100+ datasets found
  1. c

    Average daily COVID-19 incidence rate per 100,000 population by town over...

    • s.cnmilf.com
    • data.ct.gov
    • +1more
    Updated Aug 12, 2023
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    data.ct.gov (2023). Average daily COVID-19 incidence rate per 100,000 population by town over the last two weeks - ARCHIVE [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/average-daily-covid-19-incidence-rate-per-100000-population-by-town-over-the-last-two-week
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    Dataset updated
    Aug 12, 2023
    Dataset provided by
    data.ct.gov
    Description

    As of 10/22/2020, this dataset is no longer being updated and has been replaced with a new dataset, which can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2 This dataset includes the average daily COVID-19 case rate per 100,000 population by town over the last two MMWR weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). These counts do not include cases among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities. This dataset will be updated weekly.

  2. B

    Data from: The prevalence of MS in the United States: a population-based...

    • borealisdata.ca
    Updated May 19, 2021
    + more versions
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    Mitchell T. Wallin; William J. Culpepper; Jonathan D. Campbell; Lorene M. Nelson; Annette Langer-Gould; Ruth Ann Marrie; Gary R. Cutter; Wendy E. Kaye; Laurie Wagner; Helen Tremlett; Stephen L. Buka; Piyameth Dilokthornsakul; Barbara Topol; Lie H. Chen; Nicholas G. LaRocca (2021). Data from: The prevalence of MS in the United States: a population-based estimate using health claims data [Dataset]. http://doi.org/10.5683/SP2/FDHAH7
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 19, 2021
    Dataset provided by
    Borealis
    Authors
    Mitchell T. Wallin; William J. Culpepper; Jonathan D. Campbell; Lorene M. Nelson; Annette Langer-Gould; Ruth Ann Marrie; Gary R. Cutter; Wendy E. Kaye; Laurie Wagner; Helen Tremlett; Stephen L. Buka; Piyameth Dilokthornsakul; Barbara Topol; Lie H. Chen; Nicholas G. LaRocca
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    United States
    Description

    AbstractObjective: To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets. Methods: A validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017. Results: The estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017. Conclusion: The estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions. Usage notesPrev of MS in the US-E-Appendix-Feb-19-2018

  3. Bolivia BO: Incidence of Tuberculosis: per 100,000 People

    • ceicdata.com
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    CEICdata.com, Bolivia BO: Incidence of Tuberculosis: per 100,000 People [Dataset]. https://www.ceicdata.com/en/bolivia/social-health-statistics/bo-incidence-of-tuberculosis-per-100000-people
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2010 - Dec 1, 2021
    Area covered
    Bolivia
    Description

    Bolivia BO: Incidence of Tuberculosis: per 100,000 People data was reported at 109.000 Ratio in 2021. This records an increase from the previous number of 103.000 Ratio for 2020. Bolivia BO: Incidence of Tuberculosis: per 100,000 People data is updated yearly, averaging 133.000 Ratio from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 184.000 Ratio in 2000 and a record low of 103.000 Ratio in 2020. Bolivia BO: Incidence of Tuberculosis: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Health Statistics. Incidence of tuberculosis is the estimated number of new and relapse tuberculosis cases arising in a given year, expressed as the rate per 100,000 population. All forms of TB are included, including cases in people living with HIV. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.;World Health Organization, Global Tuberculosis Report.;Weighted average;Aggregate data by groups are computed based on the groupings for the World Bank fiscal year in which the data was released by the World Health Organization. This is the Sustainable Development Goal indicator 3.3.2[https://unstats.un.org/sdgs/metadata/].

  4. g

    Community Health: Lyme Disease Incidence Rate per 100,000 by County Map:...

    • gimi9.com
    • data.wu.ac.at
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    Community Health: Lyme Disease Incidence Rate per 100,000 by County Map: Latest Data [Dataset]. https://gimi9.com/dataset/ny_6sxr-cqij
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    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This map shows the Lyme Disease incidence rate per 100,000 by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower incidence rates of Lyme Disease. The darker shaded counties have higher incidence rates of Lyme Disease. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.

