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.

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, Neglected Tropical Diseases, World Health Statistics, Health financing, Tobacco, Substance use and mental health, Injuries and violence, HIV/AIDS and other STIs, Public health and environment, Nutrition, Urban health, Child mortality, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, Health inequality monitor, Health Equity Monitor, Child malnutrition, TOBACCO, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, 0, 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, Noncommunicable diseases and mental health, Health workforce, AMR GASP, ICD, SEXUAL AND REPRODUCTIVE HEALTH, Immunization, NLIS, AMC GLASS For links to individual indicator metadata, see resource descriptions.

This dataset contains Food Prices data for State of Palestine, sourced from the World Food Programme Price Database. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 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 COVID-19 vaccine dose availability forecasts as well as actual deliveries for countries with Humanitarian Response Plans. The data on vaccine availability forecasts was manually extracted from the COVAX Facility Interim Distribution Forecast as announced by COVAX on 3 February 2021. Figures for actual deliveries through channels other than COVAX are compiled by OCHA from press reports. The source(s) press releases, official announcements or articles for each such vaccine delivery are included in the dataset.

Contains data from the World Bank's data portal covering the following topics which also exist as individual datasets on HDX: Agriculture and Rural Development, Aid Effectiveness, Economy and Growth, Education, Energy and Mining, Environment, Financial Sector, Health, Infrastructure, Social Protection and Labor, Poverty, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Climate Change, External Debt, Trade.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Trade is a key means to fight poverty and achieve the Millennium Development Goals, specifically by improving developing country access to markets, and supporting a rules based, predictable trading system. In cooperation with other international development partners, the World Bank launched the Transparency in Trade Initiative to provide free and easy access to data on country-specific trade policies.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Debt statistics provide a detailed picture of debt stocks and flows of developing countries. Data presented as part of the Quarterly External Debt Statistics takes a closer look at the external debt of high-income countries and emerging markets to enable a more complete understanding of global financial flows. The Quarterly Public Sector Debt database provides further data on public sector valuation methods, debt instruments, and clearly defined tiers of debt for central, state and local government, as well as extra-budgetary agencies and funds. Data are gathered from national statistical organizations and central banks as well as by various major multilateral institutions and World Bank staff.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Climate change is expected to hit developing countries the hardest. Its effects—higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters—pose risks for agriculture, food, and water supplies. At stake are recent gains in the fight against poverty, hunger and disease, and the lives and livelihoods of billions of people in developing countries. Addressing climate change requires unprecedented global cooperation across borders. The World Bank Group is helping support developing countries and contributing to a global solution, while tailoring our approach to the differing needs of developing country partners. Data here cover climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use. Other indicators relevant to climate change are found under other data pages, particularly Environment, Agriculture & Rural Development, Energy & Mining, Health, Infrastructure, Poverty, and Urban Development.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Data here cover child labor, gender issues, refugees, and asylum seekers. Children in many countries work long hours, often combining studying with work for pay. The data on their paid work are from household surveys conducted by the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. Gender disparities are measured using a compilation of data on key topics such as education, health, labor force participation, and political participation. Data on refugees are from the United Nations High Commissioner for Refugees complemented by statistics on Palestinian refugees under the mandate of the United Nations Relief and Works Agency.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Technological innovation, often fueled by governments, drives industrial growth and helps raise living standards. Data here aims to shed light on countries technology base: research and development, scientific and technical journal articles, high-technology exports, royalty and license fees, and patents and trademarks. Sources include the UNESCO Institute for Statistics, the U.S. National Science Board, the UN Statistics Division, the International Monetary Fund, and the World Intellectual Property Organization.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Effective governments improve people's standard of living by ensuring access to essential services – health, education, water and sanitation, electricity, transport – and the opportunity to live and work in peace and security. Data here includes World Bank staff assessments of country performance in economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions for the poorest countries. Also included are indicators on revenues and expenses from the International Monetary Fund's Government Finance Statistics, and on tax policies from various sources.