100+ datasets found
  1. Average number of cases handled by attorneys in Japan 2021, by type of case

    • statista.com
    Updated Oct 23, 2023
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    Statista (2023). Average number of cases handled by attorneys in Japan 2021, by type of case [Dataset]. https://www.statista.com/statistics/1417383/japan-number-cases-per-attorney-by-type-of-case/
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    Dataset updated
    Oct 23, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Japan
    Description

    In 2021, the average number of domestic cases administered at family courts in Japan per attorney amounted to 3.1. In that year, domestic court cases had a slightly higher attorney-to-case ratio when compared to civil cases.

  2. Weekly United States COVID-19 Cases and Deaths by State - ARCHIVED

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Jun 1, 2023
    + more versions
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    CDC COVID-19 Response (2023). Weekly United States COVID-19 Cases and Deaths by State - ARCHIVED [Dataset]. https://data.cdc.gov/Case-Surveillance/Weekly-United-States-COVID-19-Cases-and-Deaths-by-/pwn4-m3yp
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    csv, application/rdfxml, xml, tsv, json, application/rssxmlAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description

    Reporting of new Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

    Aggregate Data Collection Process Since the start of the COVID-19 pandemic, data have been gathered through a robust process with the following steps:

    • A CDC data team reviews and validates the information obtained from jurisdictions’ state and local websites via an overnight data review process.
    • If more than one official county data source exists, CDC uses a comprehensive data selection process comparing each official county data source, and takes the highest case and death counts respectively, unless otherwise specified by the state.
    • CDC compiles these data and posts the finalized information on COVID Data Tracker.
    • County level data is aggregated to obtain state and territory specific totals.
    This process is collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provide the most up-to-date numbers on cases and deaths by report date. CDC may retrospectively update counts to correct data quality issues.

    Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version:

    • Source: The current Weekly-Updated Version is based on county-level aggregate count data, while the Archived Version is based on State-level aggregate count data.
    • Confirmed/Probable Cases/Death breakdown:  While the probable cases and deaths are included in the total case and total death counts in both versions (if applicable), they were reported separately from the confirmed cases and deaths by jurisdiction in the Archived Version.  In the current Weekly-Updated Version, the counts by jurisdiction are not reported by confirmed or probable status (See Confirmed and Probable Counts section for more detail).
    • Time Series Frequency: The current Weekly-Updated Version contains weekly time series data (i.e., one record per week per jurisdiction), while the Archived Version contains daily time series data (i.e., one record per day per jurisdiction).
    • Update Frequency: The current Weekly-Updated Version is updated weekly, while the Archived Version was updated twice daily up to October 20, 2022.
    Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

    Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report probable cases and deaths to CDC.* Confirmed and probable case definition criteria are described here:

    Council of State and Territorial Epidemiologists (ymaws.com).

    Deaths CDC reports death data on other sections of the website: CDC COVID Data Tracker: Home, CDC COVID Data Tracker: Cases, Deaths, and Testing, and NCHS Provisional Death Counts. Information presented on the COVID Data Tracker pages is based on the same source (total case counts) as the present dataset; however, NCHS Death Counts are based on death certificates that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Data from each of these pages are considered provisional (not complete and pending verification) and are therefore subject to change. Counts from previous weeks are continually revised as more records are received and processed.

    Number of Jurisdictions Reporting There are currently 60 public health jurisdictions reporting cases of COVID-19. This includes the 50 states, the District of Columbia, New York City, the U.S. territories of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S Virgin Islands as well as three independent countries in compacts of free association with the United States, Federated States of Micronesia, Republic of the Marshall Islands, and Republic of Palau. New York State’s reported case and death counts do not include New York City’s counts as they separately report nationally notifiable conditions to CDC.

    CDC COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths, available by state and by county. These and other data on COVID-19 are available from multiple public locations, such as:

    https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html

    https://www.cdc.gov/covid-data-tracker/index.html

    https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html

    https://www.cdc.gov/coronavirus/2019-ncov/php/open-america/surveillance-data-analytics.html

    Additional COVID-19 public use datasets, include line-level (patient-level) data, are available at: https://data.cdc.gov/browse?tags=covid-19.