  5. a

    Good Health and Well-Being

    • sdgs.amerigeoss.org
    • sdg-hub-template-wci-test-umn.hub.arcgis.com
    • +11more
    Updated Jun 21, 2022
    + more versions
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    arobby1971 (2022). Good Health and Well-Being [Dataset]. https://sdgs.amerigeoss.org/datasets/d03cb2ae606c43f89e5e14367cf755e7
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    Dataset updated
    Jun 21, 2022
    Dataset authored and provided by
    arobby1971
    Area covered
    Description

    Goal 3Ensure healthy lives and promote well-being for all at all agesTarget 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live birthsIndicator 3.1.1: Maternal mortality ratioSH_STA_MORT: Maternal mortality ratioIndicator 3.1.2: Proportion of births attended by skilled health personnelSH_STA_BRTC: Proportion of births attended by skilled health personnel (%)Target 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsIndicator 3.2.1: Under-5 mortality rateSH_DYN_IMRTN: Infant deaths (number)SH_DYN_MORT: Under-five mortality rate, by sex (deaths per 1,000 live births)SH_DYN_IMRT: Infant mortality rate (deaths per 1,000 live births)SH_DYN_MORTN: Under-five deaths (number)Indicator 3.2.2: Neonatal mortality rateSH_DYN_NMRTN: Neonatal deaths (number)SH_DYN_NMRT: Neonatal mortality rate (deaths per 1,000 live births)Target 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesIndicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsSH_HIV_INCD: Number of new HIV infections per 1,000 uninfected population, by sex and age (per 1,000 uninfected population)Indicator 3.3.2: Tuberculosis incidence per 100,000 populationSH_TBS_INCD: Tuberculosis incidence (per 100,000 population)Indicator 3.3.3: Malaria incidence per 1,000 populationSH_STA_MALR: Malaria incidence per 1,000 population at risk (per 1,000 population)Indicator 3.3.4: Hepatitis B incidence per 100,000 populationSH_HAP_HBSAG: Prevalence of hepatitis B surface antigen (HBsAg) (%)Indicator 3.3.5: Number of people requiring interventions against neglected tropical diseasesSH_TRP_INTVN: Number of people requiring interventions against neglected tropical diseases (number)Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-beingIndicator 3.4.1: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory diseaseSH_DTH_NCOM: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability)SH_DTH_NCD: Number of deaths attributed to non-communicable diseases, by type of disease and sex (number)Indicator 3.4.2: Suicide mortality rateSH_STA_SCIDE: Suicide mortality rate, by sex (deaths per 100,000 population)SH_STA_SCIDEN: Number of deaths attributed to suicide, by sex (number)Target 3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcoholIndicator 3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disordersSH_SUD_ALCOL: Alcohol use disorders, 12-month prevalence (%)SH_SUD_TREAT: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disorders (%)Indicator 3.5.2: Alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcoholSH_ALC_CONSPT: Alcohol consumption per capita (aged 15 years and older) within a calendar year (litres of pure alcohol)Target 3.6: By 2020, halve the number of global deaths and injuries from road traffic accidentsIndicator 3.6.1: Death rate due to road traffic injuriesSH_STA_TRAF: Death rate due to road traffic injuries, by sex (per 100,000 population)Target 3.7: By 2030, ensure universal access to sexual and reproductive health-care services, including for family planning, information and education, and the integration of reproductive health into national strategies and programmesIndicator 3.7.1: Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methodsSH_FPL_MTMM: Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods (% of women aged 15-49 years)Indicator 3.7.2: Adolescent birth rate (aged 10–14 years; aged 15–19 years) per 1,000 women in that age groupSP_DYN_ADKL: Adolescent birth rate (per 1,000 women aged 15-19 years)Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for allIndicator 3.8.1: Coverage of essential