3 datasets found
  1. Z

    COVID19 Flow-Maps Population data

    • data.niaid.nih.gov
    • zenodo.org
    Updated Feb 22, 2022
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    Tania Gullón (2022). COVID19 Flow-Maps Population data [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4635258
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    Dataset updated
    Feb 22, 2022
    Dataset provided by
    Salvador Capella-Gutierrez
    Miguel Ponce-de-Leon
    Matthew Smith
    Marc Bernardo
    Tania Gullón
    Jon Sanchez-Valle
    Alfonso Valencia
    José María Fernández
    Javier del Valle
    Davide Cirillo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Daily population and trips per person data from Spain 2020-2021

    This repository contains daily population records based on a study conducted by the MITMA, that analysed the mobility and distribution of the population in Spain from February 14th 2020 to May 9th 2021. The study is based on a sample of more than 13 million anonymised mobile phone lines provided by a single mobile operator whose subscribers are evenly distributed.

    For more information on the data visit: https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data

    Data provided by MITMA is related to the layer mitma_mov. For the rest of the layers, the population was estimated using the population grid from GEOSTAT: https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat

  2. Synthetic population for ESP

    • zenodo.org
    bin, csv, pdf, zip
    Updated Jul 16, 2024
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    Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie; Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie (2024). Synthetic population for ESP [Dataset]. http://doi.org/10.5281/zenodo.6503334
    Explore at:
    csv, zip, pdf, binAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie; Abhijin Adiga; Hannah Baek; Stephen Eubank; Przemyslaw Porebski; Madhav Marathe; Henning Mortveit; Samarth Swarup; Mandy Wilson; Dawen Xie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Synthetic populations for regions of the World (SPW) | Spain

    Dataset information

    A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).

    License

    CC-BY-4.0

    Acknowledgment

    This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).

    Contact information

    Henning.Mortveit@virginia.edu

    Identifiers

    Region nameSpain
    Region IDesp
    Modelcoarse
    Version0_9_0

    Statistics

    NameValue
    Population45639013.0
    Average age41.1
    Households17918332.0
    Average household size2.6
    Residence locations17918332.0
    Activity locations5782846.0
    Average number of activities5.6
    Average travel distance130.4

    Sources

    DescriptionNameVersionUrl
    Activity template dataWorld Bank2021https://data.worldbank.org
    Administrative boundariesADCW7.6https://www.adci.com/adc-worldmap
    Curated POIs based on OSMSLIPO/OSM POIshttp://slipo.eu/?p=1551 https://www.openstreetmap.org/
    Household dataIPUMShttps://international.ipums.org/international
    Population count with demographic attributesGPWv4.11https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11

    Files description

    Base data files (esp_data_v_0_9.zip)

    FilenameDescription
    esp_person_v_0_9.csvData for each person including attributes such as age, gender, and household ID.
    esp_household_v_0_9.csvData at household level.
    esp_residence_locations_v_0_9.csvData about residence locations
    esp_activity_locations_v_0_9.csvData about activity locations, including what activity types are supported at these locations
    esp_activity_location_assignment_v_0_9.csvFor each person and for each of their activities, this file specifies the location where the activity takes place

    Derived data files

    FilenameDescription
    esp_contact_matrix_v_0_9.csvA POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model.

    Validation and measures files

    FilenameDescription
    esp_household_grouping_validation_v_0_9.pdfValidation plots for household construction
    esp_activity_durations_{adult,child}_v_0_9.pdfComparison of time spent on generated activities with survey data
    esp_activity_patterns_{adult,child}_v_0_9.pdfComparison of generated activity patterns by the time of day with survey data
    esp_location_construction_0_9.pdfValidation plots for location construction
    esp_location_assignement_0_9.pdfValidation plots for location assignment, including travel distribution plots
    esp_esp_ver_0_9_0_avg_travel_distance.pdfChoropleth map visualizing average travel distance
    esp_esp_ver_0_9_0_travel_distr_combined.pdfTravel distance distribution
    esp_esp_ver_0_9_0_num_activity_loc.pdfChoropleth map visualizing number of activity locations
    esp_esp_ver_0_9_0_avg_age.pdfChoropleth map visualizing average age
    esp_esp_ver_0_9_0_pop_density_per_sqkm.pdfChoropleth map visualizing population density
    esp_esp_ver_0_9_0_pop_size.pdfChoropleth map visualizing population size

  3. Population in China in 2023, by region

    • statista.com
    Updated Apr 14, 2025
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    Statista (2025). Population in China in 2023, by region [Dataset]. https://www.statista.com/statistics/279013/population-in-china-by-region/
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    Dataset updated
    Apr 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    In 2023, approximately 127.1 million people lived in Guangdong province in China. That same year, only about 3.65 million people lived in the sparsely populated highlands of Tibet. Regional differences in China China is the world’s most populous country, with an exceptional economic growth momentum. The country can be roughly divided into three regions: Western, Eastern, and Central China. Western China covers the most remote regions from the sea. It also has the highest proportion of minority population and the lowest levels of economic output. Eastern China, on the other hand, enjoys a high level of economic development and international corporations. Central China lags behind in comparison to the booming coastal regions. In order to accelerate the economic development of Western and Central Chinese regions, the PRC government has ramped up several incentive plans such as ‘Rise of Central China’ and ‘China Western Development’. Economic power of different provinces When observed individually, some provinces could stand an international comparison. Jiangxi province, for example, a medium-sized Chinese province, had a population size comparable to Argentina or Spain in 2023. That year, the GDP of Zhejiang, an eastern coastal province, even exceeded the economic output of the Netherlands. In terms of per capita annual income, the municipality of Shanghai reached a level close to that of the Czech Republik. Nevertheless, as shown by the Gini Index, China’s economic spur leaves millions of people in dust. Among the various kinds of economic inequality in China, regional or the so-called coast-inland disparity is one of the most significant. Posing as evidence for the rather large income gap in China, the poorest province Heilongjiang had a per capita income similar to that of Sri Lanka that year.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Tania Gullón (2022). COVID19 Flow-Maps Population data [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4635258

COVID19 Flow-Maps Population data

Explore at:
Dataset updated
Feb 22, 2022
Dataset provided by
Salvador Capella-Gutierrez
Miguel Ponce-de-Leon
Matthew Smith
Marc Bernardo
Tania Gullón
Jon Sanchez-Valle
Alfonso Valencia
José María Fernández
Javier del Valle
Davide Cirillo
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Daily population and trips per person data from Spain 2020-2021

This repository contains daily population records based on a study conducted by the MITMA, that analysed the mobility and distribution of the population in Spain from February 14th 2020 to May 9th 2021. The study is based on a sample of more than 13 million anonymised mobile phone lines provided by a single mobile operator whose subscribers are evenly distributed.

For more information on the data visit: https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data

Data provided by MITMA is related to the layer mitma_mov. For the rest of the layers, the population was estimated using the population grid from GEOSTAT: https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat

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