    Archived Data Notes:

    November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 3, 2022, instead of the customary 7 days’ worth of data.

    November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 10, 2022, instead of the customary 7 days’ worth of data.

    November 10, 2022: Per the request of the jurisdiction, cases and deaths among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case and death counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases and deaths. 

    November 17, 2022: Two new columns, weekly historic cases and weekly historic deaths, were added to this dataset on November 17, 2022. These columns reflect case and death counts that were reported that week but were historical in nature and not reflective of the current burden within the jurisdiction. These historical cases and deaths are not included in the new weekly case and new weekly death columns; however, they are reflected in the cumulative totals provided for each jurisdiction. These data are used to account for artificial increases in case and death totals due to batched reporting of historical data.

    December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the data released on December 1, 2022.

    January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case and death data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case and death metrics will appear higher than expected in the January 5, 2023, weekly release.

    January 12, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0. As a result, case and death metrics will appear lower than expected in the January 12, 2023, weekly release.

    January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case and death data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release.

    January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties (Livingston and Washtenaw) were higher than expected in the January 19, 2023 weekly release.

    January 26, 2023: Due to a backlog of historic COVID-19 cases being reported this week, aggregate case and death counts in Charlotte County and Sarasota County, Florida, will appear higher than expected in the January 26, 2023 weekly release.

    January 26, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0 in the weekly release posted on January 26, 2023.

    February 2, 2023: As of the data collection deadline, CDC observed an abnormally large increase in aggregate COVID-19 cases and deaths reported for Washington State. In response, totals for new cases and new deaths released on February 2, 2023, have been displayed as zero at the state level until the issue is addressed with state officials. CDC is working with state officials to address the issue.

    February 2, 2023: Due to a decrease reported in cumulative case counts by Wyoming, case rates will be reported as 0 in the February 2, 2023, weekly release. CDC is working with state officials to verify the data submitted.

    February 16, 2023: Due to data processing delays, Utah’s aggregate case and death data will be reported as 0 in the weekly release posted on February 16, 2023. As a result, case and death metrics will appear lower than expected and should be interpreted with caution.

    February 16, 2023: Due to a reporting cadence change, Maine’s

  3. Average number of court cases per year in Romania 2013-2019

    • statista.com
    Updated May 23, 2024
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    Statista (2024). Average number of court cases per year in Romania 2013-2019 [Dataset]. https://www.statista.com/statistics/1110408/court-cases-per-year-romania/
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    Dataset updated
    May 23, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Romania
    Description

    Many judges in Romania were overwhelmed by the increasing number of cases handled each year. In 2019, a judge at the Appeal Courts had to solve approximately 544 cases. Furthermore, the average number of cases a judge had to solve per year at the High Court of Cassation and Justice rose up to 1153.

  4. d

    State's Attorney Felony Cases - Average Case Length and Sum of Length, By...

    • catalog.data.gov
    • datacatalog.cookcountyil.gov
    • +4more
    Updated Jul 5, 2025
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    datacatalog.cookcountyil.gov (2025). State's Attorney Felony Cases - Average Case Length and Sum of Length, By Offense Type [Dataset]. https://catalog.data.gov/dataset/states-attorney-felony-cases-average-case-length-and-sum-of-length-by-offense-type
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    Dataset updated
    Jul 5, 2025
    Dataset provided by
    datacatalog.cookcountyil.gov
    Description

    Sum of Length is an internal calculation used to produce the Average Case Length in a specific offense category. Neither should be read to be associated with any individual case. Rather, the Sum of Length is the number of days in total spent on all the cases in which defendants were charged in a specific charge category combined. The Average Case Length in a particular charge category is then derived by dividing the Sum of Length by the number of defendants.

