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Disease surveillance, vaccination data, epidemiology, health system capacity, mortality statistics
2,861 datasets
Weekly provisional counts of deaths involving COVID-19, pneumonia, and influenza are reported to the National Center for Health Statistics (NCHS) by state and week ending date. The dataset includes columns for total deaths, cause-specific deaths, and MMWR week. It is updated weekly by the NCHS, with the most recent platform update noted as March 2026.
Weekly cumulative estimates of COVID-19 vaccine doses administered to adults aged 18 and older in U.S. retail pharmacies and physician medical offices, segmented by age group and season. The data is sourced from IQVIA's Longitudinal Prescription Claims and Medical Claims, provided by data.cdc.gov, and was last updated in March 2026. It covers multiple COVID-19 vaccination seasons, with the 2023-24 season starting in mid-September 2023.
CDC data.cdc.gov provides weekly cumulative estimates of influenza vaccinations administered to adults in retail pharmacies and physicians' medical offices. Estimates are derived from IQVIA prescription claims and medical claims data. The dataset covers multiple influenza seasons and is updated weekly.
Seleman Said's dataset on figshare examines barriers to Hepatitis B vaccination and public knowledge of recommended doses. The dataset is 5.5 KB in size and was last updated on April 27, 2026. It is available under a CC-BY-4.0 license in an XLS (Excel) format.
Ying Yang's dataset on figshare, last updated April 27, 2026, analyzes the association between baseline red cell distribution width (RDW) tertiles and RDW trajectories with 30-day all-cause mortality. The dataset is 5.5 KB in size and is available in XLS format under a CC-BY-4.0 license.
Survey data tracks U.S. adult uptake and confidence for the updated COVID-19, seasonal influenza, and RSV vaccines. The dataset includes estimates and confidence intervals categorized by demographics, geography, and time periods. CDC provides this information starting from October 2025.
A geological formation from the Cambrian to Ordovician periods, approximately 541 to 470 million years old. This dataset contains descriptive attribute information for spatial groundwater features in the Daly Basin, grouped into themes like location, hydrogeology, and land use. It was published by the Australian Ocean Data Network and last updated in April 2026.
Weekly cumulative COVID-19 vaccination coverage estimates for Medicare Fee-For-Service beneficiaries aged 65 years and older, calculated using Kaplan-Meier survival analysis. The data is managed by the Centers for Medicare & Medicaid Services (CMS) and published via data.cdc.gov, with the latest update in March 2026. Coverage is broken down by race, ethnicity, and COVID-19 season.
Gregory Kearney's 1.8 MB dataset from 2026 serves as a metric for health disparity indicators. It likely contains data linking social vulnerability factors to spatial patterns of COVID-19 mortality. The dataset is intended to inform global implications for respiratory health equity.
A paper outlines evolving practices for head and neck surgical oncologists during the COVID-19 pandemic. It combines experiences from Wuhan University and the University of Toronto during the SARS outbreak in 2003. The author, Antoine Eskander MD ScM from Sunnybrook Health Science Centre, provides key practical considerations for maintaining oncology services.
Raw cycle threshold (Ct) values from RT-qPCR analysis of human colostrum samples, shared by Paulina Gil-Kulik on figshare. The dataset includes results from a group of women who had COVID-19 during pregnancy and a healthy control group, measuring expression levels of miR-21, miR-155, and the transcription factor SOX1. The dataset was last updated on April 16, 2026.
Plasma proteomic analysis compares 14 individuals with Post-Vaccination/Post-Infection Syndrome (PV/PIS) to 16 healthy controls. The study identifies alterations in coagulation factors, acute phase proteins, and immune response modulators using liquid-chromatography-mass spectrometry. It was authored by Maxine Waters and published in March 2026.
A proteomic study analyzes plasma from 14 individuals with Post-Vaccination/Post-Infection Syndrome and 16 healthy controls. The research identifies significant alterations in coagulation factors, acute phase proteins, and immune response modulators. It was authored by Maxine Waters and published in 2026.
Yafei Mi published a dataset comparing computational efficiency on the ACDC cardiac MRI segmentation dataset using only 10% labeled data. The dataset is a 5.5 KB XLS file, last updated in April 2026. It provides metrics for evaluating the speed and resource usage of segmentation models on a subset of the well-known ACDC benchmark.
375 participants living with HIV were recruited from clinics in Montreal, Ottawa, Toronto, and Vancouver between April 2021 and January 2022. Data includes demographics, health behaviors, vaccination history, and serology results from 4,548 serum and plasma samples collected up to October 2022. This dataset, contributed to the CITF Databank by Aslam Anis, focuses on immunogenicity and safety outcomes following third and fourth COVID 19 vaccine doses.
63,406 deaths from rheumatoid arthritis-related cardiovascular disease occurred among U.S. adults aged 25 and older from 1999 to 2023. The dataset contains age-adjusted mortality rates, annual percent change estimates, and demographic breakdowns by sex, region, race/ethnicity, and urbanicity. It was compiled by Ye Jiang using CDC WONDER mortality data and ICD-10 codes.
Python code implements a rolling-origin forecasting approach for Google Community Mobility Reports data in Thailand. The work applies Facebook Prophet, ARIMA, and Feature Engineered XGBoost models to forecast mobility trends across six location categories during the COVID-19 pandemic. The study includes a Granger Causality Test to examine relationships between mobility patterns and COVID-19 case numbers.
A 6.5 KB text file containing Python code for an ARIMA model. The code was developed by Aritath Siraphatwongkorn to forecast human mobility trends in Thailand during the COVID-19 pandemic, using data from Google Community Mobility Reports. The study compared ARIMA against Facebook Prophet and Feature Engineered XGBoost models.
Aritath Siraphatwongkorn published Python code in 2026 for forecasting human mobility trends in Thailand during the COVID-19 pandemic. The code implements Facebook Prophet, ARIMA, and Feature Engineered XGBoost models to analyze Google Community Mobility Reports data across six location categories.
A 659.9 KB CSV file containing data on motorcycle-related injuries, shared under a CC-BY-4.0 license. The dataset was uploaded by Elvis A. Tanue to figshare and last updated on April 20, 2026. Its specific contents and scope must be determined by inspecting the downloaded file.