health servicesSH_ACS_UNHC: Universal health coverage (UHC) service coverage indexIndicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or incomeSH_XPD_EARN25: Proportion of population with large household expenditures on health (greater than 25%) as a share of total household expenditure or income (%)SH_XPD_EARN10: Proportion of population with large household expenditures on health (greater than 10%) as a share of total household expenditure or income (%)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationIndicator 3.9.1: Mortality rate attributed to household and ambient air pollutionSH_HAP_ASMORT: Age-standardized mortality rate attributed to household air pollution (deaths per 100,000 population)SH_STA_AIRP: Crude death rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_STA_ASAIRP: Age-standardized mortality rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_AAP_MORT: Crude death rate attributed to ambient air pollution (deaths per 100,000 population)SH_AAP_ASMORT: Age-standardized mortality rate attributed to ambient air pollution (deaths per 100,000 population)SH_HAP_MORT: Crude death rate attributed to household air pollution (deaths per 100,000 population)Indicator 3.9.2: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services)SH_STA_WASH: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (deaths per 100,000 population)Indicator 3.9.3: Mortality rate attributed to unintentional poisoningSH_STA_POISN: Mortality rate attributed to unintentional poisonings, by sex (deaths per 100,000 population)Target 3.a: Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries, as appropriateIndicator 3.a.1: Age-standardized prevalence of current tobacco use among persons aged 15 years and olderSH_PRV_SMOK: Age-standardized prevalence of current tobacco use among persons aged 15 years and older, by sex (%)Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allIndicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeSH_ACS_DTP3: Proportion of the target population with access to 3 doses of diphtheria-tetanus-pertussis (DTP3) (%)SH_ACS_MCV2: Proportion of the target population with access to measles-containing-vaccine second-dose (MCV2) (%)SH_ACS_PCV3: Proportion of the target population with access to pneumococcal conjugate 3rd dose (PCV3) (%)SH_ACS_HPV: Proportion of the target population with access to affordable medicines and vaccines on a sustainable basis, human papillomavirus (HPV) (%)Indicator 3.b.2: Total net official development assistance to medical research and basic health sectorsDC_TOF_HLTHNT: Total official development assistance to medical research and basic heath sectors, net disbursement, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_HLTHL: Total official development assistance to medical research and basic heath sectors, gross disbursement, by recipient countries (millions of constant 2018 United States dollars)Indicator 3.b.3: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basisSH_HLF_EMED: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis (%)Target 3.c: Substantially increase health financing and the recruitment, development, training and retention of the health workforce in developing countries, especially in least developed countries and small island developing StatesIndicator 3.c.1: Health worker density and distributionSH_MED_DEN: Health worker density, by type of occupation (per 10,000 population)SH_MED_HWRKDIS: Health worker distribution, by sex and type of occupation (%)Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risksIndicator 3.d.1: International Health Regulations (IHR) capacity and health emergency preparednessSH_IHR_CAPS: International Health Regulations (IHR) capacity, by type of IHR capacity (%)Indicator 3.d.2: Percentage of bloodstream infections due to selected antimicrobial-resistant organismsiSH_BLD_MRSA: Percentage of bloodstream infection due to methicillin-resistant Staphylococcus aureus (MRSA) among patients seeking care and whose

  6. a

    Data from: Goal 3: Ensure healthy lives and promote well-being for all at...