  5. COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates -...

    • healthdata.gov
    • data.cityofchicago.org
    • +1more
    application/rdfxml +5
    Updated Apr 8, 2025
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    data.cityofchicago.org (2025). COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates - Historical [Dataset]. https://healthdata.gov/dataset/COVID-19-Daily-Rolling-Average-Case-Death-and-Hosp/sd6k-dtx6
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    csv, tsv, xml, json, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset has been retired and marked as historical-only.

    This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.

    All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.

    Only Chicago residents are included based on the home address as provided by the medical provider.

    Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.

    Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.

    Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.

    Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey

  6. d

    Number of Discharged Cases, Deaths, and Average Daily Stay at Hamad Medical...

    • data.gov.qa
    csv, excel, json
    Updated May 22, 2025
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    (2025). Number of Discharged Cases, Deaths, and Average Daily Stay at Hamad Medical Corporation Hospitals by Type of Disease [Dataset]. https://www.data.gov.qa/explore/dataset/health-statistics-number-of-discharged-cases-deaths-and-average-daily-stay-at-hamad-medical/
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    excel, json, csvAvailable download formats
    Dataset updated
    May 22, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset provides statistics on the number of discharged cases, deaths, and the average daily stay at Hamad Medical Corporation hospitals in Qatar. The information is categorized by disease type using ICD (International Classification of Diseases) codes, and spans multiple years. It offers insights into hospital performance, disease burden, and patient outcomes across a wide spectrum of medical conditions including infectious diseases, cancer, cardiovascular issues, and maternal health.

  7. Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and...

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Feb 22, 2023
    + more versions
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and Second Booster Dose [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/ukww-au2k
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    application/rdfxml, xml, csv, tsv, json, application/rssxmlAvailable download formats
    Dataset updated
    Feb 22, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

    Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

    Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138

  8. f

    Mean cumulative number of cases in the metropolitan U.S. under travel...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Joshua M. Epstein; D. Michael Goedecke; Feng Yu; Robert J. Morris; Diane K. Wagener; Georgiy V. Bobashev (2023). Mean cumulative number of cases in the metropolitan U.S. under travel restriction and vaccination intervention scenarios. [Dataset]. http://doi.org/10.1371/journal.pone.0000401.t003
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Joshua M. Epstein; D. Michael Goedecke; Feng Yu; Robert J. Morris; Diane K. Wagener; Georgiy V. Bobashev
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Base R0 = 1.7.1N: no intervention, TO: 95% travel restriction only, VO: 0.1% vaccination only, TV: both 95% travel restriction and 0.1% vaccination2The end of the epidemic is determined when there are no further cases worldwide.3These data represent means and standard deviations for all 100 runs, including the runs in which the disease did not develop a pandemic state and did not reach the U.S.

  9. d

    COVID-19 Daily Case Count in Jefferson County, KY

    • catalog.data.gov
    • data.lojic.org
    • +2more
    Updated Apr 13, 2023
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    Louisville/Jefferson County Information Consortium (2023). COVID-19 Daily Case Count in Jefferson County, KY [Dataset]. https://catalog.data.gov/dataset/covid-19-daily-case-count-in-jefferson-county-ky
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    Dataset updated
    Apr 13, 2023
    Dataset provided by
    Louisville/Jefferson County Information Consortium
    Area covered
    Jefferson County, Kentucky
    Description

