Search for a Dataset - Humanitarian Data Exchange

Afghanistan - Natural Disaster Incidents in 2022

500+ Downloads

Time Period of the Dataset [?]: January 01, 2022-September 19, 2022 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: OCHA Afghanistan - Natural Disaster Incidents

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.

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Afghanistan - Natural disaster incidents in 2017

OCHA Afghanistan

300+ Downloads

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

This dataset updates: Every year

This dataset is part of the data series [?]: OCHA Afghanistan - Natural Disaster Incidents

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.

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Afghanistan - Emergency Shelter Rapid Assessment Mechanism 2022

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: April 03, 2022-December 01, 2022 ... More

This dataset updates: Never

According to the Afghanistan Humanitarian Needs Overview 2023, 28.3 million people need humanitarian assistance with 9.7 million need Emergency Shelter and Non-Food Items (ES/NFI) assistance. The Rapid Assessment Mechanism (RAM) aims to provide a structured and standardized approach to identify and prioritize the population most in need of ES/NFI assistance as well as to inform allocations. Two rounds of data collection were completed in April and November 2022. In March April 10,900 interviews were conducted by 38 partners. In the following 2nd round, 8200 interviews were conducted. The survey covered 109 prioritised sites. 84% of surveyed households reported that they were unable to repair their shelter because of financial barriers. 81% reported not having sufficient winter clothes and 77% reported not having enough heating devices. Furthermore, 35% said they felt unsafe in their shelters.

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Afghanistan - Work of InterAction Members

InterAction

60+ Downloads

Time Period of the Dataset [?]: February 10, 2021-July 25, 2023 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: Work of InterAction Members

InterAction is an alliance of international NGOs, all working to make the world a more peaceful, just, and prosperous place. NGO Aid Map highlights the work of InterAction Member NGOs around the globe.

CSV

Afghanistan - Internal Displacements (New Displacements) – IDPs

Internal Displacement Monitoring Centre (IDMC)

600+ Downloads

Time Period of the Dataset [?]: January 01, 2008-December 31, 2023 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: IDMC - Internally displaced persons

Internally displaced persons are defined according to the 1998 Guiding Principles 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. "Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year. "Internal displacements (New Displacements)" 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.

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Afghanistan: Acute Food Insecurity Country Data

Integrated Food Security Phase Classification (IPC)

1100+ Downloads

Time Period of the Dataset [?]: May 01, 2017-October 31, 2024 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: IPC - Acute Food Insecurity Classification

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. There is also a global dataset.

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Afghanistan - Open spaces and green areas

United Nations Human Settlement Programmes, Data and Analytics Section

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

This dataset updates: Every year

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).

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Afghanistan - Housing, slums and informal settlements

United Nations Human Settlement Programmes, Data and Analytics Section

Time Period of the Dataset [?]: January 01, 2005-December 31, 2022 ... More

This dataset updates: Every year

Proportion of urban population living in slums or informal settlements per country, territory and region, based on 4 out of 5 main household shelter deprivations defined by UN-Habitat as indicators of informality: lack of access to improved water, lack of access to improved sanitation, lack of sufficient living area and quality/durability of structure. Security of tenure is the fifth deprivation that is not included due to data limitations. Proportion of urban population living in inadequate housing, calculated based on households with net monthly expenditure on housing exceeding 30% of their total monthly income .

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Afghanistan: Humanitarian Situation Monitoring Round3 KII Dataset [By Request Only]

REACH Initiative

Time Period of the Dataset [?]: October 30, 2022-November 23, 2022 ... More

This data is by request only

Humanitarian Situation Monitoring aims to collect and then triangulate information regarding service provision, sectoral needs, and vulnerabilities in Afghan communities, in order to then support geographical and sectoral prioritizations within the 2022 humanitarian response in Afghanistan, particularly in light of the rapidly evolving context in Afghanistan. The key-informant-based HSM methodology uses settlements as the unit of analysis, using a structured survey tool to interview key informants about the situation in their settlement. A sampling frame covering all 401 districts in Afghanistan was used, covering a minimum of 10% of total settlements in each district. To achieve geographical spread across each district, at least three key informant interviews (KIIs), in a number proportionate to the number of settlements, were conducted in each Basic Service Unit (BSU). To determine a BSU (defined as an economic/geographic service unit which relies on the same services, i.e. healthcare clinics and schools, and common public spaces, i.e. markets and roads), participatory mapping of settlements and services available was conducted prior to data collection. Any analysis conducted using the data in this file will generate statistically non-representative results, as the key informant methodology is indicative

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Afghanistan: Humanitarian Situation Monitoring Round5 KII Dataset [By Request Only]

