100+ datasets found
  1. Electronic Health Information Legal Epidemiology Data Set 2014

    • catalog.data.gov
    • data.virginia.gov
    • +4more
    Updated Jul 11, 2025
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    Centers for Disease Control and Prevention (2025). Electronic Health Information Legal Epidemiology Data Set 2014 [Dataset]. https://catalog.data.gov/dataset/electronic-health-information-legal-epidemiology-data-set-2014
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Authors: Cason Schmit, JD, Gregory Sunshine, JD, Dawn Pepin, JD, MPH, Tara Ramanathan, JD, MPH, Akshara Menon, JD, MPH, Matthew Penn, JD, MLIS This legal data set consists of state statutes and regulations in effect as of January 1, 2014, related to electronic health information (EHI). Jurisdictions were limited to US states, territories, and the District of Columbia that had statutes and regulations in the Westlaw legal database that expressly referenced EHI. This data set includes 2,364 EHI-related laws representing 49 EHI uses in 54 jurisdictions. For information about research methods, please reference the Electronic Health Information Legal Epidemiology Protocol 2014.

  2. Citation categorized by Data Source.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 3, 2023
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    Courtney D. Corley; Laura L. Pullum; David M. Hartley; Corey Benedum; Christine Noonan; Peter M. Rabinowitz; Mary J. Lancaster (2023). Citation categorized by Data Source. [Dataset]. http://doi.org/10.1371/journal.pone.0091989.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Courtney D. Corley; Laura L. Pullum; David M. Hartley; Corey Benedum; Christine Noonan; Peter M. Rabinowitz; Mary J. Lancaster
    License

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

    Description

    If a model utilized data from multiple categories, it was placed in each.

  3. DataBases

    • figshare.com
    bin
    Updated Jul 31, 2022
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    Betty Manrique Espinoza (2022). DataBases [Dataset]. http://doi.org/10.6084/m9.figshare.20409273.v1
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    binAvailable download formats
    Dataset updated
    Jul 31, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Betty Manrique Espinoza
    License

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

    Description

    Project databases are attached

  4. n

    Gazel Database

    • neuinfo.org
    • scicrunch.org
    • +1more
    Updated Oct 9, 2009
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    (2009). Gazel Database [Dataset]. http://identifiers.org/RRID:SCR_008962
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    Dataset updated
    Oct 9, 2009
    Description

    A 20 year, 20,000 person, open longitudinal epidemiological study of a cohort town. GAZEL was not constructed to answer a specific question rather it was designed to help analyze a wide range of scientific problems and is accessible to the community of researchers specializing in epidemiology. Translation is not available for all pages. The GAZEL cohort, set up in 1989 by Inserm Unit 88 (subsequently Unit 687), in cooperation with several departments of ��lectricit�� de France-Gaz de France (EDF-GDF), was a public utility firm in France involved in production, transmission and distribution of energy. GAZEL initially included 20 624 volunteers working at EDF-GDF (15 010 men and 5614 women), aged from 35 to 50 years. In accordance with its purpose as a scientific research platform, the GAZEL cohort is permanently open to epidemiologic research teams. Today, more than 50 projects on very diversified themes have been set up in GAZEL by some 20 teams, French, belonging to different bodies, and foreign (Germany, Belgium, Canada, Great Britain, Sweden, Finland, and USA).

  5. Databases searched.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 1, 2023
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    Rebecca Mary Diane Smyth; Elizabeth Gargon; Jamie Kirkham; Lynne Cresswell; Su Golder; Rosalind Smyth; Paula Williamson (2023). Databases searched. [Dataset]. http://doi.org/10.1371/journal.pone.0024061.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Rebecca Mary Diane Smyth; Elizabeth Gargon; Jamie Kirkham; Lynne Cresswell; Su Golder; Rosalind Smyth; Paula Williamson
    License

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

    Description

    Databases searched.