    • ethiopia-1-sdg.hub.arcgis.com
    • sdg-hub-template-test-local-2030.hub.arcgis.com
    • +6more
    Updated Jun 25, 2022
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    arobby1971 (2022). Goal 3: Ensure healthy lives and promote well-being for all at all ages [Dataset]. https://ethiopia-1-sdg.hub.arcgis.com/datasets/7a604f4fa223449e8491cc085f0be006
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    Dataset updated
    Jun 25, 2022
    Dataset authored and provided by
    arobby1971
    Description

    Goal 3Ensure healthy lives and promote well-being for all at all agesTarget 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live birthsIndicator 3.1.1: Maternal mortality ratioSH_STA_MORT: Maternal mortality ratioIndicator 3.1.2: Proportion of births attended by skilled health personnelSH_STA_BRTC: Proportion of births attended by skilled health personnel (%)Target 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsIndicator 3.2.1: Under-5 mortality rateSH_DYN_IMRTN: Infant deaths (number)SH_DYN_MORT: Under-five mortality rate, by sex (deaths per 1,000 live births)SH_DYN_IMRT: Infant mortality rate (deaths per 1,000 live births)SH_DYN_MORTN: Under-five deaths (number)Indicator 3.2.2: Neonatal mortality rateSH_DYN_NMRTN: Neonatal deaths (number)SH_DYN_NMRT: Neonatal mortality rate (deaths per 1,000 live births)Target 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesIndicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsSH_HIV_INCD: Number of new HIV infections per 1,000 uninfected population, by sex and age (per 1,000 uninfected population)Indicator 3.3.2: Tuberculosis incidence per 100,000 populationSH_TBS_INCD: Tuberculosis incidence (per 100,000 population)Indicator 3.3.3: Malaria incidence per 1,000 populationSH_STA_MALR: Malaria incidence per 1,000 population at risk (per 1,000 population)Indicator 3.3.4: Hepatitis B incidence per 100,000 populationSH_HAP_HBSAG: Prevalence of hepatitis B surface antigen (HBsAg) (%)Indicator 3.3.5: Number of people requiring interventions against neglected tropical diseasesSH_TRP_INTVN: Number of people requiring interventions against neglected tropical diseases (number)Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-beingIndicator 3.4.1: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory diseaseSH_DTH_NCOM: Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease (probability)SH_DTH_NCD: Number of deaths attributed to non-communicable diseases, by type of disease and sex (number)Indicator 3.4.2: Suicide mortality rateSH_STA_SCIDE: Suicide mortality rate, by sex (deaths per 100,000 population)SH_STA_SCIDEN: Number of deaths attributed to suicide, by sex (number)Target 3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcoholIndicator 3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disordersSH_SUD_ALCOL: Alcohol use disorders, 12-month prevalence (%)SH_SUD_TREAT: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and aftercare services) for substance use disorders (%)Indicator 3.5.2: Alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcoholSH_ALC_CONSPT: Alcohol consumption per capita (aged 15 years and older) within a calendar year (litres of pure alcohol)Target 3.6: By 2020, halve the number of global deaths and injuries from road traffic accidentsIndicator 3.6.1: Death rate due to road traffic injuriesSH_STA_TRAF: Death rate due to road traffic injuries, by sex (per 100,000 population)Target 3.7: By 2030, ensure universal access to sexual and reproductive health-care services, including for family planning, information and education, and the integration of reproductive health into national strategies and programmesIndicator 3.7.1: Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methodsSH_FPL_MTMM: Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods (% of women aged 15-49 years)Indicator 3.7.2: Adolescent birth rate (aged 10–14 years; aged 15–19 years) per 1,000 women in that age groupSP_DYN_ADKL: Adolescent birth rate (per 1,000 women aged 15-19 years)Target 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for allIndicator 3.8.1: Coverage of