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 Lebanon, 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 is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days. Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532 Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

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.

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.

The MPM (Migrant Presence Monitoring) baseline assessment is designed to systematically assess, through a series of MPM Rounds, cadastres (Admin 3 areas) in Lebanon to quantify the presence of migrants per this administrative area to support operational assistance, coordination, and planning. The data collection is based on estimations received from Key Informants (KI) who are mostly composed of Mukhtars, local authorities of these areas, and Municipality officials. The MPM relies on KIs to provide reliable information for a specific and known area. For data collection, the administrative area of a cadastre was chosen as it is the smallest administrative unit with dedicated administrative officers, and the areas are small enough to ensure that information collected on the area are reliable. As a result of the situation and arrangements of migrant populations, repeated rounds will strengthen the data collected and resultant baseline. The MPM (Migrant Presence Monitoring) baseline assessment follows the methodology of IOM’s global Displacement Tracking Matrix (DTM) Mobility Tracking component. Tailored to meet the specific operational context in Lebanon, the MPM baseline assessment gathers and analyzes data to disseminate critical multi-layered information on the presence and mobility of migrants as well as Lebanese nationals. This assessment aims to complement existing data collection exercises and it is implemented in coordination with key actors to maximize synergies, interoperability and avoid duplication

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).

More than 200 million businesses use Facebook globally. The goal of Meta’s quarterly Small Business Surveys is to learn about the unique perspectives, challenges and opportunities of small and medium-sized businesses (SMBs). The Future of Business (FoB) Survey is conducted biannually in partnership with the World Bank and the Organisation for Economic Cooperation and Development (OECD) across nearly 100 countries. The target population consists of SMEs that have an active Facebook Business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. Meta also conducts the Global State of Small Business (GSoSB) Survey bi-annually in partnership with various academic partners across approximately 30 countries. Similarly to the FoB Survey, the target population is active Facebook Page Administrators, but also includes the general population of Facebook users. Survey questions for all surveys cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, gender inequity, access to finance, digital technologies, reduction in revenues, business closures, international trade, inflation, reduction of employees and challenges/needs of the business. Aggregated country level data for each survey wave is available to the public on HDX and controlled access microdata is available to Data for Good at Meta partners. Please visit https://dataforgood.facebook.com/dfg/tools/future-of-business-survey to apply for access to microdata or contact dataforgood@fb.com for any questions.

In partnership with Yale, Meta launched a climate change opinion survey that explores public climate change knowledge, attitudes, policy preferences, and behaviors. The 2022 survey includes respondents from nearly 200 countries and territories. We are sharing country level data from this survey, providing policymakers, research institutions, and nonprofits with an international view of public climate change opinion. For more information please see https://dataforgood.facebook.com/dfg/tools/climate-change-opinion-survey If you're interested in becoming a research partner and accessing record level data, please email dataforgood@fb.com.

The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 25 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every four months, depending on seasonality). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. As the system is developed, the information collected and analyzed is being used to guide strategic decisions, to design programmes and to inform analytical processes such as the Integrated Phase Classification (IPC) and the Humanitarian Needs Overview (HNO). At the core of the system is a standardized household questionnaire administered to around 100,000 households across the 25 countries. Standardization permits comparisons across time and space, considerably enhancing the utility of the data for decision makers. At minimum the household data are representative at Admin 1 level (e.g. province, or region) and in some cases at Admin 2 level (e.g. district). Core funding for this initiative comes from the United States Agency for International Development (USAID). The initiative also benefits from support from the European Union and FAO’s Special Fund for Emergency and Rehabilitation (SFERA). The contents of the work are the sole responsibility of FAO and do not necessarily reflect the views of USAID, the United States Government or the European Union. On the Hub Homepage ( https://data-in-emergencies.fao.org/ ) it is possible to create an account and explore/download aggregated data related to the following thematic areas: 1) Incomes and shocks 2) Crop Production 3) Livestock Production 4) Food Security 5) Needs Aggregated datasets are generated from household interviews performed after August 2021. At every new survey data release, after cleaning and validation phases, aggregated data is appended to the present datasets. In each aggregated field, the values indicate the frequencies of the different responses, expressed as a weighted percentage of the total sample.