  6. n

    Adult Blood Lead Epidemiology and Surveillance Interactive Database

    • neuinfo.org
    • dknet.org
    • +2more
    Updated May 9, 2010
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    (2010). Adult Blood Lead Epidemiology and Surveillance Interactive Database [Dataset]. http://identifiers.org/RRID:SCR_006915
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    Dataset updated
    May 9, 2010
    Description

    Interactive data set on lead exposure (Blood Lead Concentrations greater than or equal to 25 micrograms per deciliter) of adults in the United States. The data comes from laboratory-reported elevated blood lead levels. Recent research has led to increased concerns about the toxicity of lead at low doses. Reflecting this increased concern, the ABLES program updated its case definition for an elevated BLL to a blood lead concentration greater than or equal to 10 micrograms per deciliter in 2009. This new case definition has also been: (1) recommended by the Council of State and Territorial Epidemiologists in 2009; (2) included in CDC''s list of nationally notifiable conditions in 2010; and (3) adopted as the Healthy People 2020 Occupational Safety and Health Objective 7. Given this new case definition, NIOSH will update the ABLES Charts and Interactive Database to include lead exposures to blood lead level greater than or equal to 10 micrograms per deciliter in the near future.

  7. DataSheet1_An integrated platform for Brucella with knowledge graph...

    • frontiersin.figshare.com
    bin
    Updated Jun 2, 2023
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    Fubo Ma; Ming Xiao; Lin Zhu; Wen Jiang; Jizhe Jiang; Peng-Fei Zhang; Kang Li; Min Yue; Le Zhang (2023). DataSheet1_An integrated platform for Brucella with knowledge graph technology: From genomic analysis to epidemiological projection.docx [Dataset]. http://doi.org/10.3389/fgene.2022.981633.s001
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    binAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Fubo Ma; Ming Xiao; Lin Zhu; Wen Jiang; Jizhe Jiang; Peng-Fei Zhang; Kang Li; Min Yue; Le Zhang
    License

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

    Description

    Motivation:Brucella, the causative agent of brucellosis, is a global zoonotic pathogen that threatens both veterinary and human health. The main sources of brucellosis are farm animals. Importantly, the bacteria can be used for biological warfare purposes, requiring source tracking and routine surveillance in an integrated manner. Additionally, brucellosis is classified among group B infectious diseases in China and has been reported in 31 Chinese provinces to varying degrees in urban areas. From a national biosecurity perspective, research on brucellosis surveillance has garnered considerable attention and requires an integrated platform to provide researchers with easy access to genomic analysis and provide policymakers with an improved understanding of both reported patients and detected cases for the purpose of precision public health interventions.Results: For the first time in China, we have developed a comprehensive information platform for Brucella based on dynamic visualization of the incidence (reported patients) and prevalence (detected cases) of brucellosis in mainland China. Especially, our study establishes a knowledge graph for the literature sources of Brucella data so that it can be expanded, queried, and analyzed. When similar “epidemiological comprehensive platforms” are established in the distant future, we can use knowledge graph to share its information. Additionally, we propose a software package for genomic sequence analysis. This platform provides a specialized, dynamic, and visual point-and-click interface for studying brucellosis in mainland China and improving the exploration of Brucella in the fields of bioinformatics and disease prevention for both human and veterinary medicine.

  8. Epidemiological data used in the model#

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Douglas S. Goodin (2023). Epidemiological data used in the model# [Dataset]. http://doi.org/10.1371/journal.pone.0034034.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Douglas S. Goodin
    License

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

    Description

    HLA+  =  carrier of ≥ 1 copy of the DRB1*1501 allele*From Canadian Data [21], based on a prevalence of 150 per 105 population and split into men and women according to [15]. Concordance rates presented as “proband-wise” rates [30].†Data unavailable on the 2 male patients [21]. The worst case is: 9/11  =  0.82**See: Prop. (1.4) of Appendix S1 (Section C)##Canadian HLA data: D Sadovnick (personal communication). Based on ∼ 3,000 cases and ∼ 400 Controls (% women not available). Control rates confirmed in a much larger transplant database.††UCSF Databases: J Oksenberg (personal communication) UCSF #1 (GeneMSA) - 485 cases (68% women) and 431 Controls (66% women) UCSF #2 (IMSGC) - 779 cases (76% women)

  9. CDC WONDER API for Data Query Web Service

    • data.virginia.gov
    • healthdata.gov
    • +4more
    api
    Updated Jul 26, 2023
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    Centers for Disease Control and Prevention, Department of Health & Human Services (2023). CDC WONDER API for Data Query Web Service [Dataset]. https://data.virginia.gov/dataset/cdc-wonder-api-for-data-query-web-service
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    apiAvailable download formats
    Dataset updated
    Jul 26, 2023
    Description