essential health servicesSH_ACS_UNHC: Universal health coverage (UHC) service coverage indexIndicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or incomeSH_XPD_EARN25: Proportion of population with large household expenditures on health (greater than 25%) as a share of total household expenditure or income (%)SH_XPD_EARN10: Proportion of population with large household expenditures on health (greater than 10%) as a share of total household expenditure or income (%)Target 3.9: By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contaminationIndicator 3.9.1: Mortality rate attributed to household and ambient air pollutionSH_HAP_ASMORT: Age-standardized mortality rate attributed to household air pollution (deaths per 100,000 population)SH_STA_AIRP: Crude death rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_STA_ASAIRP: Age-standardized mortality rate attributed to household and ambient air pollution (deaths per 100,000 population)SH_AAP_MORT: Crude death rate attributed to ambient air pollution (deaths per 100,000 population)SH_AAP_ASMORT: Age-standardized mortality rate attributed to ambient air pollution (deaths per 100,000 population)SH_HAP_MORT: Crude death rate attributed to household air pollution (deaths per 100,000 population)Indicator 3.9.2: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (exposure to unsafe Water, Sanitation and Hygiene for All (WASH) services)SH_STA_WASH: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (deaths per 100,000 population)Indicator 3.9.3: Mortality rate attributed to unintentional poisoningSH_STA_POISN: Mortality rate attributed to unintentional poisonings, by sex (deaths per 100,000 population)Target 3.a: Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries, as appropriateIndicator 3.a.1: Age-standardized prevalence of current tobacco use among persons aged 15 years and olderSH_PRV_SMOK: Age-standardized prevalence of current tobacco use among persons aged 15 years and older, by sex (%)Target 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allIndicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeSH_ACS_DTP3: Proportion of the target population with access to 3 doses of diphtheria-tetanus-pertussis (DTP3) (%)SH_ACS_MCV2: Proportion of the target population with access to measles-containing-vaccine second-dose (MCV2) (%)SH_ACS_PCV3: Proportion of the target population with access to pneumococcal conjugate 3rd dose (PCV3) (%)SH_ACS_HPV: Proportion of the target population with access to affordable medicines and vaccines on a sustainable basis, human papillomavirus (HPV) (%)Indicator 3.b.2: Total net official development assistance to medical research and basic health sectorsDC_TOF_HLTHNT: Total official development assistance to medical research and basic heath sectors, net disbursement, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_HLTHL: Total official development assistance to medical research and basic heath sectors, gross disbursement, by recipient countries (millions of constant 2018 United States dollars)Indicator 3.b.3: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basisSH_HLF_EMED: Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis (%)Target 3.c: Substantially increase health financing and the recruitment, development, training and retention of the health workforce in developing countries, especially in least developed countries and small island developing StatesIndicator 3.c.1: Health worker density and distributionSH_MED_DEN: Health worker density, by type of occupation (per 10,000 population)SH_MED_HWRKDIS: Health worker distribution, by sex and type of occupation (%)Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risksIndicator 3.d.1: International Health Regulations (IHR) capacity and health emergency preparednessSH_IHR_CAPS: International Health Regulations (IHR) capacity, by type of IHR capacity (%)Indicator 3.d.2: Percentage of bloodstream infections due to selected antimicrobial-resistant organismsiSH_BLD_MRSA: Percentage of bloodstream infection due to methicillin-resistant Staphylococcus aureus (MRSA) among patients seeking care and whose

