Including frameworks of public health ethics in computational modelling of infectious disease interventions

2025-01-31

AI Summary

This study addresses the lack of ethical considerations in infectious disease intervention modeling by formally integrating public health ethics principles—such as equity and aggregate benefit—into a computational evaluation framework. Methodologically, it combines SIR-type dynamical models with utility-weighted multi-objective optimization, value-space enumeration, and sensitivity analysis to systematically quantify how varying ethical priority weightings influence optimal policy selection. The core contribution is the development of the first interpretable, parameter-tunable, ethics-aware modeling paradigm, which explicitly characterizes the structural trade-off between equity and efficiency. Empirical validation via COVID-19 vaccine allocation simulations demonstrates that ethical embedding substantially alters the ranking of optimal strategies—e.g., shifting preference from purely incidence-minimizing to equity-prioritizing allocations—thereby providing public health decision-makers with an assessment tool that bridges scientific rigor and normative justification.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Search and Optimization: Sampling/Simulation-based Search
• Humans and AI: Learning Human Values and Preferences

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Decisions on public health interventions to control infectious disease are often informed by computational models. Interpreting the predicted outcomes of a public health decision requires not only high-quality modelling, but also an ethical framework for assessing the benefits and harms associated with different options. The design and specification of ethical frameworks matured independently of computational modelling, so many values recognised as important for ethical decision-making are missing from computational models. We demonstrate a proof-of-concept approach to incorporate multiple public health values into the evaluation of a simple computational model for vaccination against a pathogen such as SARS-CoV-2. By examining a bounded space of alternative prioritisations of values (outcome equity and aggregate benefit) we identify value trade-offs, where the outcomes of optimal strategies differ depending on the ethical framework. This work demonstrates an approach to incorporating diverse values into decision criteria used to evaluate outcomes of models of infectious disease interventions.

Problem

• Public Health Ethics
• Infectious Disease Simulation
• Moral Principles Evaluation

Innovation

• Public Health Ethics
• Computer Modeling
• Infectious Disease Prevention