Contains data from World Health Organization's data portal covering the following categories: Mortality and global health estimates, Sustainable development goals, Millennium Development Goals (MDGs), Health systems, Malaria, Tuberculosis, Child health, Infectious diseases, Neglected Tropical Diseases, World Health Statistics, Health financing, Tobacco, Substance use and mental health, Injuries and violence, HIV/AIDS and other STIs, Public health and environment, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, Health inequality monitor, Health Equity Monitor, Child malnutrition, TOBACCO, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, 0, Insecticide resistance, Oral health, Universal Health Coverage, Global Observatory for eHealth (GOe), RSUD: GOVERNANCE, POLICY AND FINANCING : PREVENTION, RSUD: GOVERNANCE, POLICY AND FINANCING: TREATMENT, RSUD: GOVERNANCE, POLICY AND FINANCING: FINANCING, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT SECTORS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT CAPACITY AND TREATMENT COVERAGE, RSUD: SERVICE ORGANIZATION AND DELIVERY: PHARMACOLOGICAL TREATMENT, RSUD: SERVICE ORGANIZATION AND DELIVERY: SCREENING AND BRIEF INTERVENTIONS, RSUD: SERVICE ORGANIZATION AND DELIVERY: PREVENTION PROGRAMS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: SPECIAL PROGRAMMES AND SERVICES, RSUD: HUMAN RESOURCES, RSUD: INFORMATION SYSTEMS, RSUD: YOUTH, FINANCIAL PROTECTION, AMR GLASS, Noncommunicable diseases and mental health, Health workforce, AMR GASP, ICD, SEXUAL AND REPRODUCTIVE HEALTH, Immunization, NLIS For links to individual indicator metadata, see resource descriptions.

Consolidated 3W and 5W data (Who does What, Where) from OCHA Ukraine, collected from the clusters and organizations involved in the response.

This bi-weekly dataset provides an overview of the latest areas of control in Yemen and includes a map, excel spreadsheet and GIS layer. All datasets are fully PCODED to Admin 2 district level, enabling interoperability with other datasets. Through understanding the latest areas of control, it is possible to enhance analysis in areas such as political-economy through adjusting tools to take into account the current geographic situation. This dataset forms part of the Yemen CrisisInsight product suite which includes the Yemen Core Dataset, Yemen: Crisis Impact Overview and Yemen Risk Overview.

This dataset brings together data from a range of sources to provide a greater overall and comparative understanding of the current situation and context inside each district. The core indicators consist of key drivers (conflict, basic commodity prices, exclusion and marginalization, and disrupted access to life-saving services and income sources) and their major expected humanitarian impacts (food insecurity, cholera). The dataset includes a mix of quantitative and qualitative data. Qualitative data is collected by ACAPS through daily media monitoring, secondary data review, thematic products and discussions with experts in Yemen and the region. ACAPS tracks changes in these indicators and alerts the humanitarian community to emerging trends or risks that could overwhelm local coping mechanisms in Yemen, triggering a humanitarian emergency. This dataset forms the core of ACAPS Yemen Crisis Insight bi-monthly products such as the Yemen: Crisis Impact Overview and Yemen Risk Overview, and ad hoc risk alerts.

Newly displaced population due to conflict between 01 January 2022 and 30 June 2022, compiled by OCHA sub offices based on inter-agency assessment results. This data is a snapshot as of 31 July 2022 and the numbers are expected to change as new assessment figures become available.

This dataset contains key figures (topline numbers) on the world's most pressing humanitarian crises. The data, curated by ReliefWeb's editorial team based on its relevance to the humanitarian community, is updated regularly. The description of the files and columns can be found in the additional metadata spreadsheet file.

Number of Refugees returning to Afghanistan for the period of 01 January 2022 to 11 August 2022 by district of destination and origin.

1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.

List of public datasets on HDX that contain HXL hashtags, together with the organisations who provided them. Updated weekly.