  7. Crime prevalence rate per 100,000 inhabitants aged 18 and over in Mexico...

    • statista.com
    Updated Jun 30, 2025
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    Statista (2025). Crime prevalence rate per 100,000 inhabitants aged 18 and over in Mexico 2010-2023 [Dataset]. https://www.statista.com/statistics/1408370/rate-of-crime-prevalence-mexico/
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    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Mexico
    Description

    In 2023, the crime prevalence rate per 100,000 inhabitants aged 18 and over in Mexico stood at approximately ******. Between 2010 and 2023, the figure dropped by around ***, though the decline followed an uneven course rather than a steady trajectory.

  8. T

    Haiti - Incidence Of Tuberculosis (per 100,000 People)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 2, 2017
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    TRADING ECONOMICS (2017). Haiti - Incidence Of Tuberculosis (per 100,000 People) [Dataset]. https://tradingeconomics.com/haiti/incidence-of-tuberculosis-per-100-000-people-wb-data.html
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    excel, json, xml, csvAvailable download formats
    Dataset updated
    Jun 2, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Haiti
    Description

    Incidence of tuberculosis (per 100,000 people) in Haiti was reported at 149 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Haiti - Incidence of tuberculosis (per 100,000 people) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  9. T

    Russia - Incidence Of Tuberculosis (per 100,000 People)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
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    TRADING ECONOMICS (2017). Russia - Incidence Of Tuberculosis (per 100,000 People) [Dataset]. https://tradingeconomics.com/russia/incidence-of-tuberculosis-per-100-000-people-wb-data.html
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    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    May 29, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Russia
    Description

    Incidence of tuberculosis (per 100,000 people) in Russia was reported at 38 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Incidence of tuberculosis (per 100,000 people) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

  10. w

    Community Health: All Cancer Incidence Rate per 100,000 by County Map:...

    • data.wu.ac.at
    • gimi9.com
    Updated Sep 14, 2017
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    Open Data NY - DOH (2017). Community Health: All Cancer Incidence Rate per 100,000 by County Map: Latest Data [Dataset]. https://data.wu.ac.at/odso/health_data_ny_gov/cDY1bi03eHp2
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    Open Data NY - DOH
    Description

    This map shows the incidence rate per 100,000 for all cancer types by county. Counties are shaded based on quartile distribution. The lighter shaded counties have lower cancer incidence rates. The darker shaded counties have higher cancer incidence rates. New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and are updated annually to consolidate and improve data linkages for the health indicators included in the County Health Assessment Indicators (CHAI) for all communities in New York. The CHIRS present data for more than 300 health indicators that are organized by 15 different health topics. Data if provided for all 62 New York State counties, 11 regions (including New York City), the State excluding New York City, and New York State. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/. The "About" tab contains additional details concerning this dataset.

  11. T

    Lebanon - Incidence Of Tuberculosis (per 100,000 People)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
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    TRADING ECONOMICS (2017). Lebanon - Incidence Of Tuberculosis (per 100,000 People) [Dataset]. https://tradingeconomics.com/lebanon/incidence-of-tuberculosis-per-100-000-people-wb-data.html
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    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    May 29, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Lebanon
    Description

    Incidence of tuberculosis (per 100,000 people) in Lebanon was reported at 10 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Lebanon - Incidence of tuberculosis (per 100,000 people) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  12. Colombia CO: Incidence of Tuberculosis: per 100,000 People

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Colombia CO: Incidence of Tuberculosis: per 100,000 People [Dataset]. https://www.ceicdata.com/en/colombia/social-health-statistics/co-incidence-of-tuberculosis-per-100000-people
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Colombia
    Description

    Colombia CO: Incidence of Tuberculosis: per 100,000 People data was reported at 46.000 Ratio in 2023. This records a decrease from the previous number of 47.000 Ratio for 2022. Colombia CO: Incidence of Tuberculosis: per 100,000 People data is updated yearly, averaging 33.000 Ratio from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 47.000 Ratio in 2022 and a record low of 30.000 Ratio in 2005. Colombia CO: Incidence of Tuberculosis: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Health Statistics. Incidence of tuberculosis is the estimated number of new and relapse tuberculosis cases arising in a given year, expressed as the rate per 100,000 population. All forms of TB are included, including cases in people living with HIV. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.;World Health Organization, Global Tuberculosis Report.;Weighted average;Aggregate data by groups are computed based on the groupings for the World Bank fiscal year in which the data was released by the World Health Organization. This is the Sustainable Development Goal indicator 3.3.2[https://unstats.un.org/sdgs/metadata/].

  13. Crime prevalence rate per 100,000 inhabitants aged 18 and over in Mexico...

    • statista.com
    Updated Jun 30, 2025
    + more versions
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    Statista (2025). Crime prevalence rate per 100,000 inhabitants aged 18 and over in Mexico State 2023 [Dataset]. https://www.statista.com/statistics/1408687/rate-of-crime-prevalence-mexico-state/
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    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Mexico
    Description

    The crime prevalence rate per 100,000 inhabitants aged 18 and over in Mexico State stood at approximately ****** in 2023. Between 2010 and 2023, the rate rose by around *****, though the increase followed an uneven trajectory rather than a consistent upward trend.

