federal archive (military archive department, Freiburg), - Collection of judgements and legal principle file (Rechtsatzkartei), - Criminal record and offender index, - Central release card index of prisoners of the former penal system administration, - Electronical files of the penal system administration on prisoners and arrested persons (Project NRA, Project NRB, Project NRC), - Published and non-published statistics of the GDR criminal statistics. Als Quellenbasis für das Tabellenwerk dienten die bis 1990 geheim gehaltenen Statistiken aus den entsprechenden Verwaltungen, Behörden (Strafvollzug, Generalstaatsanwalt und Gerichte) und Ministerien der DDR (MdJ, MDI). Folgende Hauptbestände sind für die Analyse der Politischen Strafgefangenen relevant: - Strafgefangenenakten der Länder, - Bundesbeauftragter für die Unterlagen des Staatssicherheitsdienstes der ehemaligen DDR, - Bundesarchiv (Abteilung V, Berlin), Bundesarchiv (Abteilung Militärarchiv, Freiburg), - Urteilssammlungen und Rechtsatzkartei, - Strafregister und Täterindex, - Zentrale Entlassungskartei von Strafgefangenen der ehemaligen Verwaltung Strafvollzug, - Elektronische Strafgefangenen- und Verhaftetendateien der Verwaltung Strafvollzug (Projekt NRA, Projekt NRB, Projekt NRC), - veröffentlichte und unveröffentlichte Statistiken der DDR-Kriminalitätsstatistik.

Key Table Information.Table Title.Wholesale Trade: Employment by Primary Function for the U.S.: 2022.Table ID.ECNEMPFUNC2022.EC2242EMPFUNC.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Sector 42: Wholesale Trade.Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-07-10.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of establishmentsAnnual payroll ($1,000)Number of employeesResponse coverage of employment by function inquiry (%)Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. level only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 7-digit 2022 NAICS code levels and selected 8-digit 2022 NAICS-based code levels. For information about NAICS, see Economic Census Code Lists..Business Characteristics.For Wholesale Trade (42), data are presented by Type of Operation (All Establishments; Merchant Wholesalers, except Manufacturers' Sales Branches and Offices; and Manufacturers' Sales Branches and Offices)..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For some data on this table, estimates come only from the establishments selected into the sample. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.For some data on this table, estimates come only from the establishments selected into the sample. For these estimates, selected establishments have sampling weights equal to the inverse of their selection probability, generally between 1 and 40. There is further weighting to account for nonresponse and to ensure that detailed estimates sum to basic statistics where applicable. For more information on weighting, see 2022 Economic Census Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector42/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response...

This dataset includes all Robbery occurrences by reported date and related offences since 2014.Robbery DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This dataset includes all assault occurrences by reported date and related offences since 2014.Assault DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

Toronto Neighbourhoods Boundary File includes Crime Data by Neighbourhood. Counts are available at the offence and/or victim level for Assault, Auto Theft, Bike Theft, Break and Enter, Robbery, Theft Over, Homicide, Shootings and Theft from Motor Vehicle. Data also includes crime rates per 100,000 people by neighbourhood based on each year's Projected Population by Environics Analytics.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario..In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

This dataset includes all Motor Vehicle Collision (MVC) occurrences by their occurrence date and related offences. The MVC categories include property damage (PD) collisions, Fail to Remain (FTR) collisions, injury collisions and fatalities. This data is provided at the occurrence level, therefore multiple offences and/or victims can be associated with each record. Traffic Collisions DashboardDownload DocumentationIn this dataset, a collision is defined as the contact resulting from the motion of a motor vehicle or streetcar or its load, which produces property damage, injury or death. The term collision indicates that the initial point of contact involved at least one motor vehicle or streetcar.Definitions:Fatal Collisions occur when an individual’s injuries from a MVC result in a fatality within 30 days. Please note this category excludes:(i) Occurrences on private property(ii) Occurrences related to sudden death prior to collision (suicide or medical episode)(iii) Occurrences where the individual has died more than 30 days after the collisionPersonal Injury Collisions occur when an individual involved in a MVC suffers personal injuries. Fail to Remain Collisions occur when an individual involved in a MVC fails to stop and provide their information at the scene of a collision.Property Damage Collisions occur when an individual’s property has been damaged in a MVC or the value of damages is less than $2,000 for all involved parties.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.