    WONDER online databases include county-level Compressed Mortality (death certificates) since 1979; county-level Multiple Cause of Death (death certificates) since 1999; county-level Natality (birth certificates) since 1995; county-level Linked Birth / Death records (linked birth-death certificates) since 1995; state & large metro-level United States Cancer Statistics mortality (death certificates) since 1999; state & large metro-level United States Cancer Statistics incidence (cancer registry cases) since 1999; state and metro-level Online Tuberculosis Information System (TB case reports) since 1993; state-level Sexually Transmitted Disease Morbidity (case reports) since 1984; state-level Vaccine Adverse Event Reporting system (adverse reaction case reports) since 1990; county-level population estimates since 1970. The WONDER web server also hosts the Data2010 system with state-level data for compliance with Healthy People 2010 goals since 1998; the National Notifiable Disease Surveillance System weekly provisional case reports since 1996; the 122 Cities Mortality Reporting System weekly death reports since 1996; the Prevention Guidelines database (book in electronic format) published 1998; the Scientific Data Archives (public use data sets and documentation); and links to other online data sources on the "Topics" page.

  10. m

    Databases of a clinico-ecological study of a triple epidemic

    • data.mendeley.com
    • narcis.nl
    Updated Mar 8, 2018
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    Sergian Vianna Cardozo (2018). Databases of a clinico-ecological study of a triple epidemic [Dataset]. http://doi.org/10.17632/2drcj8mtbc.1
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    Dataset updated
    Mar 8, 2018
    Authors
    Sergian Vianna Cardozo
    License

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

    Description

    In these worksheets are exposed the tabulated raw data referring to the article "A clinico-ecological study of a triple epidemic: Zika, Dengue and Chikungunya"

  11. f

    Data from: Epidemiology of inflammatory bowel disease in Mexico and...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Jan 27, 2020
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    Bardach, Ariel; Scarpellini, Bruno; Ciapponi, Agustín; Virgilio, Sacha Alexis; Gamba, Johana; Perdomo, Ana María Bravo; Martinez, Briseida Rubio; Soto, Natalie Claire; Salazar, Carlos Arturo González; Rodríguez, José Nicolás Rocha; Aldunate, Leandro; Illanes, Moisés Freddy Rojas; Berrueta, Mabel; De Paula, Juan; Machnicki, Gerardo; Ciganda, Álvaro (2020). Epidemiology of inflammatory bowel disease in Mexico and Colombia: Analysis of health databases, mathematical modelling and a case-series study [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000526934
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    Dataset updated
    Jan 27, 2020
    Authors
    Bardach, Ariel; Scarpellini, Bruno; Ciapponi, Agustín; Virgilio, Sacha Alexis; Gamba, Johana; Perdomo, Ana María Bravo; Martinez, Briseida Rubio; Soto, Natalie Claire; Salazar, Carlos Arturo González; Rodríguez, José Nicolás Rocha; Aldunate, Leandro; Illanes, Moisés Freddy Rojas; Berrueta, Mabel; De Paula, Juan; Machnicki, Gerardo; Ciganda, Álvaro
    Area covered
    Colombia, Mexico
    Description

    Background and aimsUlcerative Colitis (UC) and Crohn's Disease (CD) have a major impact on quality of life and medical costs. The aim of the study was to estimate the prevalence, incidence and clinical phenotypes of Inflammatory Bowel Disease (IBD) cases in Mexico and Colombia.MethodsWe analyzed official administrative and health databases, used mathematical modelling to estimate the incidence and complete prevalence, and performed a case-series of IBD patients at a referral center both in Mexico and Colombia.ResultsThe age-adjusted complete prevalence of UC per 100,000 inhabitants for 2015/2016 ranged from 15.65 to 71.19 in Mexico and from 27.40 to 69.97 in Colombia depending on the model considered. The prevalence of CD per 100,000 inhabitants in Mexico ranged from 15.45 to 18.08 and from 16.75 to 18.43 in Colombia.In Mexico, the age-adjusted incidence of UC per 100,000 inhabitants per year ranged from 0.90 to 2.30, and from 0.55 to 2.33 in Colombia. The incidence for CD in Mexico ranged from 0.35 to 0.66 whereas in Colombia, the age-adjusted incidence of CD ranged from 0.30 to 0.57.The case-series included 200 IBD patients from Mexico and 204 patients from Colombia. The UC/CD prevalence ratio in Mexico and Colombia was 1.50:1 and 4.5:1 respectively. In Mexico, the female/male prevalence ratio for UC was 1.50:1 and 1.28:1 for CD, while in Colombia this ratio was 0.68:1 for UC and 0.8:1 for CD. In Mexico the relapse rate for UC was 63.3% and 72.5% for CD, while those rates in Colombia were 58.2% for UC and 58.3% for CD.ConclusionsThe estimated burden of disease of IBD in Mexico and Colombia is not negligible. Although these findings need to be confirmed by population-based studies, they are useful for decision-makers, practitioners and patients with this condition.