REACH Initiative

Time Period of the Dataset [?]: November 12, 2023-December 07, 2023 ... More

This data is by request only

Humanitarian Situation Monitoring aims to collect and then triangulate information regarding service provision, sectoral needs, and vulnerabilities in Afghan communities, in order to then support geographical and sectoral prioritizations within the humanitarian response in Afghanistan, particularly in light of the rapidly evolving context in Afghanistan. The key-informant-based HSM methodology uses settlements as the unit of analysis, using a structured survey tool to interview key informants about the situation in their settlement. A sampling frame covering all 401 districts in Afghanistan was used, covering a minimum of 10% of total settlements in each district. To achieve geographical spread across each district, at least three key informant interviews (KIIs), in a number proportionate to the number of settlements, were conducted in each Basic Service Unit (BSU). To determine a BSU (defined as an economic/geographic service unit which relies on the same services, i.e. healthcare clinics and schools, and common public spaces, i.e. markets and roads), participatory mapping of settlements and services available was conducted prior to data collection. Any analysis conducted using the data in this file will generate statistically non-representative results, as the key informant methodology is indicative.

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Afghanistan Railways (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

200+ Downloads

Time Period of the Dataset [?]: August 09, 2024-August 09, 2024 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Railways

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['railway'] IN ('rail','station') Features may have these attributes: name name:en railway ele operator:type layer addr:full addr:city source name:fa This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Afghanistan Waterways (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

300+ Downloads

Time Period of the Dataset [?]: August 09, 2024-August 09, 2024 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Waterways

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay') Features may have these attributes: name name:en waterway covered width depth layer blockage tunnel natural water source name:fa This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

REACH_Afghanistan_Humanitarian_Situation_Monitoring_Pilot_KII_Dataset [By...

REACH Initiative

Time Period of the Dataset [?]: December 22, 2021-January 11, 2022 ... More

This data is by request only

The HSM Pilot aims to monitor how the needs in the districts that were assessed under the Whole of Afghanistan Assessment (WoAA 2021) are evolving under the rapidly changing context in Afghanistan, whilst providing sufficient longitudinal data to allow for the development of an analytical framework that would allow a regular monitoring of humanitarian needs. This pilot is a one-time assessment designed to demonstrate the utility of a broader HSM designed and led by the humanitarian response in Afghanistan. HSM would aim to inform both the geographical and sectoral prioritization to inform a tailored and evidence-based response. To determine the assessment framework, an adapted Hard to Reach (HtR) methodology was used. At least three key informant interviews (KIIs), in a number proportionate to the number of settlements, were conducted in each Basic Service Unit (BSU). To determine a BSU, participatory mapping of settlements and services available were conducted prior to data collection. Key informant networks were developed to cover the entirety of selected districts, stratifying each district’s network by BSU to ensure a minimum of 3 KIs per BSU, each with information covering a different settlement than the others. Any analysis conducted using the data in this file would generate statistically non-representative results, as the key informant methodology is indicative.

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Afghanistan Health Facilities (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

200+ Downloads

Time Period of the Dataset [?]: August 09, 2024-August 09, 2024 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Health Facilities

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['healthcare'] IS NOT NULL OR tags['amenity'] IN ('doctors', 'dentist', 'clinic', 'hospital', 'pharmacy') Features may have these attributes: name name:en amenity building healthcare healthcare:speciality operator:type capacity:persons addr:full addr:city source name:fa This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Afghanistan: Population Density for 400m H3 Hexagons

Kontur

60+ Downloads

Time Period of the Dataset [?]: July 10, 2023-November 01, 2023 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: Kontur - Population Density for 400m H3 Hexagons

Afghanistan population density for 400m H3 hexagons. Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution. Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.

Geopackage

Afghanistan: WOF Administrative Subdivisions and Human Settlements

Who's On First

20+ Downloads

Time Period of the Dataset [?]: August 18, 2015-March 04, 2024 ... More

This dataset updates: Every year

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

SHP

Afghanistan - Data on forcibly displaced populations and stateless persons

UNHCR - The UN Refugee Agency

1400+ Downloads

Time Period of the Dataset [?]: January 01, 2014-December 31, 2023 ... More

This dataset updates: Every six months

This dataset is part of the data series [?]: UNHCR - Data on forcibly displaced populations and stateless persons

Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across more than 70 years of statistical activities. The data includes the countries / territories of asylum and origin. Specific resources are available for end-year population totals, demographics, asylum applications, decisions, and solutions availed by refugees and IDPs (resettlement, naturalisation or returns).

CSV

Afghanistan Education Facilities (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

200+ Downloads

Time Period of the Dataset [?]: August 09, 2024-August 09, 2024 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: HOTOSM - Education Facilities

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university') Features may have these attributes: name name:en amenity building operator:type capacity:persons addr:full addr:city source name:fa This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Afghanistan - Socio-economic assessment of IDPs and returnees in the five...

