Causal inference for targeted public health interventions: interactions among environmental, social, and economic
Sewwandi Bandara1, Wakana Oishi1, Mohan Amarasiri1
1Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, Japan.
Abstract:
The One Health framework emphasizes the interconnection between human, animal, and environmental systems in shaping infectious disease dynamics. Multiple environmental, social, and economic determinants jointly influence disease transmission, operating through interconnected pathways within this system. However, the causal mechanisms linking these determinants to infectious disease outcomes remain poorly understood. This study systematically reviews and synthesizes evidence on the causal interrelationships among key determinants to better elucidate their contributions to infectious disease incidence. Drawing on literature across urbanization, climate change, land-use change, population mobility, and water, sanitation, and hygiene (WaSH) conditions, we examine how these factors interact to influence transmission dynamics through complex environmental and socioeconomic pathways. Our findings indicate that no single determinant independently drives disease transmission; rather, overlapping exposures and interactions create complex feedback loops that amplify public health vulnerabilities, particularly in resource-constrained settings. We advocate for the integration of causal inference to move beyond traditional correlation-based analyses and to identify the pathways through which these determinants influence disease dynamics. Embedding causal reasoning within the One Health framework can strengthen evidence-based policy and support the design of targeted, context-specific, and resilient public health interventions aimed at reducing the burden of infectious diseases.
Related Concept Videos
Causality in Epidemiology
Criteria for Causality: Bradford Hill Criteria - II
Models of Health Promotion and Illness Prevention II
The agent-host-environment model states that disease results from...
Criteria for Causality: Bradford Hill Criteria - I
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Introduction to Epidemiology
