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One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories

Laurent Hébert-Dufresne, Yong-Yeol Ahn, Antoine Allard

    Arxiv
    |May 2, 2025
    PubMed

    Insights

    Contagion models are siloed, yet real-world contagions interact. This review explores interaction mechanisms and models, advocating for a unified science of contagions.

    Area of Science:

    • Cross-disciplinary research
    • Mathematical modeling
    • Epidemiology
    • Sociology

    Background:

    • Contagion models are widely used in natural and social sciences but are developed in field-specific silos.
    • A common assumption is that contagions can be studied in isolation, ignoring interactions within and across hosts.
    • These interactions significantly impact the dynamics and implications of contagion models.

    Purpose of the Study:

    • To review interaction mechanisms in social and biological contagions.
    • To survey existing models and frameworks for incorporating these interactions.
    • To identify challenges and future directions for studying interacting contagions.

    Main Methods:

    • Literature review of contagion models and interaction mechanisms.
    • Analysis of existing frameworks for modeling coupled contagions.
    • Identification of challenges in interaction inference and model scalability.

    Main Results:

    • Interactions between biological and social contagions are prevalent and complex.
    • Current models often fail to capture these crucial interactions due to siloed development.
    • Challenges exist in inferring interactions and scaling mathematical models.

    Conclusions:

    • A unified science of contagions is needed to bridge the gap between social and biological contagion studies.
    • Interdisciplinary collaboration is essential for developing more realistic and comprehensive contagion models.
    • Future research should focus on robust methods for inferring interactions and scalable modeling approaches.

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