OCHA Philippines
Last updated on October 16, 2020
Interactive Data
Mindanao Displacement Dashboard Data
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  • 700+ Downloads
    Updated October 16, 2020 | Dataset date: Mar 16, 2020
    This dataset updates: As needed
    This data is about the Risk Communication and Community Engagement on COVID-19 related humanitarian activities in the Philippines.
  • 700+ Downloads
    Updated October 16, 2020 | Dataset date: Mar 25, 2020
    This dataset updates: As needed
    This data is about the humanitarian activities by civil society organizations, clusters/sectors, government, private organizations, UN agencies and Red Cross related to COVID-19.
  • 300+ Downloads
    Updated August 27, 2020 | Dataset date: Jul 10, 2019
    This dataset updates: As needed
    Based on Republic Act 8425, otherwise known as Social Reform and Poverty Alleviation Act, dated 11 December 1997, the poor refers to individuals and families whose income fall below the poverty threshold as defined by the government and/or those that cannot afford in a sustained manner to provide their basic needs of food, health, education, housing and other amenities of life. It may be estimated in terms of percentages (poverty incidence) and total number of poor families (magnitude of poor families). Also, this dataset has been generated by combining Philippine Standard Geographic Codes (PSGC) and poverty estimates from Philippine Statistics Authority (PSA). For more details, please refer to the following documents: https://psa.gov.ph/poverty-press-releases/references https://psa.gov.ph/poverty-press-releases/technotes https://psa.gov.ph/poverty-press-releases/glossary https://psa.gov.ph/sites/default/files/Technical%20Notes%20on%202015%20SAE.pdf
  • Updated June 9, 2020 | Dataset date: May 28, 2020
    This data is by request only
    Philippines COVID-19 Rapid Information, Communication, and Accountability Assessment (RICAA) for Metro Manila and Other Regions
  • 16000+ Downloads
    Updated June 5, 2020 | Dataset date: Feb 9, 2018
    This dataset updates: Every year
    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 this page. These shapefiles are suitable for database or ArcGIS joins to the sex and age disaggregated population statistics found on HDX here.
  • 5400+ Downloads
    Updated June 5, 2020 | Dataset date: Jun 5, 2020
    This dataset updates: Every year
    Sex and age disaggregated population data by various administrative levels (1 to 4) based on 2015 Census with Philippines Standard Geographic Code (PSGC). These CSV population statistics files are suitable for database or ArcGIS joins to the shapefiles found on HDX here.
  • 200+ Downloads
    Updated March 5, 2020 | Dataset date: Jan 23, 2020
    This dataset updates: As needed
    A series of earthquakes occured in provinces of Cotabato (North Cotabato) and Davao del Sur, between 16 and 31 October and December 2019, respectively. These earthquakes caused significant displacement, loss of lives and extensive damage to properties and infrastructure. This data is reflects the humanitarian activities done by the government, civil society organizations, Red Cross, and UN agencies to the affected population.
  • 12000+ Downloads
    Updated March 4, 2020 | Dataset date: Feb 12, 2019
    This dataset updates: As needed
    Who What Where of Humanitarian actors/activities in Marawi Conflict as of 9 August 2019
  • 100+ Downloads
    Updated February 11, 2020 | Dataset date: Jan 27, 2020
    This dataset updates: As needed
    This data is about the completed, ongoing and planned humanitarian activities related to the Taal volcano eruption by the government, civil society organizations, clusters, Red Cross, UN agencies and private individuals to people displaced in the evacuation centres.
  • 100+ Downloads
    Updated February 7, 2020 | Dataset date: Feb 6, 2020
    This dataset updates: As needed
    2019 Natural Disasters data on affected and displaced population
  • 60+ Downloads
    Updated January 8, 2020 | Dataset date: Jun 30, 2018
    This dataset updates: As needed
    This data refers to the cumulative number of health workers by profession and by type of facility ownership from 2010 to June 2018, based on the available data from National Database of Human Resources for Health Information System (NDHRHIS) of the Department of Health as of 30 June 2018. Data are reflective of hospitals, clinical laboratories that have self-registered in the NDHRHIS and covered 60% of licensed private and public hospitals and laboratories. Municipalities without data on public/government owned facilities does mean that there are no government-owned facilities rather that no such facilities was captured in the NDHRHIS.
