Disease dynamics in a stochastic network game: A little empathy goes a long way in averting outbreaks

Ceyhun Eksin, Jeff S. Shamma, Joshua S. Weitz

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Article number44122
JournalScientific reports
StatePublished - Mar 14 2017
Externally publishedYes

ASJC Scopus subject areas

  • General


Dive into the research topics of 'Disease dynamics in a stochastic network game: A little empathy goes a long way in averting outbreaks'. Together they form a unique fingerprint.

Cite this