DTM’s Displacement Tracking tool collects and reports on displaced numbers of households on a daily basis, allowing for regular reporting of new displacements in terms of numbers, geography and needs. More than 3.6 million people are displaced as per August 2018 assessment.

The dataset shows Global Acute Malnutrition (GAM) moderate acute malnutrition (MAM) and severe acute malnutrition (SAM) numbers in Somalia

The Who does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in South Sudan at admin 2 level.

Acute malnutrition by admin 2

In response to the need for timely and accurate information on the multi-hazard in Uganda, the International Organization for Migration (IOM) in Uganda implements the Displacement Tracking Matrix (DTM). This dataset includes the number of affected individuals and households, the number of displaced individuals and households, and the most pressing needs.

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 Ginkgo Biosecurity, the biosecurity and public health unit of Ginkgo Bioworks at help-epi-modeling@ginkgobioworks.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 Ginkgo'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. Ginkgo Biosecurity maintains a database of epidemiological information for over three thousand high-priority infectious disease events (please note: this database was previously maintained by Metabiota; the team responsible joined Ginkgo Biosecurity in August 2022. When using the database, please cite Ginkgo Biosecurity and refer to this repository). Please contact us (help-epi-modeling@ginkgobioworks.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 "Multisource Fusion" 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, Ginkgo Biosecurity compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name "Multisource Fusion". 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, Ginkgo Biosecurity does not incorporate unofficial - including media - sources into the "Multisource Fusion" 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 The information is provided “AS IS” and Concentric makes no representations or warranties, express or implied, of any type whatsoever including, without limitation, title, noninfringement, accuracy, completeness, merchantability, or fitness for any particular purpose. Use of proprietary information shall be at the user’s own risk, and Concentric assumes no liability or obligation to the user as a result of use. Ginkgo Biosecurity shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Ginkgo Biosecurity 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.

In the humanitarian context / humanitarian profiling, it demonstrates a strong evidence base, positive impact on resource allocation, and forms the basis and reference point of any relief operation aiming to deliver aid according to the population’s needs. This data gives the total size of population for Borno, Adamawa, and Yobe states (BAY) and disaggregated by sex and age (SADD) for each population category. The population category is grouped into: • Internally displaced people (IDP) • Returnees • Host community • Inaccessible areas

The number of humanitarian incidents between since January 2024, compiled by OCHA based on number of incidents reported by humanitarian access working group (HAG). The numbers are expected to change as new assessment figures become available.

A weekly dataset providing the total number of reported demonstration events broken down by country. Demonstration events include ACLED’s protests and riots event types, with the exception of the mob violence sub-event type of the riots event type. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.

A weekly dataset providing the total number of reported political violence events and fatalities broken down by country. Political violence events include ACLED’s battles, violence against civilians, and explosions/remote violence event types, as well as the mob violence sub-event type of the riots event type. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.

A weekly dataset providing the total number of reported civilian targeting events and fatalities broken down by country. Civilian targeting events include violence against civilians events and explosions/remote violence events in which civilians were directly targeted. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.

This dataset shows key figures from the escalation of hostilities since 7 October 2023.

Overview The dataset contains harmonized indicators created from high-frequency phone surveys collected by the World Bank and partners. The surveys capture the socioeconomic impacts of the COVID-19 pandemic on households and individuals from all developing regions. Data are available for over 90 indicators in 14 topic areas, including education, food security, income, safety nets, and others. For more information, please refer to our Technical Note and Data Dictionary. Unit of Measure Percentages. Aggregation Method: The data is aggregated by Urban/Rural/National and Industry Sector Disclaimer: This harmonized dataset is an ongoing collation and harmonization of COVID-19 high-frequency phone survey (HFPS) data. Harmonization involves redefining indicators and categories so that they are comparable across countries. As a result, even if the names and definitions of indicators appear similar, numbers in this global database might differ slightly from those of each country's publications or dashboard. If you see large discrepancies or other issues, please reach out. Version Notes: COVID-19 Harmonized Household Data Feb 18 • Temporarily suppressed select income, labor, and government assistance indicators collected after wave 2 surveys for harmonization review • Added need for, and access to medical care in multiple countries • Temporarily suppressed select income, labor and government assistance indicators collected after wave 2 surveys for harmonization review Funding Name, Abbreviation, Role: The project received support from the Trust Fund for Statistical Capacity Building III (TFSCB-III). TFSCB-III is funded by the United Kingdom’s Foreign, Commonwealth & Development Office, the Department of Foreign Affairs and Trade of Ireland, and the Governments of Canada and Korea. Other Acknowledgments: This dashboard was created by the Data for Goals (D4G) team and the Regional High-Frequency Phone Survey (HFPS) Focal Points in the EFI Poverty and Equity Global Practice (POV GP), under the guidance of POV GP management, using data collected under the World Bank-wide COVID-19 HFPS initiative. Time Periods: March, 2021

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

The Risk List enumerates the risks ACAPS analysts have identified. ACAPS analysts conduct daily monitoring and independent analysis of more than 150 countries to support evidence-based decision-making in the humanitarian sector. The information comes from publicly available sources and expert opinions. Learn more about the ACAPS Risk list: https://www.acaps.org/en/thematics/all-topics/risk-list

Incidentes registrados en Guatemala por el Sistema Nacional de Gestión de Riesgos, desde los años 2008 al 2022, Bajo la plataforma de SISMICEDE, y este a su vez se comparte como parte de los esfuerzos de trasparentar las acciones en Gestión de Riesgo

Total sexual violence at the national level, number of police-recorded offences from 2003 to 2011

This dataset lists climate related funding allocations from OCHA's Central Emergency Response Fund (CERF) from 2006-2021.