Philippines

  • Updated 19 June 2022 | Dataset date: January 01, 2008-December 31, 2021
    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.
    2100+ Downloads
    This dataset updates: Every year
  • Updated 31 May 2022 | Dataset date: March 01, 2020-May 22, 2022
    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/
    48000+ Downloads
    This dataset updates: As needed
  • Updated 24 May 2022 | Dataset date: September 01, 2016-April 01, 2018
    More than 200 million businesses use Facebook. Meta partners with various academic and international organizations to survey these businesses throughout the year to learn about their perspectives, challenges and opportunities. With more businesses leveraging online tools each day, these surveys provide a lens into a new mobilized and digital economy. The Future of Business Survey (FoBS) is a collaboration between Meta, the OECD and the World Bank to provide timely insights on the perceptions, challenges, and outlook of online Small and Medium Enterprises or Businesses (SMEs/SMBs). 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. The Future of Business Survey was first launched as a monthly survey in 17 countries in February 2016 and expanded to 42 countries in 2018. In 2019, the Future of Business survey increased coverage to 97 countries and moved to a bi-annual cadence. In 2020, the Future of Business Survey shifted to do additional monthly waves with questions focused on business challenges related to COVID-19. Meta also shares information from other SMB surveys, such as those that feed into the Global State of Small Business Reports, which are fielded to active Facebook Page Administrators and the general population of Facebook users. These surveys are conducted in approximately 30 countries across the globe and are also conducted on a roughly bi-annual basis. 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, reduction of employees and challenges/needs of the business. Aggregated country level data is available to the public here for each wave and controlled access microdata is available to Data for Good partners. To request access to survey microdata or to see published Meta reports, please visit: futureofbusinesssurvey.org Update 12/12/21: We have transitioned all small business survey datasets to have survey weights applied. Files with weighted estimates have now replaced the previously posted unweighted estimates. Update 10/4/21: Aggregate data in files [gsosb_2021julyaugust_data_aggregate_weighted.csv] and [gsosb_2021february_data_aggregate_weighted.csv] have been updated to provide weighted results and to correct an error found in those two files. These files were discovered to present results for large businesses rather than small and medium businesses and have been updated to provide the information for the latter group. Downloads of these two files that took place between April 1 and September 30 2021 were affected and analysis using downloads from this period may need to be amended. No analyses or reports published by Facebook were affected. Please contact dataforgood@fb.com for any questions.
    15000+ Downloads
    This dataset updates: As needed
  • Updated 3 May 2022 | Dataset date: January 01, 2016-January 31, 2021
    A dataset containing confirmed dengue cases and deaths from the Department of Health-Epidemiology Bureau in the Philippines. Notes: Reported dengue cases includes suspect, probable and confirmed. Deaths were included in the total number of cases.
    1700+ Downloads
    This dataset updates: As needed
  • Updated 2 May 2022 | Dataset date: October 23, 2021-October 23, 2021
    This project is a portmanteau of OSM + Map + Paaralan - to collaboratively map public schools (paaralan) in the Philippines, on OpenStreetMap. Documentation available at https://wiki.openstreetmap.org/wiki/Philippines/OSMaPaaralan
    40+ Downloads
    This dataset updates: As needed
  • Updated Live | Dataset date: January 18, 2020-September 26, 2022
    'Our World in Data' is compiling COVID-19 testing data over time for many countries around the world. They are adding further data in the coming days as more details become available for other countries. In some cases figures refer to the number of tests, in other cases to the number of individuals who have been tested. Refer to documentation provided here.
    22000+ Downloads
    This dataset updates: Live
  • Updated 14 April 2022 | Dataset date: April 07, 2022-April 07, 2022
    Philippines administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata. Gobal version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
    40+ Downloads
    This dataset updates: As needed
  • Updated 22 March 2022 | Dataset date: January 01, 2020-February 28, 2022
    These datasets comprise publicly reported cases of sexual violence by law enforcement bodies, conflict related sexual violence, and sexual violence that targets IDPs / refugees or vulnerable beneficiaries from information available in local, national and international news outlets and online databases. Dataset for South Sudan currently available. Other datasets covering the DRC, Ethiopia, Nigeria and South Sudan will soon be available.
