CPSC's epidemiological data include reports of incidents involving death, injury, or potential injury that are associated with consumer products. The online Clearinghouse posts summary information from death certificates (DTHS), medical examiner reports (MECAP reports), reports published on Saferproducts.gov, Newsclips, and other submissions from consumers, healthcare professionals, state, federal, and local agencies (IPII), and public safety entities.

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)

Data and code repository for the Open COVID-19 Data Working Group: a global and multi-organizational initative that aims to enable rapid sharing of trusted and open public health data to advance the response to infectious diseases.

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

RS: Retrospective study.

A full anonymized data set was collected as a part of the ICU infection control and surveillance program; 01/01/2011-12/31/2020

File "Zenodo_DB_v4.csv" contains daily data (one row is one day) on infection surveillance ordered by date.

File "Data_Dictionary_MainDB_2021.csv" contains the description of all variables from the data set.

This dataset contains key characteristics about the data described in the Data Descriptor Epidemiological data from the COVID-19 outbreak, real-time case information. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

Context

The dataset contains data of documented COVID-19 cases, partially complemented by additional Web data. The date are originally pulished at https://tinyurl.com/s6gsq5y and are updated regularly. This dataset is a snapshot downloaded on March 3, 2020.

Content

Xu et al. (2020) have built a centralised repository of individual-level information on patients with laboratory-confirmed COVID-19 (in China, confirmed by detection of virus nucleic acid at the City and Provincial Centers for Disease Control and Prevention), including their travel history, location (highest resolution available and corresponding latitude and longitude), symptoms, and reported onset dates, as well as confirmation dates and basic demographics. Information is collated from a variety of sources, including official reports from WHO, Ministries of Health, and Chinese local, provincial, and national health authorities. If additional data are available from reliable online reports, they are included.

Acknowledgements

The authors decidedly declare no competing interests. Their work was funded by the Oxford Martin School.

Reference

Xu, Bo; Kraemer, Moritz U. G.; Gutierrez, Bernardo; Mekaru, Sumiko; Sewalk, Kara; Loskill, Alyssa et al. (2020): Open access epidemiological data from the COVID-19 outbreak. In: The Lancet Infectious Diseases. DOI: 10.1016/S1473-3099(20)30119-5.

The database compiles aggregated time series data from the National Center for Epidemiology, Disease Prevention, and Control (CDC) of Peru. This comprehensive national data, collected annually, originates from the National Epidemiological Surveillance Network and the system's reporting channels. Time series have been constructed in parallel, covering the period from 1983 to 2023.

IQR = interquartile range; SCC = Swiss Concussion Center.

An ongoing outbreak of the viral disease monkeypox was confirmed in May 2022, beginning with a cluster of cases found in the United Kingdom. The first confirmed case was traced to an individual with travel links to Nigeria and was detected on 6 May 2022. During the early stages of outbreaks, obtaining reliable, synthesised data on the characteristics of cases is a challenge, especially at a global scale.

Here we present a subset of data from Ginkgo Biosecurity's Human Epidemic Database (HED), which consists of outbreak data collected from official, open-source surveillance reports. This provided dataset includes 1,044 epidemic events with onset between 2015 and 2020, covering more 230 countries and territories and 120 pathogens.

The methodology to collate these data have been described in a manuscript submitted for publication, ‘Constructing a global human epidemic database using open-source digital biosurveillance’.

Datasets included: - HED_data repository.csv - Event-level data repository with epidemics starting in 2015 to 2020. - HED_pathogens_supplement.csv - A list of pathogens and their associated grouping within our epidemic event scoring framework. This pathogen/grouping list is not comprehensive but rather a sampling of the pathogens scored. - HED_metadata.csv - Meta data describing columns in ‘HED_complete data repository.csv’

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.

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).

Abstract

TIER.net http://tier.net/ is an electronic patient management system that is used for monitoring and evaluation of HIV care and treatment programmes in government health facilities throughout South Africa. The system was designed as part of a 3-tier approach to implementing a full electronic medical records (EMR) system. This approach provides a flexible solution that allows facilities to transition towards EMR in stages, as their infrastructure improves, and resources become available. TIER.net http://tier.net/ forms the second tier, whereby patient's paper clinical records are entered into a non-networked computer at the health facility and transferred periodically to a central database.

The TIER.net http://tier.net/ database contains information on clinic visit attendance, laboratory results and ART dispensing records for all patients on ART. The system was implemented in uMkhanyakude district in 2013; patient records from all visits before 2013 were back captured into the system. AHRI has a memorandum of agreement with the Department of Health to receive the TIER.net http://tier.net/ data for the 17 clinics in the Hlabisa health sub-district and Hlabisa hospital. A dedicated data entry clerk based in each clinic enters information from patients' paper clinical records into the TIER.net http://tier.net/ system after each patient visit. Laboratory results are manually entered into TIER.net http://tier.net/ after they have been received by the clinic (i.e. are not imported electronically from the National Health Laboratory Service (NHLS) system). Currently, pre-ART visits are not recorded in TIER.net http://tier.net/, although modules to capture HIV testing and pre-ART care may be implemented in the future.