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.

NOTE: We plan to no longer update this dataset after May 22 2022. These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day. Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/

Ten years into the Syria conflict, Lebanon remains at the forefront of one of the worst humanitarian crises. The economic downturn, steep inflation, COVID-19 and finally the Beirut blast have pushed vulnerable communities in Lebanon - including Syrian refugees - to the brink, with thousands of families sinking further into poverty. The Government of Lebanon (GoL) estimates that the country hosts 1.5 million of the 6.6 million Syrians who have fled the conflict since 2011. The Syrian refugee population in Lebanon remains one of the largest concentration of refugees per capita in the world. The 2021 Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) was the ninth annual survey assessing the situation of Syrian refugees in Lebanon to identify changes and trends in their vulnerabilities. Considering the prolonged socio-economic status in Lebanon and COVID-19, it was crucial to provide needs-based estimates on Syrian refugees in the country. Since VASyR 2021 was one of the few assessments that were conducted face-to-face, the implementation was accompanied by a comprehensive protocol to ensure the safety of families and field workers. The criticality of conducting the VASyR 2021 was to provide insights about Syrian refugees impacted by the political and economic crisis that hit Lebanon in late 2019 and by the COVID-19 outbreak.

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

We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259). Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.

Since 2016, the Vulnerability Assessment of Refugees of Other Nationalities (VARON) has been a key tool for advocacy and program design. The survey aims to represent non-Syrian refugee households. For over five decades, refugees from the Middle East and Africa have sought protection in Lebanon. These include refugees from Iraq, Sudan, Ethiopia, Egypt, Yemen and other countries, many of which have been in Lebanon prior to the Syrian crisis. The compounded crisis in Lebanon, including economic deterioration and rising inflation, COVID-19 outbreak and the Beirut port blast has impacted all persons living in Lebanon, including refugees of all nationalities. The key objectives of the VARON include: • Providing a multi-sectoral update of the situation of refugees from Iraq and other countries in Lebanon through an annual household survey. The survey covers key indicators related to multiple sectors including protection, shelter, water and hygiene, health, livelihoods, socio-economic vulnerability, food security and more • Enhancing the targeting for the provision of multipurpose cash assistance. The data gathered through the VARON, particularly on expenditure, is used to build econometric models, which are used to determine eligibility for multi-purpose cash and food assistance

The assistance dataset includes the assistance history of the households that have taken the 2020 Vulnerability Assessment of Syrian Refugees (VASyR) assessment. The dataset is extracted from Refugees Assistance Information System (RAIS) which is an online Inter-Agency web application used by Lebanon Crisis Response Plan (LCRP) partners in Lebanon for tracking and reporting assistance provided to persons of concern to UNHCR.

The socio-economic desk score dataset includes the socio-economic scores of the households that have taken the 2020 Vulnerability Assessment of Syrian Refugees (VASyR) assessment. The desk score is a Proxy Means Test (PMT) score, available for all population, that predicts the economic vulnerability of households. The dataset includes the desk scores of the case numbers since 2016. In Lebanon, the desk score is revised annually and used by Lebanon Crisis Response Plan (LCRP) cash actors for the identification and selection of beneficiaries for multi-purpose cash assistance.

The Vulnerability Assessment for Syrian Refugees in Lebanon (VASyR-2018) was conducted jointly by the United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR) and the United Nations World Food Programme (WFP, dataviz.vam.wfp.org). Now in its sixth year, the Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) assesses a representative sample of Syrian refugee families to identify changes and trends in their situation. The Government of Lebanon estimates that the country hosts 1.5 million Syrian refugees who have fled their country’s conflict since 2011 (including nearly one million registered with UNHCR as of end of September 2018). The Syrian refugee population in Lebanon remains the largest concentration of refugees per capita and the fourth largest refugee population in the world. VASyR includes a sample of 4,446 Syrian refugee households from 26 districts across Lebanon. The assessment demonstrates that despite the large scale assistance and the efforts of Lebanon and its partners that have resulted in improvements in economic vulnerability and stabilization in education, food security and some improvements in the situation for women, girls and female-headed households, Syrian refugees still remain very vulnerable. The economic context remains precarious and the protection needs to persist.

