Water sanitation and hygiene wash Severity Humanitarian Datasets | Find Crisis Data

REACH Central African Republic 2022 Multi-Sectoral Needs Assessment (MSNA),...

Time Period of the Dataset [?]: July 20, 2022-September 18, 2022 ... More

This data is by request only

The 2022 Multi-Sectoral Needs Assessment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) and mandated by the Inter-cluster Coordination Group (ICCG), aims to understand the multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entire territory of the Central African Republic. It also aims to understand specific needs and vulnerabilities of population groups, namely non-displaced households, returnees, internally displaced persons (IDPs) living in host communities, and IDPs living at sites. The needs assessment covers protection, health, mental health, WASH, Shelter and NFI, Education, food security, livelihoods and disabilities, as well as the perception of and satisfaction with humanitarian aid (AAP). The 2022 MSNA was conducted through a statistically representative household survey across 66 accessible sub-prefectures (admin2) out of the 72 sub-prefectures of the country. The inaccessible sub-prefectures were evaluated using a Key Informant survey. In consultation with key humanitarian partners and actors, a joint set of indicators, questions, and answer choices were developed for the assessment of needs in the context of the Central African Republic. All surveys were conducted through face-to-face interviews, using the tablet-based Kobo Collect Open Data Kit (ODK) app. Household data collection took place from July 20 to September 18, 2022. A total of 12,347 households were assessed after data cleaning. Data is statistically representative at a 92% confidence level and a +/- 10% margin of error with a buffer of 10% for the entire population on the level of sub-prefectures (admin2) and higher levels, and for specific population groups on the level of prefectures (admin1) and higher levels.

Request access

Haiti: CBS Impact on Household Sanitation Quality of Life

Sustainable Organic Integrated Livelihoods

Time Period of the Dataset [?]: October 01, 2023-November 01, 2024 ... More

This dataset updates: Never

Staff of a container-based sanitation (CBS) service operating in Cap Haitien, Haiti surveyed baseline sanitation-related quality of life (SanQoL) among all households who expressed interest in joining the service between October 2023 and November 2024. For households who proceeded with joining, follow-up visits were conducted >4 weeks after installation to determine endline SanQoL. Each SanQoL response was scored between 0 (worst) and 3 (best). The difference between baseline and endline SanQoL overall and attribute-specific scores were calculated for each household. This dataset contains each household's baseline, endline, and delta attribute-specific and cumulative scores as well as the following demographics: the number of people residing in the household, the type and location of sanitation used prior to joining the CBS service, urbanicity of the household location, and whether anyone in the household owns a smartphone. These data have been analyzed and submitted for publication in a peer-reviewed journal.

CSV

Central America Length of Water Infrastructure by ACH-GIS4Tech

Acción contra el hambre - GIS4tech

90+ Downloads

Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More

This dataset updates: As needed

This indicator shows the length of natural and artificial watercourses per municipality area, based on information from 4 typologies (canals, streams, riverside and rivers). Source: OpenStreetMap. Categorized by country, department and municipality. For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform: https://predisan.gis4tech.com/ca4

CSV

Syrian Arab Republic: Humanitarian Needs

OCHA Humanitarian Programme Cycle Tools (HPC Tools)

2700+ Downloads

Time Period of the Dataset [?]: January 01, 2017-December 31, 2025 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Humanitarian Needs Overview

This dataset was compiled by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. It provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance, and represents a consolidated evidence base and helps inform joint strategic response planning.

CSV
XLSX

Colombia - High Frequency Survey - Q4 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: October 01, 2024-December 30, 2024 ... More

This dataset updates: Never

The data was collected using the High Frequency Survey (HFS). The survey allowes for better reaching populations of interest with remote modalities (phone interviews and self-administered surveys online) and improved sampling guidance and strategies. It includes a set of standardized regional core questions while allowing for operation-specific customizations. The core questions revolve around populations of interest's demographic profile, difficulties during their journey, specific protection needs, access to documentation and regularization, health access, coverage of basic needs, coping capacity and negative mechanisms used, and well-being and local integration. The data collected has been used by countries in their protection monitoring analysis and vulnerability analysis.

Web App
PDF

Haiti - Humanitarian Access Severity

OCHA Haiti

200+ Downloads

Time Period of the Dataset [?]: April 30, 2023-December 12, 2024 ... More

This dataset updates: Every year

Humanitarian access constraints data compiled at national level based on workshops in the 10 Departements (admin 1). The dataset provides an estimation on the severity level for different type of actors and different types of access constraints.

XLSX

Niger Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

700+ Downloads

Time Period of the Dataset [?]: January 01, 2006-December 31, 2012 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Chad Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

600+ Downloads

Time Period of the Dataset [?]: January 01, 2010-December 31, 2019 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Central African Republic Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

600+ Downloads

Time Period of the Dataset [?]: January 01, 2010-December 31, 2019 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Burundi Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

200+ Downloads

Time Period of the Dataset [?]: January 01, 2010-December 31, 2017 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Madagascar Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

200+ Downloads

Time Period of the Dataset [?]: January 01, 2008-December 31, 2021 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Mali Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

600+ Downloads

Time Period of the Dataset [?]: January 01, 2006-December 31, 2018 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Guinea Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

100+ Downloads

Time Period of the Dataset [?]: January 01, 2012-December 31, 2018 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Ethiopia Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

900+ Downloads

Time Period of the Dataset [?]: January 01, 2011-December 31, 2019 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Afghanistan Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

800+ Downloads

Time Period of the Dataset [?]: January 01, 2015-December 31, 2023 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Burkina Faso Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

700+ Downloads

Time Period of the Dataset [?]: January 01, 2010-December 31, 2021 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Guinea-Bissau Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

100+ Downloads

Time Period of the Dataset [?]: January 01, 2014-December 31, 2019 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Mozambique Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

700+ Downloads

Time Period of the Dataset [?]: January 01, 2003-December 31, 2023 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Democratic Republic of the Congo Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

700+ Downloads

Time Period of the Dataset [?]: January 01, 2007-December 31, 2018 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Mauritania Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

100+ Downloads

Time Period of the Dataset [?]: January 01, 2011-December 31, 2021 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Sierra Leone Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

100+ Downloads

Time Period of the Dataset [?]: January 01, 2013-December 31, 2019 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Benin Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

200+ Downloads

Time Period of the Dataset [?]: January 01, 2006-December 31, 2022 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Angola Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

100+ Downloads

Time Period of the Dataset [?]: January 01, 2015-December 31, 2016 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Uganda Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

300+ Downloads

Time Period of the Dataset [?]: January 01, 2011-December 31, 2016 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV

Sudan Multi Dimensional Poverty Index

Oxford Poverty & Human Development Initiative

700+ Downloads

Time Period of the Dataset [?]: January 01, 2010-December 31, 2014 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: Oxford Poverty and Human Development Initiative - Global Multidimensional Poverty Index

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources 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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

CSV