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Disease surveillance, vaccination data, epidemiology, health system capacity, mortality statistics
2,871 datasets
Historical data tracks COVID-19 cases, tests, and deaths for Chicago residents by home ZIP code. Cases are counted based on the week the test specimen was collected, and test counts include multiple tests per person. Data originates from the Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, and other public health sources.
A 1968 journal article analyzing the impact of the influenza epidemic on the U.S. Army during World War I. The work is a historical analysis published in the Journal of American History. The source material likely includes military records and historical accounts from the 1914-1918 period.
World Health Organization data on the existence of national HPV vaccination programmes. The dataset likely contains binary or categorical indicators for country-level programme status. It is published by the WHO via the Global Health Observatory platform.
Regional prevalence and alcohol-attributable Disability-Adjusted Life Years (DALYs) data, likely expressed as a percentage of total burden. The dataset originates from the World Health Organization's Global Health Observatory (WHO GHO) platform. The specific time period, geographic coverage, and number of data points are not provided in the available metadata.
WHO data tracks the existence of national targets for reducing mortality from non-communicable diseases (NCDs). This dataset likely contains country-level indicators on policy commitments, potentially sourced from the WHO Global Health Observatory. The specific metrics, time coverage, and number of records are unknown from the provided metadata.
Stigma Monkeypox versus COVID-19 is a dataset hosted on Kaggle. Its title suggests it contains data comparing social stigma or public attitudes associated with the Monkeypox and COVID-19 diseases. The dataset's author, organization, size, and specific contents are unknown.
Our World in Data provides this dataset to support the fight against COVID-19. The description indicates it is intended to mobilize researchers to apply natural language processing for new insights. The original data source is acknowledged as ourworldindata.
Weekly cumulative influenza vaccination coverage estimates for children aged 6 months through 17 years, based on the National Immunization Survey-Flu. The data is collected annually via a national random-digit-dialed cellular telephone survey conducted during the flu season from October to June. Coverage estimates are derived from parental reports.
Weekly cumulative influenza vaccination coverage estimates for adults aged 18 and older in the United States, produced by the CDC. The data is sourced from the National Immunization Survey-Adult COVID Module (NIS-ACM), which began in April 2021. It provides weekly estimates for monitoring vaccination uptake and trends.
Weekly cumulative influenza vaccination coverage estimates for children aged 6 months through 17 years in the United States, comparing the current and previous flu seasons. The data is derived from the National Immunization Survey-Flu (NIS-Flu), a national random-digit-dialed cellular telephone survey conducted annually from October to June. Coverage estimates are based on parental reports.
Weekly cumulative influenza vaccination coverage estimates for children aged 6 months through 17 years in the United States. The data is produced by the CDC's National Immunization Survey-Flu, a national random-digit-dialed cellular telephone survey conducted during the flu season (October-June). It provides a comparison between the current and previous flu seasons.
Layers in this service include Birth, Cancer, Hospitalization Discharge, Mortality, and STI Rates, as well as Demographics. The dataset is provided by Lake County, Illinois, and was last updated in March 2026. Specific row and column counts are not provided.
Animated visualizations of the COVID-19 pandemic in the United States combine case and death rates by state into a single format to depict their temporal relationship. The work by Christian Testa of Harvard University Press uses per capita state-level data from January 22, 2020 to July 8, 2020 to make the lag between cases and subsequent deaths more apparent.
Philippine morbidity and mortality rates were the world's highest during the period 1883-1903. Ken De Bevoise's historical analysis explores the conjunction of demographic, economic, technological, cultural, and political processes that led to this outcome. The work uses archival records interpreted with concepts from health sciences to examine human interaction with their total environment.
ACDC dataset is a collection of medical imaging data hosted on Kaggle. The dataset likely contains cardiac MRI scans and associated clinical annotations. Its specific content, size, and creation details require verification after download.
Featuring data from a cluster-randomized experiment involving 60,000 households in rural India, testing decentralized clean water treatment and home delivery. It measures household take-up, willingness-to-pay, willingness-to-accept, and self-reported health outcomes under varying price regimes.
Comprising data from a cluster-randomized experiment involving 60,000 households in rural India, testing decentralized clean water treatment and home delivery. It measures household take-up, willingness-to-pay, willingness-to-accept, and self-reported health outcomes under varying price regimes.
This dataset supports a study analyzing the impact of the 1909 public pension introduction on elderly mortality in England and Wales. The research uses a quasi-natural experiment with difference-in-differences and event-time designs to estimate mortality decline. The analysis links the decline to factors like residential crowding and retirement from high-mortality occupations.
This dataset supports a study on the impact of the 1909 public pension introduction in the UK on elderly mortality in England and Wales. The analysis uses difference-in-differences and event-time designs, finding a decline in mortality linked to pensioner density and disease types.
This dataset supports an investigation into the demographic effects of forced labor under the Cultivation System in nineteenth-century Java. It is used for panel analyses linking labor demands to mortality rates, with an instrumental variable approach using international market prices for coffee and sugar. The analysis suggests the system's abolition prevented a 10-30% increase in average overall mortality by the late 1870s.