Since 2016, the Vulnerability Assessment of Refugees of Other Nationalities (VARON) has been a key tool for advocacy and program design. The key objectives of the VARON include: • Providing a multi-sectoral update of the situation of refugees from Iraq and other countries in Lebanon through an annual household survey. The survey covers key indicators related to multiple sectors including protection, shelter, water and hygiene, health, livelihoods, socio-economic vulnerability, food security and more. • To enhance the targeting for the provision of multi-purpose cash assistance. The data gathered through the VARON, particularly on expenditure, is used to build econometric models, which are used to determine eligibility for multi-purpose cash and food assistance.

The Monitoring of the Effects of the Economic Deterioration on Refugee Households dataset is a Phone survey of Syrian and non-Syrian households to monitor the changes over time in key areas in the context of the deteriorating economic situation in Lebanon. This wave focuses on: livelihoods, economic vulnerability, living conditions, access to health services, food and livelihood coping strategies, covid-19. This dataset includes only the non-Syrian refugees cases.

The Monitoring of the Effects of the Economic Deterioration on Refugee Households dataset is a Phone survey of Syrian and non-Syrian households to monitor the changes over time in key areas in the context of the deteriorating economic situation in Lebanon. This wave focuses on: livelihoods, economic vulnerability, living conditions, access to health services, food and livelihood coping strategies, covid-19. This dataset includes only the Syrian refugees cases.

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.

Since the onset of the Syrian crisis, the humanitarian community has increasingly relied on cash-based assistance provided from donor contributions and implemented by aid partners under the Lebanon Crisis Response Plan to support the affected population. In November 2017, the World Food Programme (WFP) joined the United Nations High Commissioner for Refugees (UNHCR) and non-governmental organisations (NGO) in the delivery of multi-purpose cash (MPC) to assist the most economically vulnerable Syrian refugee households to meet their basic needs. This study aims to measure the short-term (12 months or less) and long-term (more than 12 months) causal impact of the $173.50 and $175 MPC assistance provided by WFP and UNHCR respectively, over and above the $27 per person per month assistance, as well as the impact of discontinuation from MPC on the well-being of Syrian refugees. This report presents the causal impact on multiple dimensions of well-being, namely household expenditures, food security, housing, water, sanitation and hygiene (WASH), education, employment, health and decision-making. The key take-away messages from the study are: 1. The impact of MPC materialised across most dimensions of well-being in the long-term, indicating the importance of households' access to a longer duration of MPC. 2. The benefits of MPC fade for many indicators within 4 to 10 months after discontinuation, and households' well-being returned to pre-assistance levels for most indicators, and dropped slightly below the pre-assistance baseline for others. 3. The findings would suggest that there are benefits to instituting longer cash cycles and/or linking MPC to other services through a 'cash plus' approach to expand and extend the positive impact of cash on beneficiary households and ensure sustainable impact. A total of 11,457 households were visited and used in this analysis, which constitutes one of the largest samples among impact evaluations conducted in Lebanon to date.

Nine years into the Syria conflict, Lebanon remains at the forefront of one of the worst humanitarian crises. The economic downturn, steep inflation, COVID-19 and finally the Beirut blast have pushed vulnerable communities in Lebanon - including Syrian refugees - to the brink, with thousands of families sinking further into poverty. The Government of Lebanon (GoL) estimates that the country hosts 1.5 million1 of the 6.6 million Syrians who have fled the conflict since 2011 (including 879,529 registered with UNHCR as of end of September 2020 ). The Syrian refugee population in Lebanon remains one of the largest concentration of refugees per capita in the world. The 2020 Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) was the eighth annual survey assessing the situation of Syrian refugees in Lebanon to identify changes and trends in their vulnerabilities. Given the COVID-19 pandemic in Lebanon, most assessments and other activities requiring in person visits were either cancelled or postponed. Considering the prolonged socio-economic status in Lebanon and COVID-19, it was crucial to provide needs-based estimates on Syrian refugees in the country. Thus, the VASyR 2020 was one of the few assessments that were conducted face-to-face; the implementation was accompanied by a comprehensive protocol to ensure the safety of families and field workers. The criticality of conducting the VASyR 2020 was to provide insights about Syrian refugees impacted by the political and economic crisis that hit Lebanon in late 2019 and by the COVID-19 outbreak.

The Vulnerability Assessment for Syrian Refugees in Lebanon (VASyR-2018) was conducted jointly by the United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR) and the United Nations World Food Programme (WFP, dataviz.vam.wfp.org). Now in its sixth year, the Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) assesses a representative sample of Syrian refugee families to identify changes and trends in their situation. The Government of Lebanon estimates that the country hosts 1.5 million Syrian refugees who have fled their country’s conflict since 2011 (including nearly one million registered with UNHCR as of end of September 2018). The Syrian refugee population in Lebanon remains the largest concentration of refugees per capita and the fourth largest refugee population in the world. VASyR includes a sample of 4,446 Syrian refugee households from 26 districts across Lebanon. The assessment demonstrates that despite the large scale assistance and the efforts of Lebanon and its partners that have resulted in improvements in economic vulnerability and stabilization in education, food security and some improvements in the situation for women, girls and female-headed households, Syrian refugees still remain very vulnerable. The economic context remains precarious and the protection needs to persist.

The Vulnerability Assessment for Syrian Refugees in Lebanon (VASyR-2019) was conducted jointly by the United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR) and the United Nations World Food Programme (WFP, dataviz.vam.wfp.org). Now in its seventh year, the Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) assesses a representative sample of Syrian refugee families to provide a multi-sectoral update of the situation and to identify changes and trends. The Government of Lebanon estimates that the country hosts 1.5 million of the 6.7 million Syrians who have fled the conflict since 2011 (including nearly one million registered with UNHCR as of end of September 2019). Survey teams visited 4,727 randomly selected Syrian refugee households, covering all districts across Lebanon. The result of the study demonstrates that while some improvements in specific indicators are noted, Syrian refugees in Lebanon continue to show heightened vulnerabilities. While rates of birth registration have seen an increase since previous years, other legal documentation issues (e.g. legal residency) remains to be an on-going challenge. About half of households are living in extreme poverty, despite large scale assistance programs to families. Additionally, while rent prices were not noted to increase dramatically, many families continue to live in substandard and over-crowded conditions across the country.

The Vulnerability Assessment for Syrian Refugees in Lebanon Arsaal, was conducted jointly by the United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR) and the United Nations World Food Programme (WFP, dataviz.vam.wfp.org). Now in its seventh year, the Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) assesses a representative sample of Syrian refugee families to identify changes and trends in their situation. The Government of Lebanon estimates that the country hosts 1.5 million of the 6.7 million Syrians who have fled the conflict since 2011 (including nearly one million registered with UNHCR as of end of September 2019). VASyR Arsaal is an addition to the 2019 VASyR, containing a representative sample of Syrian Refugee households in Arsaal.

The 2017 Vulnerability Assessment of Syrian Refugees in Lebanon (VASyR) assesses the situation of a representative sample of registered Syrian refugee households to identify situational changes and trends. With over one million registered refugees within its borders, Lebanon hosts the second-largest population of Syrian refugees in the region, and the highest per capita population of refugees in the world. Since the first assessment, the VASyR has been an essential tool for partnership and for shaping planning decisions and programme design. It is the cornerstone for support and intervention in Lebanon. A total of 4966 households were interviewed. The contents of this report, jointly issued by the United Nations High Commissioner for Refugees (UNHCR), the United Nations Childrens Fund (UNICEF) and the World Food Programme (WFP, dataviz.vam.wfp.org), demonstrate that economic vulnerability has worsened, with more than half of refugees living in extreme poverty, and that food insecurity rates are stable, but remain high.

The 2016 Vulnerability Assessment of Syrian Refugees (VASyR) surveyed a representative sample of Syrian refugee households in Lebanon to identify changes and trends in their situation. The assessment to provided valuable insight into refugees living conditions, from the size of their families to the shelter they live in, to their economic vulnerability and food insecurity. Throughout this report, refugees own viewpoints offer a crucial glimpse into the strategies they deploy to survive and their own perceptions of their situation and the assistance they receive. A total of 4596 households were surveyed. Since its inception, the VASyR has been an essential process and partnership for shaping planning decisions and programme design. It is the cornerstone for support and intervention in Lebanon. As in previous years, humanitarian agencies have incorporated VASyR findings into their programming and recommendations. The assessment, jointly issued by the United Nations High Commissioner for Refugees (UNHCR), the United Nations Children Fund (UNICEF) and the World Food Programme (WFP, dataviz.vam.wfp.org), demonstrates that economic vulnerability is, at best, as serious as previous year. Over one third of refugees are moderately to severely food insecure, an increase compared to 2015. Families have exhausted their limited resources, and are having to adapt to survive on the bare minimum. Refugees continue to rely on harmful coping mechanisms to get by.

UNHCR conducts Protection Monitoring with partners to analyze trends in the protection environment and situation of refugees in all regions of Lebanon on an ongoing basis. With the outbreak of COVID-19 in Lebanon and the introduction of movement and other restrictions aimed at preventing and containing the spread of the virus, UNHCR and its Protection Monitoring partners Caritas, Intersos and Sheild developed a specific questionnaire to elicit feedback from refugees on the impact of the COVID-19 response on their protection and well-being. The feedback from refugees is used to inform advocacy and programmatic interventions and modes of implementation with the aim of improving refugees' access to protection and essential services, assistance and information.

The Monitoring of the Effects of the Economic Deterioration on Refugee Households dataset is a Phone survey of Syrian and non-Syrian households to monitor the changes over time in key areas in the context of the deteriorating economic situation in Lebanon.The UNHCR call center was used to conduct the two waves of data collection: 20-28 February (Wave I) and 17 April-15 May (Wave II). Several call attempts were made at different times of the day to reach the largest possible number of households. After the Wave I of the survey, which was collected before the first case of Covid 19 was reported in Lebanon, the Wave II was conducted to account for the impacts of the spread of the Covid 19 virus on refugees, the level of awarness among them and their accessibility to hygiene items and health care services. This dataset includes only Wave1 fot the non-Syrian refugees cases.

The Monitoring of the Effects of the Economic Deterioration on Refugee Households dataset is a Phone survey of Syrian and non-Syrian households to monitor the changes over time in key areas in the context of the deteriorating economic situation in Lebanon.The UNHCR call center was used to conduct the two waves of data collection: 20-28 February (Wave I) and 17 April-15 May (Wave II). Several call attempts were made at different times of the day to reach the largest possible number of households. After the Wave I of the survey, which was collected before the first case of Covid 19 was reported in Lebanon, the Wave II was conducted to account for the impacts of the spread of the Covid 19 virus on refugees, the level of awarness among them and their accessibility to hygiene items and health care services. This dataset includes only the Syrian refugees cases.

The Monitoring of the Effects of the Economic Deterioration on Refugee Households dataset is a Phone survey of Syrian and non-Syrian households to monitor the changes over time in key areas in the context of the deteriorating economic situation in Lebanon.The UNHCR call center was used to conduct the two waves of data collection: 20-28 February (Wave I) and 17 April-15 May (Wave II). Several call attempts were made at different times of the day to reach the largest possible number of households. After the Wave I of the survey, which was collected before the first case of Covid 19 was reported in Lebanon, the Wave II was conducted to account for the impacts of the spread of the Covid 19 virus on refugees, the level of awarness among them and their accessibility to hygiene items and health care services. This dataset includes only Wave1 fot the non-Syrian refugees cases.

The Monitoring of the Effects of the Economic Deterioration on Refugee Households dataset is a Phone survey of Syrian and non-Syrian households to monitor the changes over time in key areas in the context of the deteriorating economic situation in Lebanon.The UNHCR call center was used to conduct the two waves of data collection: 20-28 February (Wave I) and 17 April-15 May (Wave II). Several call attempts were made at different times of the day to reach the largest possible number of households. After the Wave I of the survey, which was collected before the first case of Covid 19 was reported in Lebanon, the Wave II was conducted to account for the impacts of the spread of the Covid 19 virus on refugees, the level of awarness among them and their accessibility to hygiene items and health care services. This dataset includes only the non-Syrian refugees cases.

Since 2016, the Vulnerability Assessment of Refugees of Other Nationalities (VARON) has been a key tool for advocacy and program design. The key objectives of the VARON include: • Providing a multi-sectoral update of the situation of refugees from Iraq and other countries in Lebanon through an annual household survey. The survey covers key indicators related to multiple sectors including protection, shelter, water and hygiene, health, livelihoods, socio-economic vulnerability, food security and more. • To enhance the targeting for the provision of multi-purpose cash assistance. The data gathered through the VARON, particularly on expenditure, is used to build econometric models, which are used to determine eligibility for multi-purpose cash and food assistance.

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

Beirut port explosion operational zones UPDATED 9 October 2020: Enlarged zones with UN HABITAT socio-economic classification and the 3Km priority of the Flash Appeal priority radius added. Please see the methodology section in the metadata for further information. UPDATED 19 August 2020: 11 operational zones numbered 129 to 139 inclusive added to the Sinn El-Fil cadastre south of the origional set. Zones spreadsheet added. NOTES Users are referred to the compatible Beirut buildings footprints COD. The standard Administrative Boundary Common Operational Dataset (COD-AB) can be found at Lebanon - Subnational Administrative Boundaries.

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

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

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. Lebanon 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/WP00616

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. Lebanon 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/WP00565

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

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

UNOSAT code: FR20191016LBN This map illustrates satellite-detected fire hotspots based on the analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) accessed via NASA FIRMS, between October 15-16, 2019. 30 hotspots were detected in Lebanon and 121 hotspots were detected in three analysed Governorates (i.e. Homs, Lattakia and Tartous) in Syria. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in Al-Haffa and Al-Qardaha Districts, Lattakia Governorate, Syria, based on SPOT-6 imagery acquired on 21 October 2019. Approximately 433 ha of potentially burned areas were detected by UNOSAT as of 21 October 2019 (red). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in Akkar, Tartous and Homs Governorates, in Lebanon and Syria, based on SPOT-6 imagery acquired on 21 October 2019. Approximately 549 ha of potentially burned areas were detected by UNOSAT as of 21 October 2019 (red). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in Aley and Chouf districts, in Lebanon, based on SPOT-6 imagery acquired on 19 October 2019. Approximately 1275 ha of potentially burned areas were detected by Copernicus-EMS as of 17 October 2019 (orange) and additional 92 ha of burned were detected by UNOSAT as of 19 October 2019 (red), which is equivalent to approximately 7% increase in affected surface area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

UNOSAT code: FR20191016LBN This map illustrates satellite-detected burned areas in South and El Nabatieh Governorates, in Lebanon, based on SPOT-6 imagery acquired on 19 October 2019. Approximately 80 ha of potentially burned area were detected by UNOSAT as of 19 October 2019 (red), This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

The study conducted in partnership with IMMAP and funded by the Australian Government includes a literature review, quantitative data collection as well as data collection. Quantitative data was collected from 8,876 persons from 1,665 households from 5 locations in Jordan and Lebanon. In the light of the UN Convention on the Rights of Persons with Disabilities (UNCRPD), the study defined disability as interactions between personal and environmental factors. Disability was measured the level of difficulties a person faces when performing basic activities (referred as "domains") regardless of impairments, using the modified Washington Group's Extended Set (WG-ES) (more precisely, Short Set Enhanced plus fatigue) and Child Functioning Module (CFM).

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.

This dataset presents a list of Localities in Lebanon for the use of humanitarian actors. Central Administration of Statistics. The official governmental institutions for statistics. Cadastral Boundaries: Represent the geographic divisions of Lebanon as per the government. In total Lebanon holds 1623 Cadastral Boundaries. Each boundary could includes 1 or more villages or municipalities; or 1 or more cadastral boundaries could represent one municipality. P_code This column illustrates the agreed codes of the villages in Lebanon as per the UNICEF and UNHCR IM joint work. Location_Name_En This column illustrates the agreed names of the villages in Lebanon as per the UNICEF and UNHCR IM joint work. Location_Name_Arabic This column illustrates the name of the location in arabic based on the "Real estate areas , cities and villages in Lebanon guide" in 2005 from the ACS for the most of the location Latitude, Longitude Geographical Coordinates in Decimal Degrees. Geographical Projection WGS 1984. Elevation This column has the elevation of the location GPS coordinates. Google Webservices was used to populate this field using location GPS coordinates Governorate This column illustrates the Mohafazas (Governorates) as per the Lebanese Government divisions. In total, the no. of Mohafazas is 8. as per decree "522 dated 16/7/2003", in English Governorate_Ar This column illustrates the Mohafazas (Governorates) as per the Lebanese Government divisions. In total, the no. of Mohafazas is 8. as per decree "522 dated 16/7/2003", in Arabic UN_Area Of Operation This column illustrates the Mohafazas (Governorates) in Lebanon as per UNHCR operation areas. Noting that Nabatiyeh and South Lebanon Mohafazas were merged into one Mohafaza that is "South"also for Bekaa and Baalbek-El Hermel Mohafazas were merged into one Mohafaza that is "Bekaa" In total, the no. of Mohafazas as per UNHCR is 5.in English UN_AreaOfOperation_Ar This column illustrates the Mohafazas (Governorates) in Lebanon as per UNHCR divisions. Noting that Nabatiyeh and South Lebanon Mohafazas were merged into one Mohafaza that is "South"also for Bekaa and Baalbek-El Hermel Mohafazas were merged into one Mohafaza that is "Bekaa" In total, the no. of Mohafazas as per UNHCR is 5.in Arabic District This column illustrates the cazas (Districts) in Lebanon as per Lebanese Government divisions. In total, the no. of Cazas amounts for 26. District_Ar This column illustrates the cazas (Districts) in Lebanon as per Lebanese Government divisions. In total, the no. of Cazas amounts for 26. in Arabic CAS_CODE This column illustrates the agreed codes of the cadastral boundaries* in Lebanon as per the Lebanese Government. CAS_CODE_UN This column illustrates the agreed codes of the cadastral boundaries in Lebanon as per the Lebanese Government. The codes holds in its beginning the Lebanese acronyme LBN for international use. CAS_NAME This column illustrates the names of the cadastral boundaries in Lebanon as per the Lebanese Government in English. CAS_NAME_Ar This column illustrates the names of the cadastral boundaries in Lebanon as per the Lebanese Government in Arabic. CAS_MaxElevation This column has the elevation of the highest village in the same cadastral zone Municipality Name_EN This column illustrates the names of the Municipalities in Lebanon in English. Data Source: UNHCR Municipality Name_AR This column illustrates the names of the Municipalities in Lebanon in Arabic. Data Source: UNHCR Municipality Phone This column illustrates the Phone number of the Municipalities in Lebanon. Data Source: MoIM website Municipality Address This column illustrates the Available Address of the Municipalities in Lebanon. Data Source: UNDP/Arabia GIS UNION_ID This column illustrates the codes given for to the union of Municipalities in Lebanon. Data Source: UNHABITAT Union_Full This column illustrates the names of the union of Municipalities in Lebanon in English. Data Source: UNHABITAT UOM_Name This column illustrates the abbreviation name of the union of Municipalities in Lebanon in English. Data Source: UNHABITAT

This is the underlying data for a manuscript published in PLOS: Currents Disasters (see PDF provided). the manuscript reports results from longitudinal cohort study implemented from January 2015 through August 2016 that sought to evaluate the effectiveness of treatment guidelines and an mHealth application on quality of care and health outcomes for patients with hypertension and type 2 diabetes in primary health care facilities in Lebanon serving Syrian refugees and host communities.