    This data set is no longer being updated and is historical, last update 10/10/2022.A summary of reported data from CTT. This data includes: Daily counts as reported on the Reference Date for Confirmed, Deceased, Recovered. Total counts as reported on the Reference Date. Statistical data is based on the data as reported on the Reference Date (Counts per 100k population (2019 ACS), and 3-day average rates Fieldname Definition reported Reference date -For Confirmed cases, before CTT, use loaded date -For Confirmed cases, after CTT, use yesterday’s date CONFIRMED Number of new confirmed cases reported on reference date TOTAL_CONFIRMED Number of all confirmed cases reported on reference date DECEASED Number of cases newly marked as Deceased reported on reference date TOTAL_DECEASED Number of all cases marked as Deceased reported on reference date RECOVERED Number of cases newly marked recovered reported on reference date TOTAL_RECOVERED Number of all cases marked recovered reported on reference date WEEKBEGINNINGDATE The week beginning date for the Reported date WEEKENDINGDATE The week ending date for the Reported date YEAR_WEEK Year and week number of the Reported date Total_Population Estimated total population from the ref.ACS2019_demographics table Confirmed_RatePer100K Number of confirmed cases per 100K. CONFIRMED*100000.0/Total_Population Deceased_RatePer100K Number of cases marked as Deceased per 100K. DECEASED*100000.0/Total_Population Avg_3Day_Confirmed_RatePer100K Average of the Confirmed_RatePer100K for the current day and the 2 previous days. Avg_3Day_Deceased_RatePer100K Average of the Deceased_RatePer100K for the current day and the 2 previous days. Avg_3Day_Confirmed_RatePer100K_Diff Difference between the Avg_3Day_Confirmed_RatePer100K of the current day and previous day. Avg_3Day_Deceased_RatePer100K_Diff Difference between the Avg_3Day_ Deceased_RatePer100K of the current day and previous day. LOADED Date the data was loaded into the system For questions about this data please contact Angela Graham (Angela.Graham@louisvilleky.gov) or YuTing Chen (YuTing.Chen@louisvilleky.gov) or call (502) 574-8279.Note: This data is preliminary, routinely updated, and is subject to change.

  10. Average number of criminal cases per prosecutor in Romania 2019

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Average number of criminal cases per prosecutor in Romania 2019 [Dataset]. https://www.statista.com/statistics/1133829/romania-court-cases-per-prosecutor/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    Romania
    Description

    Many district prosecutors in Romania were overwhelmed by the increasing number of cases handled each year. In 2019, a Tribunal Prosecutor Office had to solve approximately *** cases a year.

  11. Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent)...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated May 30, 2023
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent) Booster Status [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/54ys-qyzm
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    xml, json, tsv, csv, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Updated (Bivalent) Booster Status. Click 'More' for important dataset description and footnotes

    Webpage: https://covid.cdc.gov/covid-data-tracker/#rates-by-vaccine-status

    Dataset and data visualization details:

    These data were posted and archived on May 30, 2023 and reflect cases among persons with a positive specimen collection date through April 22, 2023, and deaths among persons with a positive specimen collection date through April 1, 2023. These data will no longer be updated after May 2023.

    Vaccination status: A person vaccinated with at least a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. A person vaccinated with a primary series and a monovalent booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and at least one additional dose of any monovalent FDA-authorized or approved COVID-19 vaccine on or after August 13, 2021. (Note: this definition does not distinguish between vaccine recipients who are immunocompromised and are receiving an additional dose versus those who are not immunocompromised and receiving a booster dose.) A person vaccinated with a primary series and an updated (bivalent) booster dose had SARS-CoV-2 RNA or antigen detected in a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and an additional dose of any bivalent FDA-authorized or approved vaccine COVID-19 vaccine on or after September 1, 2022. (Note: Doses with bivalent doses reported as first or second doses are classified as vaccinated with a bivalent booster dose.) People with primary series or a monovalent booster dose were combined in the “vaccinated without an updated booster” category.

    Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Per the interim guidance of the Council of State and Territorial Epidemiologists (CSTE), this should include persons whose death certificate lists COVID-19 disease or SARS-CoV-2 as the underlying cause of death or as a significant condition contributing to death. Rates of COVID-19 deaths by vaccination status are primarily reported based on when the patient was tested for COVID-19. In select jurisdictions, deaths are included that are not laboratory confirmed and are reported based on alternative dates (i.e., onset date for most; or date of death or report date, where onset date is unavailable). Deaths usually occur up to 30 days after COVID-19 diagnosis.

    Participating jurisdictions: Currently, these 24 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Colorado, District of Columbia, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (NY), North Carolina, Rhode Island, Tennessee, Texas, Utah, and West Virginia; 23 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 48% of the total U.S. population and all ten of the Health and Human Services Regions. This list will be updated as more jurisdictions participate.

    Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with at least a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6-12 months, half of the single-year population counts for ages <12 months were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred.

    Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage.

    Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated without an updated (bivalent) booster dose) or vaccinated with an updated (bivalent) booster dose.

    Archive: An archive of historic data, including April 3, 2021-September 24, 2022 and posted on October 21, 2022 is available on data.cdc.gov. The analysis by vaccination status (unvaccinated and at least a primary series) for 31 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/3rge-nu2a. The analysis for one booster dose (unvaccinated, primary series only, and at least one booster dose) in 31 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/d6p8-wqjm. The analysis for two booster doses (unvaccinated, primary series only, one booster dose, and at least two booster doses) in 28 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/ukww-au2k.

    References

    Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290.

    Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138

    Johnson AG, Linde L, Ali AR, et al. COVID-19 Incidence and Mortality Among Unvaccinated and Vaccinated Persons Aged ≥12 Years by Receipt of Bivalent Booster Doses and Time Since Vaccination — 24 U.S. Jurisdictions, October 3, 2021–December 24, 2022. MMWR Morb Mortal Wkly Rep 2023;72:145–152

  12. a

    COVID-19 Trends in Each Country-Heb

    • coronavirus-response-israel-systematics.hub.arcgis.com
    • hub.arcgis.com
    Updated Apr 16, 2020
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    mory (2020). COVID-19 Trends in Each Country-Heb [Dataset]. https://coronavirus-response-israel-systematics.hub.arcgis.com/maps/f8b6e9872cac47aaa33b123d6e2de8d4
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    Dataset updated
    Apr 16, 2020
    Dataset authored and provided by
    mory
    Area covered
    Description

    COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.Reasons for undertaking this work:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-30 days + 5% from past 31-56 days - total deaths.We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source used as basis:Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates. 100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent one third of case days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 63 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:Last 2 days count of new cases is less than any in either the past five or 6-21 days. Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 6 to 21 days. Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:Past five days is greater than past 2 days and past 6-21 days indicates the potential of the past 2 days being an aberration. Past five days is greater than past 6-21 days and less than past 2 days indicates slight positive trend, but likely still within peak trend timeframe.Past five days is less than the past 6-21 days. This means a downward trend. This would be an important trend for any administrative area in an epidemic trend that the rate of spread is slowing.If less than the past 2 days, but not the last 6-21 days, this is still positive, but is not indicating a passage out of the peak timeframe of the daily new cases curve.Past 5 days has only one or two new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 6 to 21 days. Most recent 6-21 days: Represents the full tail of the curve and provides context for the past 2- and 5-day trends.If this is greater than both the 2- and 5-day trends, then a short-term downward trend has begun. Mean of Recent Tail NCD in the context of the Mean of All NCD, and raw counts of cases:Mean of Recent NCD is less than 0.5 cases per 100,000 = high level of controlMean of Recent NCD is less than 1.0 and fewer than 30 cases indicate continued emergent trend.3. Mean of Recent NCD is less than 1.0 and greater than 30 cases indicate a change from emergent to spreading trend.Mean of All NCD less than 2.0 per 100,000, and areas that have been in epidemic trends have Mean of Recent NCD of less than 5.0 per 100,000 is a significant indicator of changing trends from epidemic to spreading, now going in the direction of controlled trend.Similarly, in the context of Mean of All NCD greater than 2.0

  13. Average number of crimes per victim in Mexico State 2010-2023

    • statista.com
    Updated Jun 30, 2025
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    Statista (2025). Average number of crimes per victim in Mexico State 2010-2023 [Dataset]. https://www.statista.com/statistics/1408596/average-number-of-crimes-per-victim-mexico-state/
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    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Mexico
    Description

    The average number of crimes per victim in Mexico State was approximately **** in 2023. Between 2010 and 2023, the number rose by around ****, though the increase followed an uneven trajectory rather than a consistent upward trend.