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Private markets drive economic growth, tapping initiative and investment to create productive jobs and raise incomes. Trade is also a driver of economic growth as it integrates developing countries into the world economy and generates benefits for their people. Data on the private sector and trade are from the World Bank Group's Private Participation in Infrastructure Project Database, Enterprise Surveys, and Doing Business Indicators, as well as from the International Monetary Fund's Balance of Payments database and International Financial Statistics, the UN Commission on Trade and Development, the World Trade Organization, and various other sources.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. The supply of labor available in an economy includes people who are employed, those who are unemployed but seeking work, and first-time job-seekers. Not everyone who works is included: unpaid workers, family workers, and students are often omitted, while some countries do not count members of the armed forces. Data on labor and employment are compiled by the International Labour Organization (ILO) from labor force surveys, censuses, establishment censuses and surveys, and administrative records such as employment exchange registers and unemployment insurance schemes.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Infrastructure helps determine the success of manufacturing and agricultural activities. Investments in water, sanitation, energy, housing, and transport also improve lives and help reduce poverty. And new information and communication technologies promote growth, improve delivery of health and other services, expand the reach of education, and support social and cultural advances. Data here are compiled from such sources as the International Road Federation, Containerisation International, the International Civil Aviation Organization, the International Energy Association, and the International Telecommunications Union.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Improving health is central to the Millennium Development Goals, and the public sector is the main provider of health care in developing countries. To reduce inequities, many countries have emphasized primary health care, including immunization, sanitation, access to safe drinking water, and safe motherhood initiatives. Data here cover health systems, disease prevention, reproductive health, nutrition, and population dynamics. Data are from the United Nations Population Division, World Health Organization, United Nations Children's Fund, the Joint United Nations Programme on HIV/AIDS, and various other sources.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. An economy's financial markets are critical to its overall development. Banking systems and stock markets enhance growth, the main factor in poverty reduction. Strong financial systems provide reliable and accessible information that lowers transaction costs, which in turn bolsters resource allocation and economic growth. Indicators here include the size and liquidity of stock markets; the accessibility, stability, and efficiency of financial systems; and international migration and workers\ remittances, which affect growth and social welfare in both sending and receiving countries.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Natural and man-made environmental resources – fresh water, clean air, forests, grasslands, marine resources, and agro-ecosystems – provide sustenance and a foundation for social and economic development. The need to safeguard these resources crosses all borders. Today, the World Bank is one of the key promoters and financiers of environmental upgrading in the developing world. Data here cover forests, biodiversity, emissions, and pollution. Other indicators relevant to the environment are found under data pages for Agriculture & Rural Development, Energy & Mining, Infrastructure, and Urban Development.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. The world economy needs ever-increasing amounts of energy to sustain economic growth, raise living standards, and reduce poverty. But today's trends in energy use are not sustainable. As the world's population grows and economies become more industrialized, nonrenewable energy sources will become scarcer and more costly. Data here on energy production, use, dependency, and efficiency are compiled by the World Bank from the International Energy Agency and the Carbon Dioxide Information Analysis Center.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Education is one of the most powerful instruments for reducing poverty and inequality and lays a foundation for sustained economic growth. The World Bank compiles data on education inputs, participation, efficiency, and outcomes. Data on education are compiled by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics from official responses to surveys and from reports provided by education authorities in each country.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Economic growth is central to economic development. When national income grows, real people benefit. While there is no known formula for stimulating economic growth, data can help policy-makers better understand their countries' economic situations and guide any work toward improvement. Data here covers measures of economic growth, such as gross domestic product (GDP) and gross national income (GNI). It also includes indicators representing factors known to be relevant to economic growth, such as capital stock, employment, investment, savings, consumption, government spending, imports, and exports.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Aid effectiveness is the impact that aid has in reducing poverty and inequality, increasing growth, building capacity, and accelerating achievement of the Millennium Development Goals set by the international community. Indicators here cover aid received as well as progress in reducing poverty and improving education, health, and other measures of human welfare.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization.

This dataset contains agency- and open source events in which aid access, education and healthcare services were impacted by explosive weapons. Categorized by country. Insecurity Insight collaborates with the International Network on Explosive Weapons (INEW) in producing research and analysis on the harm and use of explosive weapons for the Explosive Weapons Monitor by documenting their effects on health care, education, and aid access.

