Research project

FuturePop: Constructing high spatial resolution population projections and supporting the provision, access and updates of WorldPop spatial demographic datasets

Project overview

Climate change will have fundamental impacts on health, environments and socioeconomics, but these will not be felt equally across the World. Local variations in human distributions, demographics and growth affect vulnerabilities to a changing climate. High spatial resolution data on populations are therefore vital for understanding, measuring and planning for climate impacts. WorldPop at the University of Southampton have constructed multi-temporal high-resolution population estimate datasets for many years, which have been widely adopted by researchers, governments and international agencies. A gap exists, however, in the provision of such data for future scenarios, broken down by age and sex, to enable assessments of future vulnerabilities to changing health risks, extreme weather and natural disasters. This project will produce high spatial resolution (100m grid cell) global age/sex-structured population estimates for multiple socio-economic scenarios from present day until 2100 with uncertainty metrics, which will be commensurate with existing WorldPop data, and thus can be readily integrated into workflows. It will also construct the pipelines required for updates to the present-day and future scenario datasets. A focus on co-design and development of outputs, tools and communities of practice with climate-health application stakeholders will be central to facilitate uptake, use and sustainability.

Staff

Lead researchers

Professor Andrew Tatem

Personal Chair
Research interests
  • Developing approaches to map population distributions, demographics and dynamics through comp…
  • Understanding the drivers of small area heterogeneities in population health and development …
  • The use of high resolution demographic and mobility data for improving understanding and mode…
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Other researchers

Dr Maksym Bondarenko

Principal Enterprise Fellow
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Dr Jason Hilton

Associate Professor
Research interests
  • Demographic Forecasting
  • Bayesian Statistics
  • Human Mortality
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Dr Natalia Tejedor Garavito

Principal Enterprise Fellow
Research interests
  • Geospatial data analysis
  • GIS training
  • Health metrics
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Research outputs