  14. Reported Neuroinvasive Cases of West Nile Virus by State, 2002–2023

    • s.cnmilf.com
    • catalog.data.gov
    Updated Feb 25, 2025
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    U.S. Environmental Protection Agency, Office of Air and Radiation (Publisher) (2025). Reported Neuroinvasive Cases of West Nile Virus by State, 2002–2023 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/reported-neuroinvasive-cases-of-west-nile-virus-by-state-200220231
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    Dataset updated
    Feb 25, 2025
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Description

    This map shows the average annual incidence of neuroinvasive West Nile virus disease in each state, which is calculated as the average number of new cases per 100,000 people per year from 2002 to 2023. The map is based on cases that local and state health departments report to CDC’s national disease tracking system. Neuroinvasive cases are those that affect the brain or cause neurologic dysfunction. For more information: www.epa.gov/climate-indicators

  15. W

    Outcome of reported suspect cases in England by year and number confirmed by...

    • cloud.csiss.gmu.edu
    • environment.data.gov.uk
    • +2more
    csv
    Updated Jan 8, 2020
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    United Kingdom (2020). Outcome of reported suspect cases in England by year and number confirmed by other means [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/outcome-of-reported-suspect-cases-in-england-by-year-and-number-confirmed-by-other-means
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    csvAvailable download formats
    Dataset updated
    Jan 8, 2020
    Dataset provided by
    United Kingdom
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Area covered
    England
    Description

    This dataset covers the outcome of reported suspect BSE (Bovine Spongiform Encephalopathy) cases in England by year and number confirmed by other means. This dataset includes the fields: Year (of case); Restricted (number of animals where movement restrictions have been imposed); Alternative diagnosis (number that were given an alternative diagnosis to BSE); Alive (number of suspects alive); Slaughtered (number of animals slaughtered); Pending (number of cases with results pending); Not confirmed (number of suspect cases where BSE was not detected); Confirmed (number of cases where BSE was detected); Others confirmed (number confirmed by other means). Please note: this data is available as part of a wider report on TSE surveillance, published on gov.uk. Attribution statement:

  16. A

    ‘COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates’...

    • analyst-2.ai
    Updated Feb 13, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-covid-19-daily-rolling-average-case-death-and-hospitalization-rates-4f9c/e00a61e3/
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    Dataset updated
    Feb 13, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/7acadb5f-3204-4ca3-8e83-2741d562f100 on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    This is the place to look for important information about how to use this dataset, so please expand this box and read on!

    This is the source data for some of the metrics available at https://www.chicago.gov/city/en/sites/covid-19/home/latest-data.html.

    For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19.

    This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.

    All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.

    Only Chicago residents are included based on the home address as provided by the medical provider.

    Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.

    Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).

    All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.

    Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.

    Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey

    --- Original source retains full ownership of the source dataset ---

  17. ARCHIVED: COVID-19 Cases by Vaccination Status Over Time

    • healthdata.gov
    • data.sfgov.org
    application/rdfxml +5
    Updated Apr 8, 2025
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    data.sfgov.org (2025). ARCHIVED: COVID-19 Cases by Vaccination Status Over Time [Dataset]. https://healthdata.gov/dataset/ARCHIVED-COVID-19-Cases-by-Vaccination-Status-Over/evps-wwsc
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    application/rssxml, csv, json, application/rdfxml, tsv, xmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.sfgov.org
    Description

    On 6/28/2023, data on cases by vaccination status will be archived and will no longer update.

    A. SUMMARY This dataset represents San Francisco COVID-19 positive confirmed cases by vaccination status over time, starting January 1, 2021. Cases are included on the date the positive test was collected (the specimen collection date). Cases are counted in three categories: (1) all cases; (2) unvaccinated cases; and (3) completed primary series cases.

    1. All cases: Includes cases among all San Francisco residents regardless of vaccination status.

    2. Unvaccinated cases: Cases are considered unvaccinated if their positive COVID-19 test was before receiving any vaccine. Cases that are not matched to a COVID-19 vaccination record are considered unvaccinated.

    3. Completed primary series cases: Cases are considered completed primary series if their positive COVID-19 test was 14 days or more after they received their 2nd dose in a 2-dose COVID-19 series or the single dose of a 1-dose vaccine. These are also called “breakthrough cases.”

