Updated
March 30, 2020
| Dataset date: Mar 30, 2020
This dataset updates: Every day
FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
Updated
March 29, 2020
| Dataset date: Jan 1, 1999-Dec 31, 2018
This dataset updates: Every year
FAO statistics collates and disseminates food and agricultural statistics globally. The division develops methodologies and standards for data collection, and holds regular meetings and workshops to support member countries develop statistical systems. We produce publications, working papers and statistical yearbooks that cover food security, prices, production and trade and agri-environmental statistics.
Updated
March 29, 2020
| Dataset date: Jan 1, 1990-Mar 15, 2020
This dataset updates: Every week
This dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
This dataset contains Food Prices data for Swaziland. Food prices data comes from the World Food Programme and covers foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
Updated
March 29, 2020
| Dataset date: Jan 1, 1997-Dec 31, 2020
This dataset updates: As needed
The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
Updated
March 28, 2020
| Dataset date: Jan 1, 1989-Dec 31, 1989
This dataset updates: As needed
This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.
Sundberg, Ralph, and Erik Melander, 2013, โIntroducing the UCDP Georeferenced Event Datasetโ, Journal of Peace Research, vol.50, no.4, 523-532
Hรถgbladh Stina, 2019, โUCDP GED Codebook version 19.1โ, Department of Peace and Conflict Research, Uppsala University
Updated
March 28, 2020
| Dataset date: Jan 1, 2018-Dec 31, 2018
This dataset updates: As needed
Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"People Displaced" refers to the number of people living in displacement as of the end of each year.
"New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
Updated
March 28, 2020
| Dataset date: Oct 1, 2018
This dataset updates: As needed
The population of the world, allocated to 1 arcsecond blocks. This refines CIESINโs Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.
There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.
Updated
Live
| Dataset date: Jan 22, 2020-Mar 27, 2020
This dataset updates: Live
Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn. Pneumonia. 2020, BNO News, National Health Commission of the Peopleโs Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH). JSU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on github.
Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths.
On 23/03/2020, a new data structure was released. The current resources are:
time_series_covid19_confirmed_global.csv
time_series_covid19_deaths_global.csv for the latest time series data
---DEPRECATION WARNING---
The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020:
time_series_19-covid-Confirmed.csv
time_series_19-covid-Deaths.csv
time_series_19-covid-Recovered.csv
Updated
March 24, 2020
| Dataset date: Jan 1, 2012-Dec 31, 2018
This dataset updates: As needed
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, World Health Statistics, Health financing, Public health and environment, Substance use and mental health, Tobacco, Injuries and violence, HIV/AIDS and other STIs, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Health Equity Monitor, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, 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 Coordination, AMR GLASS Surveillance, AMR GLASS Quality assurance, Noncommunicable diseases and mental health, Health workforce, Neglected Tropical Diseases, AMR GASP, ICD
For links to individual indicator metadata, see resource descriptions.
Updated
March 24, 2020
| Dataset date: Jan 1, 2013-Dec 31, 2013
This dataset updates: As needed
This layer contains information about the flood hazard - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data sources: UNEP/UNISDR GAR 2013.
The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period.
Original dataset title: ICA Eswatini, 2019 - Flood hazard, 2013
Updated
March 24, 2020
| Dataset date: Jan 1, 1981-Dec 31, 2018
This dataset updates: As needed
This layer contains information about the drought hazard - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data source: HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE), 1981-2015.
The main indicator used for the analysis was the number of poor growing seasons observed in the time window of interest.
Original dataset title: ICA Eswatini, 2019 - Drought hazard, 1981-2018
Updated
March 24, 2020
| Dataset date: Jan 1, 2019-Dec 31, 2019
This dataset updates: As needed
This layer contains information about the severity of natural hazards (floods and droughts) estimated during the Integrated Context Analysis (ICA) performed in Eswatini in 2019.
Data sources: UNEP/UNISDR GAR 2013, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1981-2018.
Original dataset title: ICA Eswatini, 2019 - Natural shocks hazard
Updated
March 24, 2020
| Dataset date: Jan 1, 2011-Dec 31, 2019
This dataset updates: As needed
This layer contains information about the food security trend analysis - by second-level administrative unit - used for the purposes of the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data source: Eswatini Vulnerability Assessment and Analysis coordinated by the Eswatini Vulnerability Assessment Committee and the Central Statistics Office, 2011-2019.
The key indicators used for the purposes of the analysis were the Food Consumption Score (FSC) and the Coping Strategy Index (CSI), with a threshold set at 20% because national average of food insecurity, throughout the available rounds, was found to be 18.75%.
