ArticleScientific reports2017
Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 58 citations in OpenAlex.
- Modeling the impact of hospitalization-induced behavioral changes on the spread of COVID-19 in New York City.Infectious Disease Modelling · 2025Article
- The impact of threshold decision mechanisms of collective behavior on disease spread.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Social divisions and risk perception drive divergent epidemics and large later waves.Evolutionary human sciences · 2023Article
- Learning to Mitigate Epidemic Risks: A Dynamic Population Game Approach.Dynamic games and applications · 2023Article
- Dynamic Games of Social Distancing During an Epidemic: Analysis of Asymmetric Solutions.Dynamic games and applications · 2022Article
- Game-Theoretic Frameworks for Epidemic Spreading and Human Decision-Making: A Review.Dynamic games and applications · 2022Article
- The benefits of peer transparency in safe workplace operation post pandemic lockdown.Journal of the Royal Society, Interface · 2021Article
- Awareness-driven behavior changes can shift the shape of epidemics away from peaks and toward plateaus, shoulders, and oscillations.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Awareness-driven Behavior Changes Can Shift the Shape of Epidemics Away from Peaks and Towards Plateaus, Shoulders, and Oscillations.medRxiv : the preprint server for health sciences · 2020Article
- Imitation dynamics in the mitigation of the novel coronavirus disease (COVID-19) outbreak in Wuhan, China from 2019 to 2020.Annals of translational medicine · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.