    On September 12, 2021, a new case definition of COVID-19 was introduced that includes criteria for enumerating new infections after previous probable or confirmed infections (also known as reinfections). A reinfection is defined as a confirmed positive PCR lab test more than 90 days after a positive PCR or antigen test. The first reinfection case was identified on December 7, 2021.

    Data is lagged by eight days, meaning the most recent specimen collection date included is eight days prior to today. All data updates daily as more information becomes available.

    B. HOW THE DATASET IS CREATED Case information is based on confirmed positive laboratory tests reported to the City. The City then completes quality assurance and other data verification processes. Vaccination data comes from the California Immunization Registry (CAIR2). The California Department of Public Health runs CAIR2. Individual-level case and vaccination data are matched to identify cases by vaccination status in this dataset. Case records are matched to vaccine records using first name, last name, date of birth, phone number, and email address.

    We include vaccination records from all nine Bay Area counties in order to improve matching rates. This allows us to identify breakthrough cases among people who moved to the City from other Bay Area counties after completing their vaccine series. Only cases among San Francisco residents are included.

    C. UPDATE PROCESS Updates automatically at 08:00 AM Pacific Time each day.

    D. HOW TO USE THIS DATASET Total San Francisco population estimates can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). To identify total San Francisco population estimates, filter the view on “demographic_category_label” = “all ages”.

    Population estimates by vaccination status are derived from our publicly reported vaccination counts, which can be found at COVID-19 Vaccinations Given to SF Residents Over Time.

    The dataset includes new cases, 7-day average new cases, new case rates, 7-day average new case rates, percent of total cases, and 7-day average percent of total cases for each vaccination category.

    New cases are the count of cases where the positive tests were collected on that specific specimen collection date. The 7-day rolling average shows the trend in new cases. The rolling average is calculated by averaging the new cases for a particular day with the prior 6 days.

    New case rates are the count of new cases per 100,000 residents in each vaccination status group. The 7-day rolling average shows the trend in case rates. The rolling average is calculated by averaging the case rate for a part

  18. T

    Average Annual Number Of Cases Of Hypospadias Among Live Male Births

    • opendata.utah.gov
    application/rdfxml +5
    Updated Oct 23, 2014
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    CDC (2014). Average Annual Number Of Cases Of Hypospadias Among Live Male Births [Dataset]. https://opendata.utah.gov/Health/Average-Annual-Number-Of-Cases-Of-Hypospadias-Amon/wa32-bme6
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    application/rssxml, json, csv, application/rdfxml, xml, tsvAvailable download formats
    Dataset updated
    Oct 23, 2014
    Dataset authored and provided by
    CDC
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Average Annual Number Of Cases Of Hypospadias Among Live Male Births

  19. Criminal court statistics quarterly: January to March 2017

    • gov.uk
    Updated Jun 29, 2017
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    Ministry of Justice (2017). Criminal court statistics quarterly: January to March 2017 [Dataset]. https://www.gov.uk/government/statistics/criminal-court-statistics-quarterly-january-to-march-2017
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    Dataset updated
    Jun 29, 2017
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    This is the first time data under the new suppliers of language services has been released. The use of interpreter statistics cover face-to-face spoken and non-spoken language interpreter services provided to MOJ bodies including HM Courts & Tribunals Service (HMCTS) and Her Majesty’s Prison and Probation Service (HMPPS). These services are supplied by contractors which changed from 31 October 2016.

    This is the annual 2016 criminal courts publication and includes additional information such as representation status of defendants, along with new Crown Court tables which present guilty pleas, waiting time and hearing time by offence groups for the first time, as preannounced last quarter. There is a new table included in the timeliness tables (T1) which covers the duration of Single Justice Procedure (SJP) cases, this will now be part of the quarterly tables pack.

    The Crown Court information release is published as management information on the https://www.judiciary.gov.uk/crown-court-information/" class="govuk-link">Courts and Tribunals Judiciary website.