Original dataset title: ICA Eswatini, 2019 - Recurrence of food insecurity, 2011-2019
Updated
March 24, 2020
| Dataset date: Jan 1, 2011-Dec 31, 2019
This dataset updates: As needed
This layer contains information about the numbers of food insecure people - by second-level administrative unit - estimated for the purposes of the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data source: Eswatini Vulnerability Assessment and Analysis coordinated by the Eswatini Vulnerability Assessment Committee and the Central Statistics Office, 2011-2019.
The main indicators used for the analysis were the percentage of food insecure population for long-term planning and the additional population figures in case of a major shock.
Original dataset title: ICA Eswatini, 2019 - Estimates of food insecure people, 2011-2019
Updated
March 24, 2020
| Dataset date: Jan 1, 2001-Dec 31, 2016
This dataset updates: As needed
This layer contains information about the land degradation phenomenon - by second-level administrative area - observed for the purposes of the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data sources: HQ OSE GIS Analysis of NASA MODIS 2001-2016, WorldClim 1970-2000, FAO and NASA SRTM Digital Elevation Model data.
The main indicators used for the analysis were the average ecological changes observed between 2001-2006 and 2011-2016 and the percentage of erosion-prone surface.
Original dataset title: ICA Eswatini, 2019 - Land Degradation, 2001-2016
Updated
March 24, 2020
| Dataset date: Jan 1, 2019-Dec 31, 2019
This dataset updates: As needed
This layer contains information about the final classification deriving from the Integrated Context Analysis (ICA) run in Eswatini in 2019, showing the areas of convergence between recurrence of food insecurity and propensity to natural shocks (floods and droughts).
Original dataset title: ICA Eswatini, 2019 - ICA Categories & Areas
Updated
March 24, 2020
| Dataset date: Jan 1, 2009-Dec 31, 2018
This dataset updates: As needed
This layer contains information about the recurrence of prevalence of stunting - by first-level administrative unit - used for the purposes of the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data source: Eswatini Vulnerability Assessment and Analysis coordinated by the Eswatini Vulnerability Assessment Committee and the Central Statistics Office, 2009-2018.
The key indicator used for the purposes of the analysis was the prevalence of stunting in children under the age of 5, with a threshold set at 20% because, according to the guidelines suggested by the World Health Organization (WHO), this is the break between the classes 'Medium' and 'High'.
Original dataset title: ICA Eswatini, 2019 - Recurrence of prevalence of stunting, 2009-2018
Updated
March 24, 2020
| Dataset date: Jan 1, 2016-Dec 31, 2016
This dataset updates: As needed
This layer contains information about the most predominant livelihood zones - by second-level administrative area - identified during the Integrated Context Analysis (ICA) run in Eswatini in 2019.
Data source: Eswatini VAC Livelihood Baseline Update, 2016.
Original dataset title: ICA Eswatini, 2019 - Most predominant livelihood zones, 2016
Updated
March 20, 2020
| Dataset date: Jan 1, 2006-Dec 31, 2006
This dataset updates: Every year
Contains data from the DHS data portal. There is also a dataset containing Kingdom of Eswatini - National Demographic and Health Data on HDX.
The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
Updated
March 20, 2020
| Dataset date: Jan 1, 2006-Dec 31, 2006
This dataset updates: Every year
Contains data from the DHS data portal. There is also a dataset containing Kingdom of Eswatini - Subnational Demographic and Health Data on HDX.
The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
Updated
March 11, 2020
| Dataset date: Jan 1, 2012-Dec 31, 2018
This dataset updates: Every week
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, World Health Statistics, Health financing, Public health and environment, Substance use and mental health, Tobacco, Injuries and violence, HIV/AIDS and other STIs, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Health Equity Monitor, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, 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 Coordination, AMR GLASS Surveillance, AMR GLASS Quality assurance, Noncommunicable diseases and mental health, Health workforce, Neglected Tropical Diseases, AMR GASP, ICD
For links to individual indicator metadata, see resource descriptions.
Updated
March 6, 2020
| Dataset date: Jan 1, 2017-Dec 31, 2017
This dataset updates: Every month
The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
railway IN ('rail','subway','station')
Features may have these attributes:
layer
addr:city
operator:type
railway
source
addr:full
name
ele
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
healthcare IS NOT NULL OR amenity IN ('doctors','dentist','clinic','hospital','pharmacy')
Features may have these attributes:
healthcare:speciality
capacity:persons
addr:city
healthcare
building
operator:type
source
addr:full
name
amenity
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
