Close

Dr Umberto Gostoli

Research Fellow in Health Impact Modelling

United Kingdom

I am a computational social scientist and economic demographer specialising in agent-based modelling (ABM) and complex systems approaches to social and population health research. I am currently a Research Fellow in Health Impact Modelling in the Department of Public Health, Environments and Society within the Faculty of Public Health and Policy at the London School of Hygiene & Tropical Medicine.

 

My research develops and applies population-based and simulation models to examine how environmental, demographic, and policy changes shape health outcomes and health inequalities in the UK. I integrate epidemiological evidence into quantitative modelling frameworks to generate scenario-based projections that inform public policy, with particular attention to distributional impacts across socioeconomic groups and older populations.

 

More broadly, my work combines economics, demography, behavioural science, and network analysis to understand how individual decisions and social interactions produce system-level outcomes. I have a longstanding interest in modelling kinship structures, social networks, and social care systems, and in evaluating the health, social care, and macroeconomic implications of policy interventions. I work closely with interdisciplinary teams and external stakeholders to ensure that modelling outputs are analytically rigorous, policy-relevant, and suitable for academic publication.

Affiliations

Department of Public Health, Environments and Society
Faculty of Public Health and Policy

Research

My research lies at the intersection of computational demography, economics, complexity science, and population health. I use agent-based and simulation modelling to investigate how individual behaviour, family structures, economic incentives, and socioeconomic constraints interact within complex adaptive systems to generate aggregate outcomes in health, social care, and labour markets.

A central focus of my work is the development of policy-relevant health and social care models that capture heterogeneity, distributional effects, and system-level feedbacks. I am particularly interested in how demographic change, environmental pressures, and social care provision shape health outcomes and health inequalities, especially among older populations.

Key areas of interest include:

  • Complexity and emergent dynamics in public health and social policy systems
  • Agent-based modelling of informal and formal social care systems
  • Socioeconomic determinants of health and health inequalities
  • Economic demography and the interaction between demographic change and economic behaviour
  • Demographic change, kinship networks, and intergenerational support
  • Synthetic population generation and bottom-up modelling approaches
  • Behavioural decision-making under structural, institutional, and economic constraints
  • Uncertainty, heterogeneity, and non-linear dynamics in social and economic systems
  • Integration of health impact modelling with economic and macroeconomic frameworks

My broader goal is to develop computational tools that integrate economic reasoning and complexity science with rigorous health impact modelling, bridging methodological innovation and real-world application to support evidence-based decision-making in population health and social care policy.

Selected Publications

Growing Populations from the ‘Bottom-Up’: An ABM Approach to the Generation of Synthetic Populations
GOSTOLI, U; Hinsch, M; Silverman, E;
2024
Springer Proceedings in Complexity
Situating agent-based modelling in population health research
Silverman, E; GOSTOLI, U; Picascia, S; Almagor, J; McCann, M; Shaw, R; Angione, C;
2021
Emerging themes in epidemiology
Modelling social care provision in an agent-based framework with kinship networks
GOSTOLI, U; Silverman, E;
2019
Royal Society Open Science
A re-examination of “bias” in human randomness perception.
Warren, PA; GOSTOLI, U; Farmer, GD; El-Deredy, W; Hahn, U;
2018
Journal of Experimental Psychology: Human Perception and Performance
See more information