Updated
15 April 2021
| Dataset date: March 01, 2020-December 31, 2020
This dataset updates: Every three months
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.
Updated
4 March 2021
| Dataset date: November 20, 2020-November 20, 2020
This dataset updates: As needed
Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.
Updated
7 February 2021
| Dataset date: February 01, 2019-March 31, 2020
This dataset updates: Never
The size of the outflows from Venezuela sharply increased from some 700,000 in 2015 to over 4 million by June 2019, largely driven by a substantial deterioration of the situation in the country. Given the disruption of the functioning of some democratic institutions and rule of law, and its impact on the preservation of security, economic stability, health, public peace and the general welfare system, the crisis continues to worsen and serious human rights violations are widely reported. The displacement outside Venezuela has mostly affected countries in Latin America and the Caribbean, particularly Argentina, Brazil, Chile, Colombia, Ecuador, Peru, and the southern Caribbean islands. Most governments in the region have made efforts to facilitate access to territory, documentation and access to services, but the capacity of host countries has become overstretched to address the increasing protection and integration needs, resulting in tighter border controls being put in place. Protection monitoring is a core UNHCR activity which aims at ensuring an adequate and timely understanding of the protection situation of persons affected by forced displacement. The action-oriented nature of protection monitoring allows UNHCR to adapt to the needs and protection risks faced by persons displaced outside Venezuela and informs a broad range of responses.
Updated
24 November 2020
| Dataset date: January 01, 2000-December 31, 2020
This dataset updates: Every year
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
Updated
24 November 2020
| Dataset date: January 01, 2000-December 31, 2020
This dataset updates: Every year
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
Updated
Live
| Dataset date: January 22, 2020-June 27, 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 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
Updated
27 July 2020
| Dataset date: October 11, 2017-June 29, 2022
This dataset updates: Every year
Uruguay administrative level 0 (country), 1 (department, departamento), and 2 (poblacion, población) boundaries.
These boundaries are suitable for database or GIS linkage to the Uruguay - Subnational Population Statistics tables.
Updated
22 July 2020
| Dataset date: June 17, 2020-June 29, 2022
This dataset updates: Every year
Uruguay administrative level 0-1 projected 2020 sex and age disaggregated population statistics
REFERENCE YEAR: 2020
These tables are suitable for database or GIS linkage to the Uruguay - Subnational Administrative Boundaries.
Updated
14 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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:
population
name
place
source
is_in
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
14 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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:
name
network
amenity
addr:full
addr:city
operator
source
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
14 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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
name
building
amenity
addr:full
addr:city
source
capacity:persons
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
14 July 2020
| Dataset date: March 05, 2021-March 05, 2021
This dataset updates: Every month
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:
operator:type
name
building
addr:full
addr:city
emergency
aeroway
source
emergency:helipad
capacity:persons
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
14 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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
healthcare
name
healthcare:speciality
building
amenity
addr:full
addr:city
source
capacity:persons
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
14 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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','subway','station')
Features may have these attributes:
operator:type
layer
name
source
addr:full
addr:city
railway
ele
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
10 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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:materials
addr:housenumber
name
building:levels
building
addr:street
addr:full
addr:city
office
source
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
10 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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:
layer
name
smoothness
bridge
highway
width
oneway
surface
source
lanes
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
8 July 2020
| Dataset date: March 05, 2021-March 05, 2021
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:
layer
name
blockage
natural
width
tunnel
depth
covered
water
source
waterway
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
29 June 2020
| Dataset date: January 01, 2000-December 31, 2020
This dataset updates: Every year
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
Updated
29 June 2020
| Dataset date: January 01, 2017-December 31, 2017
This dataset updates: Every year
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). 2017. Uruguay 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/WP00474
Updated
29 June 2020
| Dataset date: January 01, 2017-December 31, 2017
This dataset updates: Every year
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). 2017. Uruguay 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/WP00366
Updated
2 June 2020
| Dataset date: March 05, 2021-March 05, 2021
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:
addr:housenumber
tourism
name
rooms
beds
addr:street
amenity
man_made
addr:full
shop
addr:city
source
opening_hours
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
2 June 2020
| Dataset date: March 05, 2021-March 05, 2021
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
name
building
amenity
addr:full
addr:city
port
source
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
11 June 2019
| Dataset date: June 10, 2019-June 10, 2019
This dataset updates: As needed
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Uruguay: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
Updated
28 September 2018
| Dataset date: January 01, 1950-December 31, 2050
This dataset updates: Every year
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.
