Uncertainty and Value of Information Analysis in the Integrated Transport and Health Impact Modelling Tool for Global Cities (ITHIM-Global)

Abstract

Introduction Health impact assessment models are a key tool for stakeholders to understand the effect of transport on public health. The Integrated Transport and Health Impact Model for Global Cities (ITHIM-Global) is an open-source model developed primarily for low- and middle-income countries to assess the impact of changes in transport on population health at the city level. It models impacts through three different pathways: air pollution, physical activity, and road traffic fatalities; however, the uncertainty in input parameters and model calculations requires further examination. Methods ITHIM-Global uses Monte Carlo simulation, sampling from predefined probability distributions of inputs to generate credible intervals for model outputs. Value of Information (VoI) analysis identifies which input parameters most influence output uncertainty. Using Bogotá as an example, we illustrate this approach with three hypothetical scenarios, each shifting 5% of trips to cycling, public transport, or car journeys. Results Increases in cycling or public transport consistently improved population health, regardless of input uncertainty, while increased car journeys consistently worsened health outcomes. Perfect knowledge of individual input parameters, such as the number of people with no travel-related physical activity, could reduce the standard deviation of credible intervals for years of life lost by up to 7%. Conclusions ITHIM-Global can support evidence-based decision-making by demonstrating health impacts of transport scenarios across varied contexts, the practicalities of using VoI analysis and the value of prioritising data collection to reduce model uncertainty.