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Research group

WorldPop

A resident of Ganvie stilt village in Benin navigates a boat through water

Regularly updating data on population numbers and characteristics to help with effective governance and efficient allocation of resources.

About

We work to ensure that everyone is mapped and counted in decision making. We develop geospatial integration methods to make detailed demographic datasets. Our work features in Nature, Science, and the Proceedings of the National Academy of Sciences.

Our datasets are used by governments, international agencies, academia, NGOs and the private sector. We work closely with the United Nation agencies and national statistical offices in low and middle-income countries. Our approaches are designed to maximise uptake and impact, and to strengthen local capacity.

Our work focus areas for development and implementation cover population distributions, demographics and dynamics in resource-poor settings. Our geostatistical modelling integrates data from traditional sources including censuses, and satellite and cellphone datasets.

We produce high resolution maps of:

  • age/sex structures
  • births
  • poverty
  • access to services
  • vaccination coverage

We also develop modelling frameworks for subnational migration flows, urban change and disease spread.

WorldPop is made up of more than 30 members of staff, including demographers, geographers, ecologists, statisticians, epidemiologists and computer scientists.

Principal funders and collaborators include:

  • the Bill and Melinda Gates Foundation
  • UK Department for International Development
  • the World Bank

Research highlights

People, projects and publications

People

Dr Hal Voepel PhD, MS, BSE, BS

Senior Research Fellow

Research interests

  • Hydrological and sediment processes in watersheds and rivers
  • Contaminant transport throughout hydrologic systems
  • Water and sediment impact on human development

Accepting applications from PhD students

Email: h.e.voepel@soton.ac.uk

Address: B44, West Highfield Campus, University Road, SO17 1BJ

Miss Heather Chamberlain

Senior Enterprise Fellow

Email: h.chamberlain@soton.ac.uk

Address: B39, West Highfield Campus, University Road, SO17 1BJ

Mr Ian Coady

WorldPop Deputy Director, Operations

Dr Jamal Hossain PhD, MSc, BSc (Hons)

Lecturer in Applied Health Statistics

Research interests

  • Quantitative Research Methods and Health Survey Data Analysis
  • Multilevel Modelling and Longitudinal Analysis of Health Outcomes
  • Application of Statistical and Machine Learning Methods in Healthcare and Social Science Research

Accepting applications from PhD students

Email: mj.hossain@soton.ac.uk

Address: B67, West Highfield Campus, University Road, SO17 1BJ

Dr Jessica Steele

Senior Enterprise Fellow

Email: js1m14@soton.ac.uk

Address: B39, West Highfield Campus, University Road, SO17 1BJ

Dr Kristine Nilsen

Lecturer in Global Health

Research interests

  • Access, utilisation and quality of maternal and child health services in low income countries
  • Integration of traditional and novel data sources for health
  • Equity and geographical coverage analysis, generalised linear mixed models, small area estimation and subnational geospatial modelling

Accepting applications from PhD students

Email: kristine.nilsen@soton.ac.uk

Address: B58, West Highfield Campus, University Road, SO17 1BJ

Dr Maksym Bondarenko

Senior Enterprise Fellow

Dr Natalia Tejedor Garavito

Principal Enterprise Fellow

Research interests

  • Geospatial data analysis
  • GIS training
  • Health metrics

Accepting applications from PhD students

Email: n.tejedor-garavito@soton.ac.uk

Address: B39, West Highfield Campus, University Road, SO17 1BJ

Dr Ortis Yankey

Research Fellow

Research interests

  • Population Modelling
  • Spatial Epidemiology
  • Health/Medical geography

Email: o.yankey@soton.ac.uk

Address: B37, East Highfield Campus, University Road, SO17 1BJ

Dr Rhorom Priyatikanto

Senior GIS Application Developer

Research interests

  • Machine learning for classification and regression tasks
  • Domain adaptation and transfer learning
WorldPop complements traditional population data sources with dynamic, high-resolution data from satellites, surveys and cellphones to map human population distributions at high resolution, with the ultimate goal of ensuring that everyone, everywhere is counted in decision making.
Personal Chair

Contact information

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