  12. Database of infection control and surveillance program, 2011-2018

    • zenodo.org
    csv
    Updated Oct 25, 2021
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    Olga N. Ershova; Nataliya V. Kurdyumova; Ivan A. Savin; Gleb V. Danilov; Michael A. Shifrin; Ksenia I. Ershova; Ksenia I. Ershova; Oleg A. Khomenko; Ekaterina A. Sokolova; Olga N. Ershova; Nataliya V. Kurdyumova; Ivan A. Savin; Gleb V. Danilov; Michael A. Shifrin; Oleg A. Khomenko; Ekaterina A. Sokolova (2021). Database of infection control and surveillance program, 2011-2018 [Dataset]. http://doi.org/10.5281/zenodo.3995319
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    csvAvailable download formats
    Dataset updated
    Oct 25, 2021
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Olga N. Ershova; Nataliya V. Kurdyumova; Ivan A. Savin; Gleb V. Danilov; Michael A. Shifrin; Ksenia I. Ershova; Ksenia I. Ershova; Oleg A. Khomenko; Ekaterina A. Sokolova; Olga N. Ershova; Nataliya V. Kurdyumova; Ivan A. Savin; Gleb V. Danilov; Michael A. Shifrin; Oleg A. Khomenko; Ekaterina A. Sokolova
    License

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

    Description

    A full anonymized data set collected as a part of ICU infection control and surveillance program; 01/01/2011-01/01-2018

    Files "VAE_Data_Main_0821_1338.csv" contains daily data (one row is one day) on infection surveillance ordered by date.

    Files "Data_Dictionary_MainDB.csv" contains the description of all variables from the main data set.

  13. H

    SEER Cancer Statistics Database

    • data.niaid.nih.gov
    • dataverse.harvard.edu
    Updated Jul 11, 2011
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    (2011). SEER Cancer Statistics Database [Dataset]. http://doi.org/10.7910/DVN/C9KBBC
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    Dataset updated
    Jul 11, 2011
    License

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

    Description

    Users can access data about cancer statistics in the United States including but not limited to searches by type of cancer and race, sex, ethnicity, age at diagnosis, and age at death. Background Surveillance Epidemiology and End Results (SEER) database’s mission is to provide information on cancer statistics to help reduce the burden of disease in the U.S. population. The SEER database is a project to the National Cancer Institute. The SEER database collects information on incidence, prevalence, and survival from specific geographic areas representing 28 percent of the United States population. User functionality Users can access a variety of reso urces. Cancer Stat Fact Sheets allow users to look at summaries of statistics by major cancer type. Cancer Statistic Reviews are available from 1975-2008 in table format. Users are also able to build their own tables and graphs using Fast Stats. The Cancer Query system provides more flexibility and a larger set of cancer statistics than F ast Stats but requires more input from the user. State Cancer Profiles include dynamic maps and graphs enabling the investigation of cancer trends at the county, state, and national levels. SEER research data files and SEER*Stat software are available to download through your Internet connection (SEER*Stat’s client-server mode) or via discs shipped directly to you. A signed data agreement form is required to access the SEER data Data Notes Data is available in different formats depending on which type of data is accessed. Some data is available in table, PDF, and html formats. Detailed information about the data is available under “Data Documentation and Variable Recodes”.

