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African map showing population density through colour

Geostatistics for population health

African map showing population density through colour

We develop and apply novel geostatistical methods to address global public health challenges, with a focus on neglected tropical diseases, and other conditions affecting low- and middle-income countries. Our work spans statistical methodology, open-source software development, and direct collaboration with Ministries of Health to support evidence-based policy and decision-making.

About the Research

The Geostatistics for Population Health group develops statistical methods for disease mapping and spatial epidemiology, with applications across a wide range of public health challenges globally. While our work focuses particularly on infectious and tropical diseases, our methods are applied more broadly to population health problems in both low- and middle-income countries and high-income settings. A core commitment of the group is ensuring that advances in statistical methodology translate into practical tools for researchers and public health practitioners worldwide. This is exemplified by RiskMap, our flagship open-source R package for geostatistical analysis and disease risk mapping, and the accompanying textbook Model-based Geostatistics for Global Public Health using R.

The group leads the WHO Collaborating Centre on Geostatistical Methods for Neglected Tropical Disease Research, working closely with Ministries of Health and international partners including the World Health Organization, the Gates Foundation, and The Task Force for Global Health. Applied work spans sub-Saharan Africa, South America, and South-East Asia, contributing to the control and elimination of diseases such as trachoma, soil-transmitted helminths, lymphatic filariasis, schistosomiasis and onchocerciasis.

Methodological contributions of the group include:

  • geostatistical inference for disease prevalence mapping
  • evaluation of the impact of public health interventions
  • statistical methods for analysing serological data
  • integration of multiple data sources and diagnostics
  • development of efficient survey designs for disease surveillance
  • open-source statistical software development

Through these activities, the group aims to strengthen the use of quantitative methods in population health decision-making and to support countries in generating and using data for public health action across a range of resource settings.

Members of the Geostastistics team

Research theme leads

  • Professor Emanuele Giorgi

    Professor of Statistical Science

    Staff profile for Professor Emanuele Giorgi, Professor of Statistical Science within the Department of Applied Health Sciences, College of Medicine and Health, University of Birmingham.

  • Dr Claudio Fronterre

    Senior Research Fellow in Statistical Science

    Staff profile for Dr Claudio Fronterre, Senior Research Fellow in Statistical Science within the Department of Applied Health Sciences, University of Birmingham.

Nirali Soni – Research Fellow

Spatial and spatio-temporal statistics for global health, Mapping and modelling neglected tropical diseases.

Simon Smart – Software Engineer

R package development, Reproducible Shiny apps for conducting complex analyses, Developing pipelines for mapping neglected tropical diseases.

Jennifer NcNally - Project Officer

Spatial and spatio-temporal statistics for global health.

Professor Peter Diggle, Honorary Professor of Epidemiology

Peter contributes to our work on Geostatistics for public health, Development of open-source statistical software, Statistical methods for longitudinal data.

Dominic Hewson

Meet the team

The Geostatistics for Population Health group are part of BESTEAM.

BESTEAM members

Affiliated centres

Funded projects

  • Geostatistics for Global Health (Gates Foundation, 2025–2030)

    The Geostatistics for Global Health programme applies advanced statistical and spatial modelling approaches to address substantive global public health challenges centred around the control and elimination of neglected tropical diseases in low- and middle-income countries. Its research generates evidence to support disease surveillance, inform policy, and improve health outcomes globally.

  • Geostatistical methods for soil-transmitted helminths control (EvidenceAction, 2025–2026

    This project aims to apply cutting-edge geostatistical approaches to the design and analysis of survey data on soil-transmitted helminths (STH) in Sub-Saharan Africa and Southeast Asia. STH are parasitic worm infections that spread through contaminated soil, and they remain one of the most widespread health problems in areas where clean water and sanitation are limited. 

 

 

Workshops, conferences and seminars

  • WHO Collaborating Centre Technical Meeting on Capacity Building of Geostatistical Expertise in LMICs, Lancaster, March 2025
  • WHO Collaborating Centre Technical Meeting on Geostatistical Methods for Trachoma Elimination, Lancaster, March 2024
  • Invited Royal Statistical Society course on Model-based Geostatistics for Global Public Health, Edinburgh, September 2025
  • METMA XI11th International Conference on Spatio-Temporal Modelling, Lancaster, July 2024

Collaboration and opportunities

The group welcomes collaborations with researchers from a wide range of backgrounds. We work with epidemiologists, public health practitioners, and disease control programmes seeking to apply geostatistical methods to surveillance and intervention planning, as well as with statisticians and quantitative scientists with an interest in methodological development at the interface of spatial and spatio-temporal statistics and population health. Whether your primary interest lies in tackling a specific applied problem or in developing new statistical theory and methods, we would be happy to hear from you. Prospective PhD students and postdoctoral researchers are particularly encouraged to get in touch.

Key publications

Theme contact