One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories (2504.15053v1)

Abstract: From pathogens and computer viruses to genes and memes, contagion models have found widespread utility across the natural and social sciences. Despite their success and breadth of adoption, the approach and structure of these models remain surprisingly siloed by field. Given the siloed nature of their development and widespread use, one persistent assumption is that a given contagion can be studied in isolation, independently from what else might be spreading in the population. In reality, countless contagions of biological and social nature interact within hosts (interacting with existing beliefs, or the immune system) and across hosts (interacting in the environment, or affecting transmission mechanisms). Additionally, from a modeling perspective, we know that relaxing these assumptions has profound effects on the physics and translational implications of the models. Here, we review mechanisms for interactions in social and biological contagions, as well as the models and frameworks developed to include these interactions in the study of the contagions. We highlight existing problems related to the inference of interactions and to the scalability of mathematical models and identify promising avenues of future inquiries. In doing so, we highlight the need for interdisciplinary efforts under a unified science of contagions and for removing a common dichotomy between social and biological contagions.

Analyzing Interactions in Contagion Models: Implications for Disease and Information Spread

The paper "One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories" examines the limitations of traditional contagion models that treat pathogens and ideas as independent entities. It underscores the necessity of considering interactions among various biological and social contagions to reflect the complexity observed in real-world scenarios. This comprehensive review not only highlights the shortcomings of studying contagions in isolation but also advocates for a more integrated, interdisciplinary approach that bridges the gap between the biological and social sciences.

Key Insights from the Paper

The authors critique the traditional assumption in contagion models that pathogens or ideas spread independently. Instead, they provide evidence that interactions between contagions—whether biological, social, or informational—are crucial in shaping epidemics and the spread of beliefs. Here are several pivotal themes discussed in the paper:

1. Interacting Biological Pathogens: The authors describe scenarios where pathogens do not act independently within a host but instead interact with other microbes, the immune system, and even genetic factors. For instance, the co-infection of viruses like hepatitis D and B demonstrates how one pathogen can depend on another, leading to more severe disease outcomes.
2. Complexity of Social Contagion: Social contagions often involve complex interactions, where ideas, information, or behaviors do not spread in isolation. The spread of misinformation or cultural trends typically involves a network of related beliefs and behaviors, which can either amplify or attenuate the overall impact.
3. Ecological and Network Perspectives: The paper proposes that contagions be studied through ecological or network lenses, which can offer insights into their interactive dynamics. For instance, synergistic contagions that benefit from each other's presence can exhibit non-linear spread patterns, akin to ecological symbiosis.
4. Modeling Challenges and Opportunities: The review emphasizes the challenges of modeling high-dimensional systems where numerous contagions interact simultaneously. The authors suggest that mathematical and computational models must evolve to accommodate these interactions and provide meaningful predictions of contagion dynamics.
5. Implications for Public Health and Policy: The recognition of interaction among contagions has significant implications for public health strategies. For instance, addressing misinformation requires countermeasures that account for the interconnected nature of beliefs, rather than tackling each false claim individually.

Implications and Future Directions

The findings outlined in this paper have profound implications. By acknowledging the interactive nature of contagions, researchers can improve the accuracy of predictive models used in epidemiology and information science. This integrated perspective can also enhance efforts to combat misinformation, social polarization, and public health crises by developing strategies that consider the full landscape of interacting factors.

Moving forward, the paper suggests several promising research avenues. These include the development of new models that incorporate network dynamics and ecological principles, as well as empirical research to gather co-infection and co-spreading data across social platforms and biological systems. Furthermore, interdisciplinary collaborations will be essential to foster a unified science of contagions that transcends traditional boundaries between fields.

By shifting to a framework that considers the interplay between multiple contagions, science can more effectively anticipate and manage the challenges that arise from both biological pathogens and the spread of ideas in society. This nuanced approach not only broadens our understanding of contagion processes but also equips policymakers with tools to better navigate the complex web of modern epidemics, whether they involve diseases or information.