UNHCR - The UN Refugee Agency

10+ Downloads

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

This dataset updates: Never

At the end of 2015, Herat Province was among the highest IDP hosting provinces in Afghanistan, accounting for approximately 10% of the country's IDP population. In order to obtain reliable information on the socio-economic conditions of IDPs and returnees in Herat Province, a comprehensive sample survey was carried out among 11,264 households in the 5 most populated IDP/returnee settlements (Shagofan, Jebraiel, Maslakh, Now Abad and Kahdistan) in 2017.

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Afghanistan - Socio-economic assessment of IDPs and returnees in the five...

UNHCR - The UN Refugee Agency

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

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Socioeconomic assessment of Refugees

At the end of 2015, Herat Province was among the highest IDP hosting provinces in Afghanistan, accounting for approximately 10% of the country's IDP population. In order to obtain reliable information on the socio-economic conditions of IDPs and returnees in Herat Province, a comprehensive sample survey was carried out among 11,264 households in the 5 most populated IDP/returnee settlements (Shagofan, Jebraiel, Maslakh, Now Abad and Kahdistan) in 2017.

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PDF

Afghanistan - Socio-economic assessment of IDPs and returnees in the five...

UNHCR - The UN Refugee Agency

30+ Downloads

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

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Socioeconomic assessment of Refugees

At the end of 2015, Herat Province was among the highest IDP hosting provinces in Afghanistan, accounting for approximately 10% of the country's IDP population. In order to obtain reliable information on the socio-economic conditions of IDPs and returnees in Herat Province, a comprehensive sample survey was carried out among 11,264 households in the 5 most populated IDP/returnee settlements (Shagofan, Jebraiel, Maslakh, Now Abad and Kahdistan) in 2017.

Web App
PDF

REACH_Afghanistan_Humanitarian_Situation_Monitoring_Round1_KII_Dataset [By...

REACH Initiative

Time Period of the Dataset [?]: February 28, 2022-April 12, 2022 ... More

This data is by request only

Humanitarian Situation Monitoring aims to collect and then triangulate information regarding service provision, sectoral needs, and vulnerabilities in Afghan communities, in order to then support geographical and sectoral prioritizations within the 2022 humanitarian response in Afghanistan, particularly in light of the rapidly evolving context in Afghanistan. The key-informant-based HSM methodology uses settlements as the unit of analysis, using a structured survey tool to interview key informants about the situation in their settlement. A sampling frame covering all 419 districts in Afghanistan was used, covering a minimum of 10% of total settlements in each district. To achieve geographical spread across each district, at least three key informant interviews (KIIs), in a number proportionate to the number of settlements, were conducted in each Basic Service Unit (BSU). To determine a BSU (defined as an economic/geographic service unit which relies on the same services, i.e. healthcare clinics and schools, and common public spaces, i.e. markets and roads), participatory mapping of settlements and services available was conducted prior to data collection. Any analysis conducted using the data in this file will generate statistically non-representative results, as the key informant methodology is indicative

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REACH_Afghanistan_Humanitarian_Situation_Monitoring_Round2_KII_Dataset [By...

REACH Initiative

Time Period of the Dataset [?]: July 30, 2022-September 07, 2022 ... More

This data is by request only

Humanitarian Situation Monitoring aims to collect and then triangulate information regarding service provision, sectoral needs, and vulnerabilities in Afghan communities, in order to then support geographical and sectoral prioritizations within the 2022 humanitarian response in Afghanistan, particularly in light of the rapidly evolving context in Afghanistan. The key-informant-based HSM methodology uses settlements as the unit of analysis, using a structured survey tool to interview key informants about the situation in their settlement. A sampling frame covering all 401 districts in Afghanistan was used, covering a minimum of 10% of total settlements in each district. To achieve geographical spread across each district, at least three key informant interviews (KIIs), in a number proportionate to the number of settlements, were conducted in each Basic Service Unit (BSU). To determine a BSU (defined as an economic/geographic service unit which relies on the same services, i.e. healthcare clinics and schools, and common public spaces, i.e. markets and roads), participatory mapping of settlements and services available was conducted prior to data collection. Any analysis conducted using the data in this file will generate statistically non-representative results, as the key informant methodology is indicative.

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Afghanistan - JOINT MARKET MONITORING INITIATIVE (JMMI) 2022

REACH Initiative

90+ Downloads

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

This dataset updates: Never

JOINT MARKET MONITORING INITIATIVE (JMMI) Datasets for the year 2022.

XLSX

Afghanistan - Livelihoods Programme Monitoring Beneficiary Survey, 2019

UNHCR - The UN Refugee Agency

10+ Downloads

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

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Livelihoods Programme Monitoring Beneficiary Survey

The UNHCR Livelihoods Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices. Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. More info is available on the official website: https://lis.unhcr.org

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