    For future publications, the quarterly tables will be made up of M1 to M2, C1 to C8 and T1 to T6. Reasons for ineffective and cracked trials for both magistrates’ courts and Crown Court will now be part of the annual publication, along with timeliness by plea indicators (previously T1, now AT1). The waiting and hearing times data which was previously held in tables C8, C9, C10 and C11, are now held in two tables: table C6 contains all waiting times data and table C7 contains all hearing times data.

    Criminal courts

    • In 2016, disposals remained higher than receipts in magistrates’ courts which resulted in the number of outstanding cases dropping by 11% from 327,200 in 2015 to 291,400 in 2016. Provisional figures for Q1 2017 indicate outstanding cases have decreased by a further 1%.
    • In the Crown Court receipts and disposals fell during 2016, by 10% and 6% respectively from 2015. Disposals remained higher than receipts in 2016, continuing to drive the decrease in outstanding cases. Outstanding cases declined further between Q4 2016 and Q1 2017, by 5% to 40,000 cases, the lowest number since Q1 2013.
    • For cases completing in the Crown Court the average number of days from first listing at the magistrates’ court to completion in the Crown Court decreased by 2 days from 196 days in 2015 to 194 days in 2016. This is despite a quarterly peak of 218 days in Q4 2016, the highest of the time series, before decreasing to 178 days in Q1 2017. This decrease is possibly as a result of the courts having cleared some of their backlog of outstanding cases.

    Use of language interpreter and translation services

    • The success rate for completed language interpreter and translation service requests was 97% in Q1 2017, similar to Q1 2016.
    • The complaint rate in Q1 2017 was just under 2%, compared to just over 1% in Q1 2016.
    • The total number of ‘off contract’ service requests increased from 220 in Q1 2016 to 370 in Q1 2017. Off contract requests are used when a request cannot be supplied under the contract.

    Pre-release

    In addition to Ministry of Justice (MOJ) professional and production staff, pre-release access to the quarterly statistics of up to 24 hours is granted to the following postholders:

    MOJ

    Lord Chancellor and Secretary of State for Justice; Minister of State for Justice; Ministry of Justice spokesperson in the Lords; Lord Chief Justice; Permanent Secretary; Chief Financial Officer; Director, Criminal Justice Policy; Deputy Director, Criminal Courts Policy; Criminal Court Reform Lead; Jurisdictional and Operational Support Manager; Head of Analytical Services; Chief Statistician; Economic adviser to the Secretary of State; Attorney General’s Office; 3 Press Officers and 9 Private Secretaries.

    Her Majesty’s Court and Tribunals Service

    Chief Executive, HMCTS; Deputy Chief Executive, HMCTS; Deputy Director of Legal Services, Court Users and Summary Justice Reform; Head of Operational Performance; Head of Criminal Enforcement team, HMCTS; Head of data and management information, HMCTS; Head of Management Information Systems; Jurisdictional Operation manager and Head of Contracted Services and Performance for HMCTS Operations Directorate .

  20. k

    Month-wise Average Number of New Cases per Day in District Bannu Year 2021 -...

    • opendata.kp.gov.pk
    Updated Feb 15, 2022
    + more versions
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    (2022). Month-wise Average Number of New Cases per Day in District Bannu Year 2021 - Datasets - KP OpenData Portal [Dataset]. https://opendata.kp.gov.pk/dataset/month-wise-average-number-of-new-cases-per-day-in-district-bannu-year-2021
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    Dataset updated
    Feb 15, 2022
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Bannu
    Description

    Month-wise Average Number of New Cases per Day in District Bannu Year 2021

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Statista (2023). Average number of cases handled by attorneys in Japan 2021, by type of case [Dataset]. https://www.statista.com/statistics/1417383/japan-number-cases-per-attorney-by-type-of-case/
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Average number of cases handled by attorneys in Japan 2021, by type of case

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Dataset updated
Oct 23, 2023
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2021
Area covered
Japan
Description

In 2021, the average number of domestic cases administered at family courts in Japan per attorney amounted to 3.1. In that year, domestic court cases had a slightly higher attorney-to-case ratio when compared to civil cases.

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