  14. r

    Alcohol and Alcohol Problems Science Database

    • rrid.site
    • scicrunch.org
    • +1more
    Updated Jan 29, 2022
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    (2022). Alcohol and Alcohol Problems Science Database [Dataset]. http://identifiers.org/RRID:SCR_003768
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    Dataset updated
    Jan 29, 2022
    Description

    Portal to support researchers and practitioners searching for information related to alcohol research including links to a number of databases, journals, and Web sites focused on alcohol research and related topics. Also included is a link to the archived ETOH database, the premier Alcohol and Alcohol Problems Science Database, which contains over 130,000 records and covers the period from 1972 through 2003. Included in ETOH are abstracts and bibliographic references to journal articles, books, dissertation abstracts, conference papers and proceedings, reports and studies, and chapters in edited works. ETOH's scope reflects the multidisciplinary nature of the alcohol research field. The range of subject areas contained in ETOH includes: medicine, biochemistry, psychology, psychiatry, epidemiology, sociology, anthropology, treatment, prevention, education, accidents and safety, legislation, criminal justice, public policy, and health services research. The ETOH database is indexed with vocabulary from the Alcohol and Other Drug Thesaurus: A Guide to Concepts and Terminology in Substance Abuse and Addiction (AOD Thesaurus), Third Edition. More than 5,000 terms in the AOD Thesaurus are used as ETOH descriptors. The Databases/Resources section includes databases and resources for alcohol researchers and practitioners. It includes an introduction to the National Library of Medicine's PubMed and some sample searches on alcohol to run in the PubMed database; descriptions of and links to the various databases of the National Clearinghouse for Alcohol and Drug Information (NCADI); a selection of alcohol and other drug databases with their descriptions and links; links to peer-reviewed journals most often used by alcohol researchers; and links to a selection of Web sites pertinent to the substance abuse field.

  15. u

    PATRON Primary Care Research Data Repository

    • figshare.unimelb.edu.au
    pdf
    Updated May 30, 2023
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    DOUGLAS BOYLE; LENA SANCI; Jon Emery; JANE GUNN; JANE HOCKING; JO-ANNE MANSKI-NANKERVIS; RACHEL CANAWAY (2023). PATRON Primary Care Research Data Repository [Dataset]. http://doi.org/10.26188/5c52934b4aeb0
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    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    The University of Melbourne
    Authors
    DOUGLAS BOYLE; LENA SANCI; Jon Emery; JANE GUNN; JANE HOCKING; JO-ANNE MANSKI-NANKERVIS; RACHEL CANAWAY
    License

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

    Description

    PATRON is a human ethics approved program of research incorporating an enduring de-identified repository of Primary Care data facilitating research and knowledge generation. PATRON is a part of the 'Data for Decisions' initiative of the Department of General Practice, University of Melbourne. 'Data for Decisions' is a research initiative in partnership with general practices. It is an exciting undertaking that makes possible primary care research projects to increase knowledge and improve healthcare practices and policy. Principal Researcher: Jon EmeryData Custodian: Lena SanciData Steward: Douglas BoyleManager: Rachel CanawayMore information about Data for Decisions and utilising PATRON data is available from the Data for Decisions website.

  16. n

    Human Life-Table Database

    • neuinfo.org
    • dknet.org
    • +2more
    Updated Oct 11, 2024
    + more versions
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    (2024). Human Life-Table Database [Dataset]. http://identifiers.org/RRID:SCR_006248
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    Dataset updated
    Oct 11, 2024
    Description

    A collection of population life tables covering a multitude of countries and many years. Most of the HLD life tables are life tables for national populations, which have been officially published by national statistical offices. Some of the HLD life tables refer to certain regional or ethnic sub-populations within countries. Parts of the HLD life tables are non-official life tables produced by researchers. Life tables describe the extent to which a generation of people (i.e. life table cohort) dies off with age. Life tables are the most ancient and important tool in demography. They are widely used for descriptive and analytical purposes in demography, public health, epidemiology, population geography, biology and many other branches of science. HLD includes the following types of data: * complete life tables in text format; * abridged life tables in text format; * references to statistical publications and other data sources; * scanned copies of the original life tables as they were published. Three scientific institutions are jointly developing the HLD: the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany, the Department of Demography at the University of California at Berkeley, USA and the Institut national d''��tudes d��mographiques (INED) in Paris, France. The MPIDR is responsible for maintaining the database.

  17. d

    Data from: An open-access database of infectious disease transmission trees...