  14. Prevalence of 15 neglected tropical diseases worldwide from 1990 to 2020

    • statista.com
    Updated Jan 2, 2023
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    Statista (2023). Prevalence of 15 neglected tropical diseases worldwide from 1990 to 2020 [Dataset]. https://www.statista.com/statistics/1344875/prevalence-of-neglected-tropical-diseases-worldwide/
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    Dataset updated
    Jan 2, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 1990, there were around 43.1 thousand cases of 15 neglected tropical diseases (NTDs) per 100,000 population worldwide. By 2020, that figure had decreased to only around 12.1 thousand cases per 100,000 population. This statistic illustrates the prevalence of 15 neglected tropical diseases worldwide from 1990 to 2020.

  15. r

    Hepatitis B incidence per 100,000 population

    • researchdata.edu.au
    • cloud.csiss.gmu.edu
    • +1more
    Updated May 29, 2018
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    Sustainable Development Goals (2018). Hepatitis B incidence per 100,000 population [Dataset]. https://researchdata.edu.au/hepatitis-b-incidence-100000-population/2982013
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    Dataset updated
    May 29, 2018
    Dataset provided by
    data.gov.au
    Authors
    Sustainable Development Goals
    License

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

    Description

    Notification Rate of Hepatitis B per 100,000 population, 2015 to 2020\r \r Rates are not available per 1,000 population, however they are available per 100,000 population.\r \r Hepatitis B cases are notified as either: newly acquired, where evidence was available that the infection was acquired within 24 months prior to diagnosis; or unspecified, where the infection was acquired more than 24 months prior diagnosis or the period of infection is unspecified. \r \r Determination of a case as newly acquired is reliant on public health follow-up and the availability of previous serology test results, with the method and intensity of follow-up varying by jurisdiction and over time. This makes interpretation of incidence using only notification data difficult. For the purposes of this indicator notification rates for both unspecified and newly acquired hepatitis B are presented in the table below and represent prevalence as a surrogate for incidence.\r \r It is important to recognise that for hepatitis B infections, notifications to the National Notifiable Disease Surveillance System (NNDSS) represent only a proportion of the total cases and may be influenced by changes to testing patterns.\r \r Further information can be found here > http://www9.health.gov.au/cda/source/cda-index.cfm \r \r

  16. M

    Mauritania MR: Incidence of Tuberculosis: per 100,000 People

    • ceicdata.com
    Updated Feb 4, 2021
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    CEICdata.com (2021). Mauritania MR: Incidence of Tuberculosis: per 100,000 People [Dataset]. https://www.ceicdata.com/en/mauritania/health-statistics/mr-incidence-of-tuberculosis-per-100000-people
    Explore at:
    Dataset updated
    Feb 4, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Mauritania
    Description

    Mauritania MR: Incidence of Tuberculosis: per 100,000 People data was reported at 102.000 Ratio in 2016. This records a decrease from the previous number of 107.000 Ratio for 2015. Mauritania MR: Incidence of Tuberculosis: per 100,000 People data is updated yearly, averaging 151.000 Ratio from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 250.000 Ratio in 2000 and a record low of 102.000 Ratio in 2016. Mauritania MR: Incidence of Tuberculosis: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mauritania – Table MR.World Bank: Health Statistics. Incidence of tuberculosis is the estimated number of new and relapse tuberculosis cases arising in a given year, expressed as the rate per 100,000 population. All forms of TB are included, including cases in people living with HIV. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.; ; World Health Organization, Global Tuberculosis Report.; Weighted average;

  17. d

    Number Of Cases And Incidence Rate (Per 100,000 Population) Of communicable...

    • archive.data.gov.my
    Updated Mar 23, 2021
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    (2021). Number Of Cases And Incidence Rate (Per 100,000 Population) Of communicable Diseases, Malaysia - Dataset - MAMPU [Dataset]. https://archive.data.gov.my/data/dataset/number-of-cases-and-incidence-rate-per-100000-population-of-communicable-diseases-malaysia
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    Dataset updated
    Mar 23, 2021
    License

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

    Area covered
    Malaysia
    Description

    This dataset shows the Number Of Cases And Incidence Rate (Per 100,000 Population) Of communicable Diseases, Malaysia, 2000 - 2021. Footnote: Incidence rate is per 100,000 population Source : Ministry of Health, Malaysia No. of Views : 543

  18. Incidence rate AIDS Japan 2012-2021

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Incidence rate AIDS Japan 2012-2021 [Dataset]. https://www.statista.com/statistics/799184/japan-aids-incidence-rate/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Japan
    Description

    In 2021, the number of acquired immunodeficiency syndrome (AIDS) per 100,000 inhabitants in Japan did not change in comparison to the previous year. The number of acquired immunodeficiency syndrome (AIDS) per 100,000 inhabitants remained at *** cases per ******** inhabitants. Find more statistics on other topics about Japan with key insights such as incidence rate for measles per 100,000 population and number of acquired immunodeficiency syndrome (AIDS).

  19. F

    French Polynesia PF: Incidence of Tuberculosis: per 100,000 People

    • ceicdata.com
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    CEICdata.com, French Polynesia PF: Incidence of Tuberculosis: per 100,000 People [Dataset]. https://www.ceicdata.com/en/french-polynesia/health-statistics/pf-incidence-of-tuberculosis-per-100000-people
    Explore at:
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Polynesia, French Polynesia
    Description

    French Polynesia PF: Incidence of Tuberculosis: per 100,000 People data was reported at 20.000 Ratio in 2016. This records an increase from the previous number of 19.000 Ratio for 2015. French Polynesia PF: Incidence of Tuberculosis: per 100,000 People data is updated yearly, averaging 24.000 Ratio from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 31.000 Ratio in 2006 and a record low of 18.000 Ratio in 2010. French Polynesia PF: Incidence of Tuberculosis: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s French Polynesia – Table PF.World Bank.WDI: Health Statistics. Incidence of tuberculosis is the estimated number of new and relapse tuberculosis cases arising in a given year, expressed as the rate per 100,000 population. All forms of TB are included, including cases in people living with HIV. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.; ; World Health Organization, Global Tuberculosis Report.; Weighted average;

  20. b

    Incidence of Tuberculosis (TB) per 100,000 population - WMCA

    • cityobservatory.birmingham.gov.uk
    csv, excel, geojson +1
    Updated Jul 2, 2025
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    (2025). Incidence of Tuberculosis (TB) per 100,000 population - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/incidence-of-tb-per-100000-population-wmca/
    Explore at:
    csv, geojson, excel, jsonAvailable download formats
    Dataset updated
    Jul 2, 2025
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    The three-year average incidence of TB per 100,000 population is calculated by dividing the numerator (the number of TB notifications in the 3-year period) by the denominator (the sum of the mid-year population estimates for the same 3-year period) and multiplying by 100,000.

    Data for all previous years are updated using the most recent TB notification dataset. This update means that the values for a given area and year may be different (either smaller or larger) when compared to what has been shown on this profile in the past.Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

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data.ct.gov (2023). Average daily COVID-19 incidence rate per 100,000 population by town over the last two weeks - ARCHIVE [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/average-daily-covid-19-incidence-rate-per-100000-population-by-town-over-the-last-two-week

Average daily COVID-19 incidence rate per 100,000 population by town over the last two weeks - ARCHIVE

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Dataset updated
Aug 12, 2023
Dataset provided by
data.ct.gov
Description

As of 10/22/2020, this dataset is no longer being updated and has been replaced with a new dataset, which can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2 This dataset includes the average daily COVID-19 case rate per 100,000 population by town over the last two MMWR weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). These counts do not include cases among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities. This dataset will be updated weekly.

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