{"geometry": {"type": "MultiPolygon", "coordinates": [[[[126.01749, 9.26583], [126.29109, 8.97416], [126.36256, 7.90386], [126.55887, 7.19944], [126.07666, 6.84361], [125.651520000000119, 7.23458], [125.39861, 6.80305], [125.70276, 6.025], [125.40555, 5.56333], [125.17693, 5.83583], [124.32416, 6.11458], [124.04221, 6.43167], [123.99304, 7.02389], [124.2661, 7.36305], [123.676650000000109, 7.8125], [123.228880000000117, 7.5343], [122.78027, 7.47139], [122.54776, 7.73028], [122.18664, 6.95014], [121.89694, 7.07722], [122.351090000000113, 8.03861], [122.990950000000112, 8.20166], [123.06388, 8.5168], [123.43414, 8.71736], [124.22401, 8.2125], [124.77332, 8.97014], [125.07387, 8.82889], [125.53777, 9.06472], [125.3911, 9.64972], [125.922150000000101, 9.48726], [126.01749, 9.26583 ] ]], [[ [ 124.46721, 10.05833], [124.35721, 9.62361], [123.86123, 9.63528], [124.15249, 10.14805], [124.46721, 10.05833 ] ]], [[ [ 123.35206, 9.41673], [123.374, 9.99069], [123.863880000000108, 10.81278], [124.01999, 10.38701], [123.63651, 10.06986], [123.35206, 9.41673 ] ]], [[ [ 123.20638, 9.98389], [123.296380000000113, 9.22972], [122.541650000000118, 9.48375], [122.45388, 9.97486], [122.85694, 10.09514], [122.95247, 10.89444], [123.56387, 10.79416], [123.20638, 9.98389 ] ]], [[ [ 119.562364574000071, 11.259262386000046], [119.496444594000081, 10.990089133000026], [119.4840200000001, 10.8793], [119.71585, 10.51094], [119.20194, 10.04847], [118.75333, 9.925], [118.73226000000011, 9.65389], [117.99891, 8.87746], [117.45166, 8.5025], [117.34444, 8.72611], [118.02721, 9.25916], [119.34119, 10.7201], [119.419537950000063, 11.028542454000046], [119.419537950000063, 11.303209039000023], [119.562364574000071, 11.259262386000046 ] ]], [[ [ 124.581730000000107, 11.30958], [124.95026, 11.42173], [125.01506, 10.7434], [125.25908, 10.26305], [124.76471, 10.19639], [124.804850000000101, 10.66125], [124.581730000000107, 11.30958 ] ]], [[ [ 122.22943, 11.79778], [122.90692, 11.4318], [123.12359, 11.16569], [122.72916, 10.80083], [121.90984, 10.44458], [122.22943, 11.79778 ] ]], [[ [ 125.17831, 12.56111], [125.50471, 12.205], [125.45027, 11.59027], [125.04207, 11.72791], [124.393600000000106, 12.18833], [124.25776, 12.55111], [125.17831, 12.56111 ] ]], [[ [ 120.72165, 13.47778], [120.96748, 13.52305], [121.50222, 13.14889], [121.5579, 12.60146], [121.12317, 12.245], [120.80172, 12.72493], [120.72165, 13.47778 ] ]], [[ [ 121.25665, 18.56611], [121.9497, 18.26889], [122.2572100000001, 17.36347], [122.53304, 17.10139], [122.309710000000109, 16.56361], [121.37637, 15.315], [121.73553, 14.16847], [122.246940000000109, 13.92305], [122.47331, 14.34055], [123.41776, 13.98222], [123.86844, 13.135], [123.40901, 13.04417], [123.20151, 13.41798], [122.56099, 13.93657], [122.10859, 13.76389], [121.70193, 13.95916], [121.27943, 13.59389], [120.71666, 13.92528], [120.59221, 14.23111], [120.99109, 14.54917], [120.08735, 14.78347], [119.91304, 15.84069], [120.42609, 16.16912], [120.3172, 16.63111], [120.44915, 16.96861], [120.43997, 17.73249], [120.57278, 18.46805], [121.25665, 18.56611]]]]}, "type": "Feature", "properties": {"url": "/group/phl", "name": "Philippines"}, "id": "PHL"}
237
-
Updated
Live
| Dataset date: January 22, 2020-August 15, 2022
This dataset updates: Live
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 Peopleโs 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
-
10+ Downloads
Updated
7 February 2021
| Dataset date: June 04, 2018-June 14, 2018
This dataset updates: Never
This report presents the findings of the profiling activities conducted from June to August 2018 in communities hosting internally displaced persons (IDPs) of the Marawi conflict and return communities in the provinces of Lanao del Sur, Lanao del Norte, Misamis Oriental and Bukidnon. Data was collected through structured interviews with IDP households using the koboโข tool. Primary respondents were heads of households and in their absence, any person of legal age in the family. A total of 34,785 heads of households were interviewed in the profiling activity, representing 97,126 IDPs in 56 municipalities and 3 cities.
This report presents data on demographic makeup of the IDPs such as age, sex, number of households, and family size, as well as protection information relating to displacement location, place of origin, resettlement, integration; various vulnerabilities of persons with special needs; educational attainment; income livelihood and skills; access to assistance; access to information; civil documentation; property ownership; intent to return; access to information, assistance received, and sources of assistance. Special focus is given on children and women in separate sections of this report.