Data Overview This repository contains spatiotemporal data from many official sources for 2019-Novel Coronavirus beginning 2019 in Hubei, China ("nCoV_2019") You may not use this data for commercial purposes. If there is a need for commercial use of the data, please contact Metabiota at info@metabiota.com to obtain a commercial use license. The incidence data are in a CSV file format. One row in an incidence file contains a piece of epidemiological data extracted from the specified source. The file contains data from multiple sources at multiple spatial resolutions in cumulative and non-cumulative formats by confirmation status. To select a single time series of case or death data, filter the incidence dataset by source, spatial resolution, location, confirmation status, and cumulative flag. Data are collected, structured, and validated by Metabiota’s digital surveillance experts. The data structuring process is designed to produce the most reliable estimates of reported cases and deaths over space and time. The data are cleaned and provided in a uniform format such that information can be compared across multiple sources. Data are collected at the time of publication in the highest geographic and temporal resolutions available in the original report. This repository is intended to provide a single access point for data from a wide range of data sources. Data will be updated periodically with the latest epidemiological data. Metabiota maintains a database of epidemiological information for over two thousand high-priority infectious disease events. Please contact us (info@metabiota.com) if you are interested in licensing the complete dataset. Cumulative vs. Non-Cumulative Incidence Reporting sources provide either cumulative incidence, non-cumulative incidence, or both. If the source only provides a non-cumulative incidence value, the cumulative values are inferred using prior reports from the same source. Use the CUMULATIVE FLAG variable to subset the data to cumulative (TRUE) or non-cumulative (FALSE) values. Case Confirmation Status The incidence datasets include the confirmation status of cases and deaths when this information is provided by the reporting source. Subset the data by the CONFIRMATION_STATUS variable to either TOTAL, CONFIRMED, SUSPECTED, or PROBABLE to obtain the data of your choice. Total incidence values include confirmed, suspected, and probable incidence values. If a source only provides suspected, probable, or confirmed incidence, the total incidence is inferred to be the sum of the provided values. If the report does not specify confirmation status, the value is included in the "total" confirmation status value. The data provided under the "Metabiota Composite Source" often does not include suspected incidence due to inconsistencies in reporting cases and deaths with this confirmation status. Outcome - Cases vs. Deaths The incidence datasets include cases and deaths. Subset the data to either CASE or DEATH using the OUTCOME variable. It should be noted that deaths are included in case counts. Spatial Resolution Data are provided at multiple spatial resolutions. Data should be subset to a single spatial resolution of interest using the SPATIAL_RESOLUTION variable. Information is included at the finest spatial resolution provided to the original epidemic report. We also aggregate incidence to coarser geographic resolutions. For example, if a source only provides data at the province-level, then province-level data are included in the dataset as well as country-level totals. Users should avoid summing all cases or deaths in a given country for a given date without specifying the SPATIAL_RESOLUTION value. For example, subset the data to SPATIAL_RESOLUTION equal to “AL0” in order to view only the aggregated country level data. There are differences in administrative division naming practices by country. Administrative levels in this dataset are defined using the Google Geolocation API (https://developers.google.com/maps/documentation/geolocation/). For example, the data for the 2019-nCoV from one source provides information for the city of Beijing, which Google Geolocations indicates is a “locality.” Beijing is also the name of the municipality where the city Beijing is located. Thus, the 2019-nCoV dataset includes rows of data for both the city Beijing, as well as the municipality of the same name. If additional cities in the Beijing municipality reported data, those data would be aggregated with the city Beijing data to form the municipality Beijing data. Sources Data sources in this repository were selected to provide comprehensive spatiotemporal data for each outbreak. Data from a specific source can be selected using the SOURCE variable. In addition to the original reporting sources, Metabiota compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name “Metabiota Composite Source.” The purpose of generating this new view of the outbreak is to provide the most accurate and precise spatiotemporal data for the outbreak. At this time, Metabiota does not incorporate unofficial - including media - sources into the “Metabiota Composite Source” dataset. Quality Assurance Data are collected by a team of digital surveillance experts and undergo many quality assurance tests. After data are collected, they are independently verified by at least one additional analyst. The data also pass an automated validation program to ensure data consistency and integrity. NonCommercial Use License Creative Commons License Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) This is a human-readable summary of the Legal Code. You are free: to Share — to copy, distribute and transmit the work to Remix — to adapt the work Under the following conditions: Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Noncommercial — You may not use this work for commercial purposes. Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same or similar license to this one. With the understanding that: Waiver — Any of the above conditions can be waived if you get permission from the copyright holder. Public Domain — Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license. Other Rights — In no way are any of the following rights affected by the license: Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations; The author's moral rights; Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights. Notice — For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to this web page. For details and the full license text, see http://creativecommons.org/licenses/by-nc-sa/3.0/ Liability Metabiota shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Metabiota be liable for any damages (whatsoever) arising out of the use or inability to use the database. The entire risk arising out of the use of the database remains with the user.