Geographic coverage

Hlabisa sub-district, KwaZulu-Natal, South Africa

Analysis unit

Individuals on ART at one of the 17 clinics from Hlabisa sub-district, uMkhanyakude district

Universe

Individuals from Hlabisa sub-district, KwaZulu-Natal, South Africa

Kind of data

Clinical Data

Sampling procedure

All individuals accessing ART treatment and care in the 17 clinics in Hlabisa sub-district, KwaZulu-Natal, South Africa

Cleaning operations

Tier.Net data is processed and stored on servers under the physical control of AHRI until datasets are made available on the data repository. The data is de-identified and can then be downloaded for processing on the data user's computer.

Data is stored on industry-standard relational databases with data integrity and user authentication for access control. Data is replicated on at least a daily basis to the Durban site of the Institution to provide secure offsite storage of data. Transactional logs are backed up every 30 minutes to enable recovery of data in the event of equipment failure.

All users of the system are authenticated through individual passwords with minimum complexity and regular change rules (passwords must be at least eight digits, with a mix of small and capital letters, at least one numeric or non-alphabetic digit and changed at least every 45 days). AHRI uses industry standard malware and intrusion detection with at least annual penetration tests by a reputable outside security audit company.

A collection of data of an epidemiological study of chronic disease in the oldest old based on information collected from Kaiser Permanente facilities in Northern California (KPNC). The initial sample was drawn from the Kaiser''s active membership lists for the years 1971 and 1980. The sample was restricted to members that had a Multiphasic Health Checkup examination (MHC) within 7 years of the baseline date. The sample was stratified to attain equal numbers of observations (1,000 in each) in three sex-age cells for each cohort: 65-69, 70-79, and 80+. Each cohort was followed for 9 years through existing medical records and computerized hospitalization tapes. Mortality data was collected by matching the sampled data with state Vital Statistics data for an additional 3 years for a total follow-up time of 12 years. Part 1 of the data collections consists of Master Records, which includes information from the morbidity review, in which over 35 chronic conditions or diagnoses were abstracted from the member charts, as well as detailed diagnostic criteria for the major conditions. A prevalence review was done, which included the 4 years prior to the baseline date for these same conditions. Recurrent disease is included for the following conditions: cancers, myocardial infarction, and various forms of strokes. A detailed account of outpatient health services use, and data from the multiphasic health checkup, which was administered to each participant during the nine yearly follow-ups, are also included in the Master Records file. The labs and procedures included: chemistry, hematology, urinalysis, bacteriology, chest x-ray, GI x-ray, ultrasound, CT/MRI, mammogram, resting ECG, treadmill ECG, echocardiograms, nuclear scans, outpatient breast biopsy, cystoscopy, and cataract surgery. Inpatient utilization includes all hospitalizations, procedures done during a hospital stay, length of stay, admitting/discharge diagnosis. Part 2, Hospitalization, contains records of causes and dates of hospitalizations and discharges and nursing home admissions. There is also a section on incomplete reviews and the reasons for them. Demographic information and some lifestyle information from the multiphasic health checkup (e.g., smoking, alcohol, and Body Mass Index) are also in this file. Data Availability: These datasets have been documented extensively and are available from the ICPSR (Study No. 4219). * Dates of Study: 1971-1992 * Study Features: Longitudinal, Anthropometric Measures * Sample Size: ** 1971 cohort: 2,877 (baseline) ** 1980 cohort: 3,113 (baseline) ** 1971 & 1980: 5,990 ** Hospitalization: 14,730 Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/04219 * HSRR: http://wwwcf.nlm.nih.gov/hsrr_search/view_hsrr_record_table.cfm?TITLE_ID=381&PROGRAM_CAME=toc_with_source2.cfm

Github repository with 2019 Novel Coronavirus line listings reported inside and outside Hubei province. Data are entered by a group of volunteers and de-duplication occurs based on a statistical algorithm that checks the probability of a case being a duplicate. Data are collected and curated individual-level data from national, provincial, and municipal health reports, as well as additional information from online reports. All data are geo-coded and, include symptoms, key dates (date of onset, admission, and confirmation), and travel history, if available. The repository is daily updated, usually by 10pm PT (1am EST, 6am GMT) .

COVID-19 integrated surveillance data provided by the Italian Institute of Health and processed via UnrollingAverages.jl to deconvolve the weekly moving averages.

The 2017 nucleic acid and amino acid sequence data for enteroviruses and influenza viruses, as well as corresponding epidemiological data. It can be presented by the counties and cities within the country. The sequence data can facilitate further research by domestic and external researchers.