{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T02:13:22Z","timestamp":1791252802093,"version":"4.1.0"},"reference-count":45,"publisher":"AIP Publishing","issue":"1","funder":[{"DOI":"10.13039\/501100001501","name":"University Grants Commission","doi-asserted-by":"publisher","award":["221610082189"],"award-info":[{"award-number":["221610082189"]}],"id":[{"id":"10.13039\/501100001501","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["pubs.aip.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,1,1]]},"abstract":"<jats:p>During a pandemic, many people face confusion and struggle to decide the most appropriate action to protect themselves by choosing between health-conscious and health-unconscious strategies. This decision is influenced by two main factors: the spread of infection within the population and the perceived benefits or risks of contracting the infection. To remove this confusion, development of an epidemic model with the dynamics of individuals\u2019 decision-making processes to investigate how individuals choose the strategies is important. In this study, we introduce an epidemic model in which susceptible, infected, and recovered individuals are partitioned into health-conscious and health-unconscious subpopulations. Our findings indicate that at Nash equilibrium, individuals in both the health-conscious and health-unconscious groups exhibit the same behavior. Local sensitivity analysis quantifies the contribution of individual parameters to the basic reproduction number, while global sensitivity analysis evaluates parameter influence on the infected classes across the full model space. To provide a comprehensive understanding of the overall social benefit, average social payoff is evaluated in both Nash equilibrium and social optimum. Our results also indicate that the social dilemma intensifies as individual costs, waning immunity, and disease transmission rates increase for both groups.<\/jats:p>","DOI":"10.1063\/5.0314285","type":"journal-article","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T14:08:17Z","timestamp":1769177297000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":1,"title":["Imitation-based evolutionary dynamics of behavioral decisions between health-conscious and health-unconscious strategies"],"prefix":"10.1063","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0231-3411","authenticated-orcid":false,"given":"Kiriti","family":"Bhusan Mahato","sequence":"first","affiliation":[{"name":"Department of Mathematics, Indian Institute of Engineering Science and Technology 1 , