Organization:WorldPop Project

From HandWiki
WorldPop
Logo of the WorldPop Project
AbbreviationWorldPop
Formation2013-10-01
TypeResearch project
PurposeProducing detailed and freely-available population distribution maps for low- and middle-income countries.
HeadquartersUniversity of Southampton Southampton, Hampshire
Location
  • United Kingdom
Region served
Global
Official language
English
Coordinator
Professor Andrew J Tatem
AffiliationsSchool of Geography and Environmental Science, University of Southampton
Websitehttp://www.worldpop.org/

WorldPop is a research programme based in the School of Geography and Environmental Science, University of Southampton.[1] The programme employs a multidisciplinary team of researchers, analysts, GIS technicians, and project specialists who construct open data on populations and population attributes at high spatial resolution. Created from a combination of The AfriPop Project, AmeriPop, and AsiaPop projects in 2013, WorldPop engages in geospatial demographic projects with governments and institutions in low- and middle-income countries (LMICs) as well as collaborations with partner organisations, such as the Bill & Melinda Gates Foundation, Gavi, the Vaccine Alliance, United Nations agencies, the UK Foreign, Commonwealth and Development Office,[2] commercial data providers and other international development organisations. The programme provides training in population modelling to ministries of health and national statistical offices in LMICs and works with them to support health and demographic surveys[3] to achieve Sustainable Development Goals[4]

Areas of interest

Screen capture of WorldPop Demographics Portal interface showing subnational age/sex structures for Africa, 2020

Population estimation

WorldPop develops statistical population modelling methods to produce gridded population estimates that support census activities.[11][12] The programme develops new methods for data synthesis that use demographic and health surveys, census, satellite imagery,[13] cell phone[14] and other data to create consistent gridded outputs[15] and map detailed population densities.[16][17]

A case study evaluating several geospatial datasets against the 'gold-standard' census data for Bioko Island, Equatorial Guinea found that while the WorldPop Constrained dataset for the area matched best at lower population densities, WorldPop Unconstrained data performed poorly at all densities.[18]

Population of Papua New Guinea

Although the government of Papua New Guinea had estimated the country's population at 9.4 million, unpublished findings of a population estimation study funded by the United Nations Population Fund[19] and conducted by WorldPop in November 2022 suggested the true population was close to 17 million.[20][21] This estimate was reviewed and amended to less than 11 million and the methodology used to calculate this figure was published in July 2023.[22][23]

Academic debate on rural population estimates

In 2025, the accuracy of WorldPop and other global gridded population datasets was discussed in the academic literature with respect to the representation of rural populations. The debate centred on whether observed discrepancies indicate a systemic bias in population modelling or reflect localised methodological limitations.

Rural underrepresentation study (2025)

A study published in Nature Communications by Láng-Ritter et al. (2025) analysed five major global population datasets, including WorldPop, and reported systematic underestimation of rural populations.[24] Using historical resettlement records from 307 large dam projects across 35 countries as an independent reference, the authors estimated a 53.4% negative bias in WorldPop’s rural population estimates. The study attributed this discrepancy to incomplete rural census data and modelling approaches primarily calibrated for urban environments, and suggested potential implications for development planning and resource allocation.

Response from data producers

In a published rebuttal, a group of population data producers, including WorldPop Director Andrew J. Tatem, disputed the study’s conclusions and argued that its findings resulted from methodological shortcomings rather than systemic bias.[25] The rebuttal raised several points:

  • The study was said to measure known technical limitations, such as the use of static water masks and growth-only building models, in areas affected by reservoir flooding where population allocation is not intended.
  • The authors argued that displacement linked to large dam reservoirs represents rare and localised cases that should not be generalised to global rural population accuracy.
  • They stated that population in such areas is typically redistributed to nearby grid cells rather than omitted from datasets.
  • The rebuttal estimated that reservoir-related population misplacement affects less than 2% of the global rural population, contrasting with the larger global underestimation proposed by Láng-Ritter et al..

The data producers acknowledged the value of improving rural demographic data but maintained that the study does not demonstrate a fundamental flaw in WorldPop or other global gridded population datasets.

WorldPop Database

Outputs from WorldPop research contribute to a spatial database of linked information on contemporary census data, satellite-imagery-derived settlement maps, and land cover information. The resultant API, datasets, methods, and maps are available under Creative Commons license on the project's websites. Through collaboration with Esri, gridded population datasets produced by WorldPop are also available in the ArcGIS Living Atlas of the World [26][27]

See also

References

  1. ↑ "Southampton Geospatial". University of Southampton. https://www.southampton.ac.uk/research/institutes-centres/southampton-geospatial. 
  2. ↑ Ian Coady (2021-05-24). "Highlight on the Foreign, Commonwealth and Development Office: How the Foreign, Commonwealth and Development Office is helping to put everyone on the map". https://www.gov.uk/government/news/highlight-on-the-foreign-commonwealth-and-development-office. 
  3. ↑ Tatem, Andrew (2015-01-31). "WorldPop, open data for spatial demography". Scientific Data 4 (170004): 3. doi:10.1038/sdata.2017.4. PMID 28140397. 
  4. ↑ Andrew J. Tatem (2016-07-01). "The Beveridge Memorial Lecture, 2016". https://rss.org.uk/RSS/media/File-library/Events/Key%20events/Tatem-Beveridge-Jun16.pdf. 
  5. ↑ Tatem, Andrew (2014-08-14). "Mapping the denominator: spatial demography in the measurement of progress". International Health 6 (3): 153–155. doi:10.1093/inthealth/ihu057. PMID 25125576. PMC 4161992. https://academic.oup.com/inthealth/article/6/3/153/2964850. Retrieved 2022-12-09. 
  6. ↑ Pindolia, Deepa; Garcia, Andres; Wesolowski, Amy; Smith, David; Buckee, Caroline; Noor, Abdisalan; Snow, Robert; Tatem, Andrew (2012-06-18). "Human movement data for malaria control and elimination strategic planning". Malaria Journal 11 (205): 205. doi:10.1186/1475-2875-11-205. PMID 22703541. 
  7. ↑ Tatem, Andrew (2022-06-21). "Small area population denominators for improved disease surveillance and response". Epidemics 40 (September 2022). doi:10.1016/j.epidem.2022.100597. PMID 35749928. 
  8. ↑ Nilsen, Kristine; Tejedor-Garavito, Natalia; Leasure, Douglas; Utazi, Edson; Ruktanonchai, Corrine; Wigley, Adelle; Dooley, Claire; Matthews, Zoë et al. (2021-09-13). "A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators". BMC Health Services Research 21 (370): 370. doi:10.1186/s12913-021-06370-y. PMID 34511089. 
  9. ↑ Lai, Shengjie; Ruktanonchai, Nick; Zhou, Liangcai; Prosper, Oliver; Luo, Wei; Floyd, Jessica; Wesolowski, Amy; Santillana, Mauricio et al. (2020-05-04). "Effect of non-pharmaceutical interventions to contain COVID-19 in China". Nature 585 (7825): 410–413 (2020). doi:10.1038/s41586-020-2293-x. PMID 32365354. Bibcode: 2020Natur.585..410L. 
  10. ↑ Dotse-Gborgbortsi, Winfred; Nilsen, Kristine; Ofosu, Anthony; Matthews, Zoë; Tejedor-Garavito, Natalia; Wright, Jim; Tatem, Andrew (2022-08-31). "Distance is "a big problem": a geographic analysis of reported and modelled proximity to maternal health services in Ghana". BMC Pregnancy and Childbirth 22 (672): 672. doi:10.1186/s12884-022-04998-0. PMID 36045351. 
  11. ↑ United Nations Population Fund (2020). "The Value of Modelled Population Estimates for Census Planning and Preparation". https://www.unfpa.org/sites/default/files/resource-pdf/Technical-Guidance-Note_Vaue_of_Modeled_Pop_Estimates_in_Census_FINAL.pdf. 
  12. ↑ Ryan Lenora Brown (2021-11-29). "As South Sudan builds back, here's how a census can help". https://www.csmonitor.com/World/Africa/2021/1129/As-South-Sudan-builds-back-here-s-how-a-census-can-help. 
  13. ↑ "Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery". Remote Sensing of Environment 93 (1–2): 42–52. 2004. doi:10.1016/j.rse.2004.06.014. PMID 22581984. Bibcode: 2004RSEnv..93...42T. 
  14. ↑ Steele, Jessica; Pezzulo, Carla; Albert, Maximillian; Brooks, Christopher; zu Erbach-Schoenberg, Elisabeth; O'Connor, Siobhán; Sundsøy, Pål; Engø-Monsen, Kenth et al. (2021-11-22). "Mobility and phone call behavior explain patterns in poverty at high-resolution across multiple settings". Humanities and Social Sciences Communications 8: 288. doi:10.1057/s41599-021-00953-0. 
  15. ↑ Thompson, Dana; Rhoda, Dale; Tatem, Andrew; Castro, Marcia (2020-09-09). "Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda". International Journal of Health Geography 19 (34): 16. doi:10.1186/s12942-020-00230-4. PMID 32907588. 
  16. ↑ Linard C, Alegana, VA, Noor AM, Snow RW, Tatem AJ (2010). "A high resolution spatial population database of Somalia for disease risk mapping". International Journal of Health Geographics 9: 45. doi:10.1186/1476-072x-9-45. PMID 20840751. 
  17. ↑ "High resolution settlement and population maps for low income nations: combining land cover and national census in East Africa". PLOS ONE 2 (12). 2007. doi:10.1371/journal.pone.0001298. PMID 18074022.  open access
  18. ↑ "Measuring the accuracy of gridded human population density surfaces: A case study in Bioko Island, Equatorial Guinea". PLOS ONE 19 (9). 2021-11-22. doi:10.1371/journal.pone.0248646. PMID 34469444. Bibcode: 2021PLoSO..1648646F. 
  19. ↑ United Nations Population Fund (2020). "UNFPA: Census". https://www.unfpa.org/census#readmore-expand. 
  20. ↑ Sydney, Bernard Lagan. "Papua New Guinea finds real population is almost double official estimates" (in en). The Times. ISSN 0140-0460. https://www.thetimes.com/uk/politics/article/papua-new-guinea-finds-real-population-is-almost-double-official-estimates-n86g6sdpm. 
  21. ↑ Randall, Angus. "Papua New Guinea population could hit 17 million" (in en). https://www.abc.net.au/radio/programs/worldtoday/papua-new-guinea-population-could-hit-17-million/101734306. 
  22. ↑ National Statistical Office of Papua New Guinea (2023). "Population Estimates 2021". https://www.nso.gov.pg/statistics/population/. 
  23. ↑ WorldPop (July 27, 2023). "Modelled Population Estimates for Papua New Guinea". https://wopr.worldpop.org/?PNG/Population. 
  24. ↑ Láng-Ritter, R. (2025). "Systematic underestimation of rural populations in global gridded population datasets". Nature Communications 16. doi:10.1038/s41467-025-56906-7. 
  25. ↑ "Rebuttal to claims of systematic rural undercounting in global population datasets". SocArXiv. 2025. https://osf.io/preprints/socarxiv/rhq97_v1. 
  26. ↑ "Esri and WorldPop Partner to Bring Updated Demographic Data to Policy Makers". 2021-12-17. https://www.esri.com/about/newsroom/announcements/esri-and-worldpop-partner-to-bring-updated-demographic-data-to-policy-makers/. 
  27. ↑ "WorldPop Project". Esri. 2021-12-17. https://www.arcgis.com/home/user.html?user=WorldPop_Project. 



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