  • 50+ Downloads
    Updated December 27, 2019 | Dataset date: Nov 30, 2019
    This dataset updates: Never
    This data is about the key figures of the severely affected areas on the 6.6 earthquake in Tulunan, Cotabato (North Cotabato).
  • 50+ Downloads
    Updated December 27, 2019 | Dataset date: Nov 30, 2019
    This dataset updates: As needed
    The data covers all registered Pantawid IP beneficiaries regardless of their program status. The Modified Conditional Cash Transfer Program (MCCT) is a sub-component of Pantawid Pamilyang Pilipino Program which is uses modified approach in implementing the CCT program for poor families including homeless, Indigenous People and Families in Need of Special Protection (FNSP).
  • 100+ Downloads
    Updated November 19, 2019 | Dataset date: Oct 4, 2019
    This dataset updates: As needed
    This data is about the population projections using the results of the 2015 Census of Population.
  • 50+ Downloads
    Updated November 19, 2019 | Dataset date: Jun 30, 2017
    This dataset updates: As needed
    This data is about the number of workers by major occupation category and age group.
  • 1500+ Downloads
    Updated November 10, 2019 | Dataset date: Apr 5, 2019
    This dataset updates: As needed
    Typhoon Mangkhut (Ompong) Who does What Where (3W) matrix
  • 4500+ Downloads
    Updated November 10, 2019 | Dataset date: Sep 1, 2015
    This dataset updates: Never
    This datasets contains a collection of pre-disaster indicators for the Philippines.
  • 400+ Downloads
    Updated November 10, 2019 | Dataset date: Sep 10, 2019
    This dataset updates: As needed
    Simultaneous law enforcement operations of the Armed Forces of the Philippines against non-state armed groups are reported in the provinces of Maguindanao, Lanao del Sur and Sulu since the first half of March 2019. The “Who What Where” or 3W, is vital for efficient coordination. It maintains updated information on WHO (which organizations) are doing WHAT (which activities), WHERE (in which locations) to help coordination of relief efforts to meet the immediate needs of those affected by the conflict. Such information can help to alleviate duplications, identify possible gaps, better inform decision makers, and allow everyone to ask better questions.
  • 300+ Downloads
    Updated November 10, 2019 | Dataset date: Jun 29, 2017
    This dataset updates: Never
    Number of IDPs affected by Marawi Conflict by municipality
  • 200+ Downloads
    Updated November 10, 2019 | Dataset date: Jan 11, 2018
    This dataset updates: Every month
    Tropical Storm Tembin (Vinta) Who What Where
  • 200+ Downloads
    Updated November 10, 2019 | Dataset date: Mar 1, 2019
    This dataset updates: As needed
    The data is coming from Philippines Institute of Volcanology and Seismology (DOST-PHIVOLCS). It was also available in here: https://gisweb.phivolcs.dost.gov.ph/phivolcs_hazardmaps/?fbclid=IwAR1QpGFhkVl07XTCIEMtpBOG3v4jWV05v_1QhYPNyF2_1n0NsjY3do8TiZk by region.
  • 100+ Downloads
    Updated November 10, 2019 | Dataset date: May 31, 2017-Dec 31, 2018
    This dataset updates: As needed
    Marawi Conflict IDP and returned figures by month and region from May 2017- present. Data from Task Force Bangon Marawi Regional Subcommittee on Health and Social Welfare.
  • 1400+ Downloads
    Updated November 10, 2019 | Dataset date: Nov 4, 2016
    This dataset updates: Never
    Who is doing what and where in Philippines for Typhoon Haima (Lawin)
  • 700+ Downloads
    Updated November 10, 2019 | Dataset date: Dec 16, 2014
    This dataset updates: Never
    This data is the list containing the location of FSPs consolidated by the Cash Working Group for Typhoon Haiyan Response in the Philippines 2014
  • 200+ Downloads
    Updated September 3, 2019 | Dataset date: Dec 31, 2013
    This dataset updates: Never
    Region VII - Households under the 4Ps program 2011 This data provides information on the households under the 4P (Pantawid Pamilyang Pilipino Program) - a conditional cash transfer scheme run by the government of the Philippines. All personally information on individuals has been removed. Data has been aggregated at the household level. For each household in the database, the geographic information is provided as is data on the approximate income of the the household, whether they are identified as "poor" and whether or not they are receiving 4P assistance.