These document are compiled by the Information Management team in the Global Health Cluster Unit GHCU, and aims to compile the monitoring framework of the Humanitarian Response Plans in Activated Health Clusteres. The data comes from humanitarianaction For any ideas, updates, or corrections please contact Alberto Castillo Aroca castilloalb@who.int GHCU-IM Assessment and Analysis IMO or the GHC healthcluster@who.int. The data used as populations, names, and other designations are used only as a reference and do not imply any endorsement. The compilation is made by the Global Health Cluster IM team and it is expected to be updated. Not all the fields are available in the reviewed documents and it is expected to be complemented. Please see the version control table in the document

This document is compiled by the Information Management team in the Global Health Cluster Unit GHCU, and aims to gather the figures relevant to Humanitarian Health response at global levels. The information is collected from the last available data from publicly validated sources. See detailed info below. The data is mainly compiled from HRP and follows the structure of the Global Humanitarian Overview. For any ideas, updates, or corrections please contact Luis Hernando AGUILAR R aguilarl@who.int GHCU-IM team-lead or the GHC healthcluster@who.int. The data used as populations, names, and other designations are used only as a reference and do not imply any endorsement. The compilation is expected to be updated. Not all the fields are available in the reviewed documents, and it is expected to be complemented.

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 methodology is detailed in Alkire, Kanagaratnam & Suppa (2022).

oPt International Boundaries after 1967 war Admin COD datasets oPt endorsed by COD on January 2016 5 August 2021 update: small changes were made to the boundary between the Gaza Strip [PS02] and Israel affecting administrative level 2 features 'Gaza' [PS0260] and 'Rafah' [PS0275]. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. The lines shapefile includes "no man's land" boundaries (coded as admLevel 88) that are not part of the administrative level 0-2 boundaries. 19 March 2021 update: ITOS processing and live services provided. 9 November 2020 update: "No Man's Land" boundary is now included only in the lines layer, leaving the administrative level 1 and 2 features more integral. Administrative level 1 is now P-coded (maintaining compatibility with the existing administrative level 2 P-codes). ADM0: State of Palestine [PS] ADM1: Regions - West Bank [PS01] and Gaza Strip [PS02] ADM2: Governorates The 'pse_admbndl_ALL_pamop_2020' layer includes line features with Admlevel = 88 representing the border between the main parts of Jerusalem [PS0140] and Ramallah [PS0130] governorates and those parts forming "No Man's Land". These boundaries are suitable for database or GIS linkage to the State of Palestine - Subnational Population Statistics tables.

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).

The 2022 Multi-Sector Needs Assessment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA), aims to understand the multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entirety of the oPt. The 2022 MSNA was conducted through a statistically representative household survey across the entirety of the oPt. 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 Palestinian context. All surveys were conducted through face-to-face interviews, using the tablet-based Kobo Collect Open Data Kit (ODK) app where possible and paper surveys in other instances (primarily in East Jerusalem and households in Area C in close proximity to Israeli settlements or army bases) Household data collection took place from May 30 to July 06, 2022. Data collection activities were conducted by the Palestinian Central Bureau of Statistics (PCBS). A total of 8,331 households were assessed across 57 geographic strata. These strata included all localities and refugee camps in the Gaza Strip, and all governorates in the West Bank with individual strata within each governorate by Oslo Area (Areas A & B combined, Area C separate), in addition to H2 and East Jerusalem. Data is statistically representative at a 95% confidence level and a +/- 9% margin of error for all strata with a buffer of 15%. At the national level and regional level (e.g., West Bank and Gaza Strip), findings will be statistically representative at a higher level.

The 2022 Multi-Sector Needs Assessment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA), aims to identify and assess multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entirety of the Occupied Palestinian Territories (oPt). The assessment is designed to directly inform joint humanitarian-development planning across the oPt through the provision of comprehensive, multi-sectoral data and inter-sectoral analysis. In particular, the MSNA serves as a critical information resource for Humanitarian Program Cycle (HPC) activities, principally the development of the Humanitarian Needs Overview (HNO) and the Humanitarian Response Plan. All data collection activities for the MSNA were conducted by the Palestinian Central Bureau for Statistics (PCBS) and took place from May 30 to July 6. A total of 8,331 households were assessed, of which 4,152 were in the Gaza Strip and 4,179 in the West Bank, including 244 in East Jerusalem. Analysis findings at the strata level, meaning the localities of the Gaza Strip, the governorates of the West Bank according to “Oslo Area”, East Jerusalem, and H2, are statistically representative with a 95% level of confidence and a +/- 9% margin of error. Findings at the governorate level, for both the West Bank and Gaza, are representative at a higher degree of accuracy.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('kindergarten','school','college','university') OR building IN ('kindergarten','school','college','university') Features may have these attributes: amenity name operator:type addr:full building source addr:city capacity:persons 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: amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL Features may have these attributes: amenity port name operator:type addr:full building source addr:city 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: aeroway IS NOT NULL OR building = 'aerodrome' OR emergency:helipad IS NOT NULL OR emergency = 'landing_site' Features may have these attributes: emergency name operator:type emergency:helipad addr:full aeroway building source addr:city capacity:persons 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: 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: amenity addr:street name beds man_made addr:full rooms addr:housenumber source addr:city shop opening_hours tourism 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: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: covered name width natural waterway layer water source tunnel depth blockage 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: amenity IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office') Features may have these attributes: amenity operator name network addr:full source addr:city 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: amenity healthcare name operator:type addr:full building source healthcare:speciality addr:city capacity:persons 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: building IS NOT NULL Features may have these attributes: addr:street name addr:city building:materials office addr:full addr:housenumber building source building:levels This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

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.

UNOSAT code: CE20210515PSE This map illustrates a rapid satellite imagery based building damage analysis within an area of Gaza and North Gaza Governorates, Gaza Strip, Occupied Palestinian Territory based on an image collected on 20 May 2021. According to satellite imagery analysis, there are visible 23 impact craters to roads, 331 destroyed or damaged buildings, and 131 areas of possible damage on the road or road-blocking debris. According to publicly available data about 12 health care facilities and more than 40 educational facilities are located within 100 meters of damaged areas and are shown on the map. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at: https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home

This dataset is an extraction of roads from OpenStreetMap data made by WFP following UNSDI-T standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include streets and pathways that have been published on a separate dataset (streets and pathways). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download

The first Multi-Sector Needs Assesment (MSNA), conducted by REACH Initiative in close collaboration with OCHA, aims to understand the multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entirety of the Occupied Palestinian Territory (oPt). The current assessment is designed to support humanitarian actors in their development of the 2022 Humanitarian Needs Overview (HNO) and Humanitarian Response Plan (HRP), in addition to supporting humanitarian, development, and peace actors in their development and implementation of a nexus approach for the oPt.

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

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'.

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.

The dataset contains the full data collected in the field related to energy access. The assessment used the "Beyond Connection" methodology, developed by ESMAP (World Bank). The full sample is based on 210 interviews at the household level in 68 different communities within the Hebron Governorate. All the households are in Area C. As soon the data are fully analyzed, an open version will be released.

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

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

The data describes financial transactions from OCHA to their implementing partners in IRQ and oPT, and then onwards to sub-implementing partners. The data is a combination of data from OCHA GMS and data collected from OCHA implementing parters. The data from Implementing partners complement OCHA:s data with information on when funds were recieved and if/when funds were sent on to sub-implementing partners. This allows for analysis of how long and costly financial transactions are.

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, BNO News, National Health Commission of the People’s 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), and others. JHU 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 for the latest time series data are: time_series_covid19_confirmed_global.csv time_series_covid19_deaths_global.csv time_series_covid19_recovered_global.csv ---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

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. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. 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/WP00646

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. State of Palestine 1km Pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00630

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. State of Palestine 1km Births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00579

This dataset is an extraction of streets and pathways from OpenStreetMap data made by WFP that follow UNSDIT standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include main roads that have been published on a separate dataset (main roads). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

These data summarize the latest available WorldPop gridded population datasets into the administrative units of the common operational dataset (COD). Note that these data should not be considered the COD datasets for population unless endorsed by the humanitarian community in country, but rather as a starting point if no COD dataset is available, or as a point of comparison with other population datasets. These data are provided as a prototype and feedback is welcome at hdx.feedback@gmail.com