Madagascar

Key Figures
  • Updated 30 May 2021 | Dataset date: January 01, 2008-December 31, 2020
    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.
    300+ Downloads
    This dataset updates: Every year
  • Updated 6 May 2021 | Dataset date: April 01, 2021-December 03, 2021
    The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication (preprint) for the Relative Wealth Index is available here: https://arxiv.org/abs/2104.07761 Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
    8200+ Downloads
    This dataset updates: As needed
  • Updated 4 May 2021 | Dataset date: January 01, 1990-December 31, 2030
    The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
    100+ Downloads
    This dataset updates: Every year
  • Updated Live | Dataset date: January 01, 2008-December 03, 2021
    List of airports in Madagascar, with latitude and longitude. Unverified community data from http://ourairports.com/countries/MG/
    60+ Downloads
    This dataset updates: Live
  • Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
    100+ Downloads
    This dataset updates: Every three months
  • Updated 2 April 2021 | Dataset date: May 05, 2020-May 05, 2020
    This data was developed as part of the Modelling Exposure Through Earth Observation Routines (METEOR) project and is a Level 1, or a global-quality exposure data set. Minimal country-specific data was collected. The data is intended for CAT modeling and loss estimation. Repurposing this data for any reason other than assessing risk is not recommended. The data presents the estimated number of buildings, building area, and rebuilding value at a 15-arcsecond grid resolution (approximately 500 meters at the equator). This data set is in point shapefile format where the points represent the centroids of the 15-arcsecond grid. The results were created through a process of spreading the number of buildings to the 15-arcsecond level by a statistical assessment of moderate resolution EO data, which is described in more detail in the dasymetric mapping lineage processing step. The estimated building count at any given area is a result of statistical processes and should not be mistaken as a building count. The structural classes of buildings used for risk assessment are estimated given the building wall, floor, and roof material classes surveyed through 2002 Population and Housing Census - Volume 1. Analytical report. Additionally, the data is provided in Open Exposure Data (OED) import format, as a pair of CSV files. One CSV file contains the location details, and the other is an "account" file that is filled with default information to satisfy OED format requirements. The OED input files are set to use "All perils" (i.e. "AA1"). All required OED account-related fields are populated with "1" by default (such as PortNumber, AccNumber, PolNumber). If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 Please see the METEOR project page for information about the METEOR Project: http://meteor-project.org/ Please see the METEOR map portal for interactive maps: https://maps.meteor-project.org/ For more information about the Open Exposure Data (OED) standard, please see https://github.com/OasisLMF/OpenDataStandards
    30+ Downloads
    This dataset updates: Never
  • Updated 6 March 2021 | Dataset date: January 01, 2020-December 31, 2020
    UNICEF Eastern and Southern Africa Risks and Hazards- situation and response
    100+ Downloads
    This dataset updates: Never
  • Updated Live | Dataset date: February 08, 2021-December 03, 2021
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
    100+ Downloads
    This dataset updates: Live
  • Updated 22 February 2021 | Dataset date: December 01, 2020-February 19, 2021
    The dataset contains 93 harmonized indicators on 14 topics (demographic, food security, education, labor, health..) on households and individuals in 44 countries across all developing regions.
    500+ Downloads
    This dataset updates: As needed
  • Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
    80+ Downloads
    This dataset updates: Every year
  • Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
    200+ Downloads
    This dataset updates: Every year
  • Updated 30 October 2020 | Dataset date: December 31, 2019-December 31, 2019
    UNICEF Eastern and Southern Africa Risks and Hazards- situation
    100+ Downloads
    This dataset updates: As needed
  • Updated 30 October 2020 | Dataset date: December 31, 2019-December 31, 2019
    The Database and dashboard covers the regional humanitarian situation including targets, results and funding all as of December 2019 for entire Eastern and Southern Africa. Annual 2019 Database.
    100+ Downloads
    This dataset updates: As needed
  • Updated Live | Dataset date: November 16, 2015-December 03, 2021
    List of aid activities by InterAction members in Madagascar. Source: http://ngoaidmap.org/location/gn_1062947
    10+ Downloads
    This dataset updates: Live
  • Updated 10 September 2020 | Dataset date: July 08, 2020-July 10, 2021
    This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2020 methodology is detailed in Alkire, Kanagaratnam & Suppa (2020).
    80+ Downloads
    This dataset updates: Every year
  • Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset is compiled from two categories of sources: (a) verified security events submitted to Insecurity Insight by 30 Aid in Danger partner agencies; and (b) publicly reported events identified by Insecurity Insight and published in the Aid in Danger Monthly News Brief. Events are categorised by date, country, type of organisation affected and event category, based on standard definitions.
    500+ Downloads
    This dataset updates: As needed
  • Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset contains events in which an aid worker was involved in a road safety accident (RSA). Categorized by country.
    800+ Downloads
    This dataset updates: As needed
  • Updated 2 September 2020 | Dataset date: May 01, 2016-September 01, 2016
    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).
    300+ Downloads
    This dataset updates: Every month
  • Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: beds addr:city addr:street man_made opening_hours addr:housenumber name amenity shop rooms addr:full source tourism This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    100+ Downloads
    This dataset updates: Every month
  • Updated 12 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: addr:city addr:street building building:levels source addr:housenumber name addr:full office building:materials This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    200+ Downloads
    This dataset updates: Every month
  • Updated 12 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: covered natural source water name width blockage tunnel depth waterway layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    500+ Downloads
    This dataset updates: Every month
  • Updated 12 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: bridge smoothness source oneway surface highway name width lanes layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    500+ Downloads
    This dataset updates: Every month
  • Updated 9 July 2020 | Dataset date: March 01, 2017-December 31, 2021
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    10+ Downloads
    This dataset updates: As needed
  • Updated 4 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL Features may have these attributes: addr:city name amenity port operator:type addr:full source building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    60+ Downloads
    This dataset updates: Every month
  • Updated 4 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    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: addr:city railway name operator:type addr:full source ele layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    50+ Downloads
    This dataset updates: Every month