Geostatistics for Population Health Group

Developing statistical tools and disease mapping methods to support data-driven public health decision-making and disease control worldwide.

The geostatistics for Population Health group 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.

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.

The Geostatistics for Population Health group are part of BESTEAM at the University of Birmingham.