    400+ Downloads
    This dataset updates: As needed
  • Updated 15 March 2022 | Dataset date: September 30, 2021-September 30, 2021
    This dataset shows the number of people in need(PiN), funds required and funds received by country and over the years, from 2010 to 2021. PIN figures for 2022 are available in this dataset: Interagency Response Plans in 2022
    700+ Downloads
    This dataset updates: Every year
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in Jimalalud and La Libertad municipalities, Negros Oriental province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 22 December 2021. Within the analyzed area, UNOSAT identified 566 damaged structures and 154 potentially damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in City of Carcar and San Fernando municipalities, Cebu province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 23 December 2021 & a GeoEye-1 image acquired on 20 December 2021. Within the analyzed area, UNOSAT identified 1929 damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures/buildings in Roxas town, Palawan province, Region IV-B (Mimaropa) of Philippines as observed from a Pleiades image acquired on 21 December 2021 after landfall of the Tropical Cyclone RAI-21. Within the analysis extent, UNITAR-UNOSAT identified 280 damaged structures and 265 potentially damaged structures including Roxas Medicare Hospital and 6 potentially damaged education facilities. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures/buildings in Bucas Grande Island, Socorro, Surigao del Norte of Philippines as detected by WorldView-3 image acquired on 17 December 2021. Within the analyzed area, UNOSAT has identified 351 damaged structures, 129 potentially damaged structures, 5 road obstacles and 1 destroyed bridge. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in City of Talisay, Cebu province, Region VII (Central Visayas), Philippines as observed from a GeoEye-1 image acquired on 20 December 2021 & a Pleiades image acquired on 21 December 2021. Within the analyzed area, UNOSAT identified 483 damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures/buildings in Siargao Island, General Luna, Surigao del Norte of Philippines as detected by Pleiades image acquired on 26 December 2021 and WorldView-3 acquired on 23 December 2021. Within the analyzed area, UNOSAT has identified 1,769 damaged structures, 380 potentially damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL A category 5 Tropical Cyclone RAI-21 struck the Philippines on the 16th of December 2021, causing damage, devastation, and destruction. The Tropical Cyclone RAI-21 made landfall north of General Luna city on Siargao Island, the easternmost island of the Philippines, and continued westward through the central part of the country. The Philippines National Disaster Risk Reduction and Management Council (NDRRMC) has stated that 2,182,791 families have been affected in 11 out of 17 regions of the Philippines. About 3M people, ~ 30% of the affected area population – need emergency humanitarian assistance. According to OCHA, the death toll has reached 177 persons, with more than 275 persons injured and 630,000 displaced. More than 159,000 houses have been damaged, 61,900 have been destroyed. These figures are likely to rise as the after-effects of the Tropical Cyclone are fully realized. Preliminary assessment has shown devastating damage to houses, roads, and bridges disrupting aid movement into the affected areas. This report summarizes satellite-derived building damage analysis covering the most affected areas within Region IV-B (Mimaropa), Region VII (Central Visayas), Region VIII (Eastern Visayas), and Region XIII (Caraga) of the Philippines.
    10+ Downloads
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in Dinagat Island, Region XIII, the Philippines as observed from a Pleiades image acquired on 23 December 2021. Within the analyzed area, UNOSAT and Copernicus EMS identified 3,278 damaged structures, 523 potentially damaged structures, and 3 potentially damaged ports. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in City of Naga & Minglanilla municipalities, Cebu province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 21 December 2021. Within the analyzed area, UNOSAT identified 876 damaged structures and 1,361 potentially damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in Talibon municipality, Bohol province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 23 December 2021. Within the analyzed area, UNOSAT identified 3,103 damaged structures and 933 potentially damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in Bien Unido, Trinidad and Ubay municipalities, Bohol province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 23 December 2021. Within the analyzed area, UNOSAT identified 2,225 damaged structures and 888 potentially damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20211216PHL This map illustrates potentially damaged structures and buildings in ubay municipality, Bohol province, Region VII (Central Visayas), Philippines as observed from a Pleiades image acquired on 23 December 2021. Within the analyzed area, UNOSAT identified 1,751 damaged structures and 220 potentially damaged structures. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
    This dataset updates: Never
  • Updated 15 February 2022 | Dataset date: January 01, 2017-December 31, 2021
    This page provides the data published in the Education in Danger Monthly News Brief. All data contains incidents identified in open sources. Categorized by country and with link to the relevant Monthly News Brief (where possible).
    6200+ Downloads
    This dataset updates: As needed
  • Updated 11 February 2022 | Dataset date: April 01, 2021-September 28, 2022
    The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following: Microestimates of wealth for all low- and middle-income countries Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119 More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119 Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
    18000+ Downloads
    This dataset updates: As needed
  • Updated 14 January 2022 | Dataset date: September 21, 2020-September 21, 2020
    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
    3700+ Downloads
    This dataset updates: Every year
  • Updated 24 December 2021 | Dataset date: February 09, 2018-September 28, 2022
    Philippines administrative levels: (0) Country (1) Region (Filipino: rehiyon) (2) Provinces (Filipino: lalawigan, probinsiya) and independent cities (Filipino: lungsod, siyudad/ciudad, dakbayan, lakanbalen) (3) Municipalities (Filipino: bayan, balen, bungto, banwa, ili) and component cities (Filipino: lungsod, siyudad/ciudad, dakbayan, dakbanwa, lakanbalen) The original datasets were derived from the boundaries of the Barangays as observed at the end of April 2016 as per the Philippine Geographic Standard Code (PSGC) dataset. It has been generated on the basis of the layer created by the Philippine Statistics Authority (PSA) in the context of the 2015 population census. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. OCHA acknowledges PSA and the National Mapping and Resource Information Authority (NAMRIA) as the sources. LMB is the source of official administrative boundaries of the Philippines. In the absence of available official administrative boundary, the IMTWG have agreed to clean and use the PSA administrative boundaries which are used to facilitate data collection of surveys and censuses. The dataset can only be considered as indicative boundaries and not official. For administrative level 4 (Barangay) please contact the contributor (OCHA Philippines) via the 'Contact the contributor' button near the top of this page. These shapefiles are suitable for database or ArcGIS joins to the Philippines - Subnational Population Statistics.
    31000+ Downloads
    This dataset updates: Every year