This dataset lists all contributions made by donors to the Central Emergency Response Fund (CERF). CERF receives broad support from United Nations Member States, observers, regional governments and international organizations, and the private sector, including corporations, non-governmental organizations and individuals.

This dataset lists project funding allocations from OCHA's Central Emergency Response Fund (CERF). CERF allocations are made to ensure a rapid response to sudden-onset emergencies or to rapidly deteriorating conditions in an existing emergency and to support humanitarian response activities within an underfunded emergency.

Trinidad and Tobago administrative levels 0 (country) and 1 (regional corporation or municipality) population statistics REFERENCE YEAR: 2011 INTERIM version combining Tobago parishes into one municipality (P-code TT90) for compatibility with the COD-AB. These CSV tables are suitable for database or GIS linkage to the Trinidad and Tobago administrative level 0-1 boundaries shapefiles.

Uzbekistan administrative level 0 (country) and 1 (province / viloyat, autonomous republic / respublika, or independent city / shahar) population statistics and level 0,1, and 2 (district / tuman) gazetteer. REFERENCE YEAR: 2018 The administrative level 1 CSV table is suitable for database or GIS linkage to the administrative level 1 shapefile available on HDX here. REVISION HISTORY: 22 July 2019 2018 population statistics update 12 July 2018 Initial upload

Saint Vincent and The Grenadines administrative level 002 sex and age disaggregated population statistics REFERENCE YEAR: 2012 These tables (at administrative level 0-1) are suitable for database or GIS linkage to the Saint Vincent and The Grenadines - Subnational Administrative Boundaries.

Venezuela administrative level 0 (country); 1 (state / estado; Capital District / Distrito Capital; and the Federal Dependencies / Dependencias Federales); 2 (municpality / municipio), and 3 (parish / parroquia) population statistics and gazeteer REFERENCE YEAR: 2011 UNFPA investigated replacement or projection of this dataset in 2021. No better alternative is currently available. These population statistics tables are suitable for database or GIS linkage to the Venezuela (Bolivarian Republic of) - Subnational Administrative Boundaries.

British Virgin Islands administrative level 0 (territory) and 1 (district) 2010 sex and age disaggregated population statistics REFERENCE YEAR: 2010 These tables are suitable for database or GIS linkage to the British Virgin Islands administrative level 0-1 boundaries.

United States Virgin Islands administrative level 0 (territory), 1 (district) and 2 (sub-district) disaggregated population statistics REFERENCE YEAR: 2010 These tables are suitable for database or GIS linkage to the United States Virgin Islands administrative level 0-2 boundaries.

This dataset contains shapefiles for Guinea, Liberia, and Sierra Leone from the OpenStreetMap (OSM) project. Each country has its individual file. The dataset counts with contributions of hundreds of users. This dataset is updated daily. The original dataset can be downloaded from the OSM West Africa Ebola response wiki.

This dataset contains the number of confirmed cases, recoveries and deaths by province due to the Coronavirus pandemic in Afghanistan.

The file provides information on the cases, deaths, ... of the various pathologies on the extent of the national territory. Le fichier renseigne sur les cas, décès, ... des différentes pathologies sur l'étendue du territoire national.