    • datadryad.org
    zip
    Updated Jun 10, 2022
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    Juliana C. Taube; Paige B. Miller; John M. Drake (2022). An open-access database of infectious disease transmission trees to explore superspreader epidemiology [Dataset]. http://doi.org/10.5061/dryad.nk98sf7w7
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    zipAvailable download formats
    Dataset updated
    Jun 10, 2022
    Dataset provided by
    Dryad
    Authors
    Juliana C. Taube; Paige B. Miller; John M. Drake
    Time period covered
    May 16, 2022
    Description

    The code using these data to reproduce the figures in Taube et al. "An open-access database of infectious disease transmission trees enables exploration of superspreader epidemiology" can be found on Github at https://github.com/DrakeLab/taube-transmission-trees. OutbreakTrees, the database of transmission trees underlying these data, can be found at https://outbreaktrees.ecology.uga.edu/.

  18. f

    Risk factors associated with toxoplasmosis.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jul 1, 2024
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    Ki Hyun Lee; Awachana Jiamsakul; Sasisopin Kiertiburanakul; Rohidas Borse; Vohith Khol; Evy Yunihastuti; Iskandar Azwa; I. Ketut Agus Somia; Romanee Chaiwarith; Thach Ngoc Pham; Suwimon Khusuwan; Cuong Duy Do; Nagalingeswaran Kumarasamy; Yasmin Gani; Rossana Ditangco; Oon Tek Ng; Sanjay Pujari; Man Po Lee; Anchalee Avihingsanon; Hsin-Pai Chen; Fujie Zhang; Junko Tanuma; Jeremy Ross; Jun Yong Choi (2024). Risk factors associated with toxoplasmosis. [Dataset]. http://doi.org/10.1371/journal.pone.0306245.t002
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    xlsAvailable download formats
    Dataset updated
    Jul 1, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Ki Hyun Lee; Awachana Jiamsakul; Sasisopin Kiertiburanakul; Rohidas Borse; Vohith Khol; Evy Yunihastuti; Iskandar Azwa; I. Ketut Agus Somia; Romanee Chaiwarith; Thach Ngoc Pham; Suwimon Khusuwan; Cuong Duy Do; Nagalingeswaran Kumarasamy; Yasmin Gani; Rossana Ditangco; Oon Tek Ng; Sanjay Pujari; Man Po Lee; Anchalee Avihingsanon; Hsin-Pai Chen; Fujie Zhang; Junko Tanuma; Jeremy Ross; Jun Yong Choi
    License

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

    Description

    IntroductionToxoplasma gondii can cause symptomatic toxoplasmosis in immunodeficient hosts, including in people living with human immunodeficiency virus (PLWH), mainly because of the reactivation of latent infection. We assessed the prevalence of toxoplasmosis and its associated risk factors in PLWH in the Asia-Pacific region using data from the TREAT Asia Human Immunodeficiency Virus (HIV) Observational Database (TAHOD) of the International Epidemiology Databases to Evaluate AIDS (IeDEA) Asia-Pacific.MethodsThis study included both retrospective and prospective cases of toxoplasmosis reported between 1997 and 2020. A matched case-control method was employed, where PLWH diagnosed with toxoplasmosis (cases) were each matched to two PLWH without a toxoplasmosis diagnosis (controls) from the same site. Sites without toxoplasmosis were excluded. Risk factors for toxoplasmosis were analyzed using conditional logistic regression.ResultsA total of 269/9576 (2.8%) PLWH were diagnosed with toxoplasmosis in 19 TAHOD sites. Of these, 227 (84%) were reported retrospectively and 42 (16%) were prospective diagnoses after cohort enrollment. At the time of toxoplasmosis diagnosis, the median age was 33 years (interquartile range 28–38), and 80% participants were male, 75% were not on antiretroviral therapy (ART). Excluding 63 out of 269 people without CD4 values, 192 (93.2%) had CD4 ≤200 cells/μL and 162 (78.6%) had CD4 ≤100 cells/μL. By employing 538 matched controls, we found that factors associated with toxoplasmosis included abstaining from ART (odds ratio [OR] 3.62, 95% CI 1.81–7.24), in comparison to receiving nucleoside reverse transcriptase inhibitors plus non-nucleoside reverse transcriptase inhibitors, HIV exposure through injection drug use (OR 2.27, 95% CI 1.15–4.47) as opposed to engaging in heterosexual intercourse and testing positive for hepatitis B virus surface antigen (OR 3.19, 95% CI 1.41–7.21). Toxoplasmosis was less likely with increasing CD4 counts (51–100 cells/μL: OR 0.41, 95% CI 0.18–0.96; 101–200 cells/μL: OR 0.14, 95% CI 0.06–0.34; >200 cells/μL: OR 0.02, 95% CI 0.01–0.06), when compared to CD4 ≤50 cells/μL. Moreover, the use of prophylactic cotrimoxazole was not associated with toxoplasmosis.ConclusionsSymptomatic toxoplasmosis is rare but still occurs in PLWH in the Asia-Pacific region, especially in the context of delayed diagnosis, causing advanced HIV disease. Immune reconstitution through early diagnosis and ART administration remains a priority in Asian PLWH.