A significant number of IDPs continue to experience gaps in assistance related to health, education, shelter and long-term livelihood support. Also, IDPs continue to experience protection risks due to lack of civil documentation due to loss or destruction of birth certificates. A more nuanced and targeted approach that will address specific protection needs of IDPs is needed.
-
Updated
7 February 2021
| Dataset date: July 01, 2016-August 31, 2016
This dataset updates: Never
In April 2016, following a series of consultations between the United Nations High Commissioner for Refugees, the City Social Welfare and Development Office and other partners in Zamboanga, a profiling exercise for home-based internally displaced persons (IDPs) was conceptualized. The main purpose was to validate the relevance of existing lists and obtain up-to-date information from home-based IDPs who decided to take part in the exercise so that the government, as well as other humanitarian and development actors, can make informed and consultative decisions while designing and targeting their assistance programs, including protection interventions.
Following a piloting phase in June 2016, the full-blown profiling was conducted in July-August 2016 and reached 6,474 families from 66 barangays in Zamboanga. Of these, 1,135 families were assessed to be potential home-based IDPs based on the documents they presented. The profiling revealed that most home-based IDPs are living in barangays of Sta. Catalina, Sta. Barbara, Talon-Talon and Rio Hondo.
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Updated
16 August 2022
| Dataset date: August 16, 2022-August 16, 2022
This dataset updates: Every day
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.
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31000+ Downloads
Updated
24 December 2021
| Dataset date: February 09, 2018-August 16, 2022
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 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.
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100+ Downloads
Updated
16 August 2022
| Dataset date: July 30, 2022-August 16, 2022
This dataset updates: Every six months
This document is compiled by the Information Management team in the Global Health Cluster Unit GHCU, and aims to compile the figures relevant to Humanitarian Health response at global levels. The information is compiled from the last available data in public validated sources. See detailed info below. The data is mostly 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. 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
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Updated
15 August 2022
| Dataset date: January 01, 1961-December 31, 2019
This dataset updates: Every month
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, 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
For links to individual indicator metadata, see resource descriptions.
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22000+ Downloads
Updated
Live
| Dataset date: January 18, 2020-August 14, 2022
This dataset updates: Live
'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.
-
Updated
14 August 2022
| Dataset date: January 01, 1991-December 31, 2021
This dataset updates: Every year
Prices for Philippines.
Contains data from the FAOSTAT bulk data service covering the following categories: Consumer Price Indices, Deflators, Exchange rates, Producer Prices
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Updated
14 August 2022
| Dataset date: January 15, 2000-March 15, 2022
This dataset updates: Every week
This dataset contains Food Prices data for Philippines, 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.
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400+ Downloads
Updated
10 August 2022
| Dataset date: January 01, 2016-August 05, 2022
This dataset updates: Every week
A weekly dataset providing the total number of reported political violence, civilian-targeting, and demonstration events in Philippines. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.
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Updated
3 August 2022
| Dataset date: January 01, 1989-December 29, 2021
This dataset updates: Every month
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, โIntroducing the UCDP Georeferenced Event Datasetโ, Journal of Peace Research, vol.50, no.4, 523-532
Hรถgbladh Stina, 2019, โUCDP GED Codebook version 19.1โ, Department of Peace and Conflict Research, Uppsala University
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8500+ Downloads
Updated
2 August 2022
| Dataset date: June 05, 2020-August 16, 2022
This dataset updates: Every year
Philippines administrative level 0-2 sex and age disaggregated 2022, 2023, 2024, and 2025 population statistics
REFERENCE YEAR: 2022 (and 2023, 2024, 2025)
These CSV population statistics files are suitable for database or ArcGIS joins to the Philippines - Subnational Administrative Boundaries.
See caveats.
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Updated
Live
| Dataset date: January 01, 2017-August 16, 2022
This dataset updates: Live
Projects proposed, in progress, or completed as part of the annual Philippines Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on
https://hpc.tools
Note that some projects are not publicly listed, due to security or personal-privacy concerns.
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Updated
Live
| Dataset date: December 14, 2020-August 02, 2022
This dataset updates: Live
Immunization campaigns impacted due to COVID-19
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200+ Downloads
Updated
3 August 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
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.
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100+ Downloads
Updated
4 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
place IN ('isolated_dwelling','town','village','hamlet','city')
Features may have these attributes:
name
is_in
place
source
population
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
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100+ Downloads
Updated
4 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
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.
-
100+ Downloads
Updated
11 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL
Features may have these attributes:
beds
tourism
addr:housenumber
source
name
amenity
man_made
rooms
addr:street
shop
addr:full
opening_hours
addr:city
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
400+ Downloads
Updated
12 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
highway IS NOT NULL
Features may have these attributes:
highway
surface
name
smoothness
lanes
width
source
layer
oneway
bridge
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
70+ Downloads
Updated
4 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
railway IN ('rail','station')
Features may have these attributes:
operator:type
source
railway
name
ele
addr:full
addr:city
layer
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
-
100+ Downloads
Updated
4 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
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.
-
300+ Downloads
Updated
12 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
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.
-
60+ Downloads
Updated
4 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
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.
-
100+ Downloads
Updated
4 July 2020
| Dataset date: August 01, 2022-August 01, 2022
This dataset updates: Every month
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.