Improved mapping of residential populations for targeted public health planning, service delivery, and development in low- and middle-income countries
Research led by geographers at the University of Southampton’s WorldPop research programme has led to a series of innovations in the construction of consistent and high resolution population maps through integrating census, survey and satellite-based data.
Issues
The global human population is growing by more than 80 million a year, with the vast majority of this growth concentrated in low- and middle- income countries. While high income countries have extensive mapping resources and expertise at their disposal to create such data, these are either lacking or of poor quality across low-income regions, forming a major obstacle to planning of services and intervention targeting.
Approach
Southampton’s WorldPop research group have been developing methods for improving the spatial demographic evidence base in low- and middle- income countries since October 2013. The underlying research involves development of spatial statistical algorithms for the integration of more 'traditional' sources of demographic data, such as censuses and household surveys, with newer digital datasets derived from GPS, digital boundaries, satellite imagery and elsewhere.
Impact
In Afghanistan, WorldPop’s modelled estimates have replaced projections from the last census in 1979. These estimates have been used in implementing polio vaccination in the country by the government and the WHO’s polio eradication initiative. They have also been used by the government and World Bank in designing new household surveys.
Similarly in Nigeria, population modelling has been used to plan polio elimination after the 2006 census data proved to be too inaccurate. The switch to the modelled estimates for assessment of needs, planning vaccination strategies, and operational implementation contributed to successful delivery of vaccinations and the elimination of polio in the country in 2015.
The Afghanistan and Nigeria work resulted in WorldPop’s modelling approaches being adopted in the United Nations Population Fund census strategy in July 2019. The work also resulted in the establishment of a new $40M programme, GRID3, where the WorldPop group are funded to support governments in sub-Saharan Africa with modelling and capacity strengthening.
High resolution gridded population datasets were made open access through the WorldPop website, leading to a range of collaborations. From November 2013 to present, WorldPop’s maps have consistently formed the standard dataset for the Operational Satellite Applications Programme (UNOSAT) of the UN Institute for Training and Research for assessment of populations impacted by disasters and other events. The population mapping work was also presented to head of all national statistical offices at the UN’s Commission on Population and Development. WorldPop delivered training on data use through workshops.
WorldPop datasets have been widely used in COVID-19 pandemic response. This has included use as the demographic basis for the highly publicised Imperial College and IHME COVID transmission models, which led to the implementation of lockdown measures by the UK and US governments in March 2020.
More information
Institution: University of Southampton
Researchers: Professor Andrew Tatem, Dr Alessandro Sorichetta, Dr Edson Utazi, Dr Doug Leasure, Claudio Bosco, Dr Nicola Wardrop, Dr Victor Alegana, Warren C. Jochem, Dr Donna Clarke, Heather Chamberlain, David Kerr, Dr Carla Pezzulo, Tomas Bird, Nikolaos Ves, Dr Chris Lloyd, Graeme Hornby, Dr Natalia Tejedor, Alessandra Carioli, Julia Thorley, Dr Tracey Adole, Dr Nick Ruktanoncha, Dr Claire Dooley, Oliver Pannell, Dr Gianluca Boo, Edith Darin
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How to cite
Royal Geographical Society (with IBG) (2023) Improved mapping of residential populations to target public health planning, service delivery, and development in low and middle income countries. Available at https://rgs.org/Improved-mapping-of-residential-populations Last accessed on: <date>