  19. NCI State Late Stage Breast Cancer Incidence Rates

    • hub.arcgis.com
    Updated Jan 21, 2020
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    National Cancer Institute (2020). NCI State Late Stage Breast Cancer Incidence Rates [Dataset]. https://hub.arcgis.com/datasets/NCI::nci-state-late-stage-breast-cancer-incidence-rates/geoservice
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    Dataset updated
    Jan 21, 2020
    Dataset authored and provided by
    National Cancer Institutehttp://www.cancer.gov/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

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    Description

    This dataset contains Cancer Incidence data for Breast Cancer (Late Stage^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2016 to 2020.Data are for females segmented by age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ Late Stage is defined as cases determined to be regional or distant. Due to changes in stage coding, Combined Summary Stage (2004+) is used for data from Surveillance, Epidemiology, and End Results (SEER) databases and Merged Summary Stage is used for data from National Program of Cancer Registries databases. Due to the increased complexity with staging, other staging variables maybe used if necessary.Data Source Field Key(1) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(5) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(6) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2022 submission).(7) Source: SEER November 2022 submission.(8) Source: Incidence data provided by the SEER Program. AAPCs are calculated by the Joinpoint Regression Program and are based on APCs. Data are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84,85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with SEER November 2022 data.Some data are not available, see Data Not Available for combinations of geography, cancer site, age, and race/ethnicity.Data for the United States does not include data from Nevada.Data for the United States does not include Puerto Rico.

  20. f

    Output from the Staramr tool with study E. coli genome contigs scanned...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Nov 16, 2023
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    Weissman, Scott J.; Roberts, Marilyn C.; Rabinowitz, Peter M.; Tseng, Ashley S. (2023). Output from the Staramr tool with study E. coli genome contigs scanned against the Center for Genomic Epidemiology’s ResFinder, PointFinder, and PlasmidFinder databases using the default 90% identity match and 60% minimum length coverage of the target gene thresholds, and 100% minimum total length coverage. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001080484
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    Dataset updated
    Nov 16, 2023
    Authors
    Weissman, Scott J.; Roberts, Marilyn C.; Rabinowitz, Peter M.; Tseng, Ashley S.
    Description

    Output from the Staramr tool with study E. coli genome contigs scanned against the Center for Genomic Epidemiology’s ResFinder, PointFinder, and PlasmidFinder databases using the default 90% identity match and 60% minimum length coverage of the target gene thresholds, and 100% minimum total length coverage.

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Centers for Disease Control and Prevention (2025). Electronic Health Information Legal Epidemiology Data Set 2014 [Dataset]. https://catalog.data.gov/dataset/electronic-health-information-legal-epidemiology-data-set-2014
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Electronic Health Information Legal Epidemiology Data Set 2014

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Dataset updated
Jul 11, 2025
Dataset provided by
Centers for Disease Control and Preventionhttp://www.cdc.gov/
Description

Authors: Cason Schmit, JD, Gregory Sunshine, JD, Dawn Pepin, JD, MPH, Tara Ramanathan, JD, MPH, Akshara Menon, JD, MPH, Matthew Penn, JD, MLIS This legal data set consists of state statutes and regulations in effect as of January 1, 2014, related to electronic health information (EHI). Jurisdictions were limited to US states, territories, and the District of Columbia that had statutes and regulations in the Westlaw legal database that expressly referenced EHI. This data set includes 2,364 EHI-related laws representing 49 EHI uses in 54 jurisdictions. For information about research methods, please reference the Electronic Health Information Legal Epidemiology Protocol 2014.

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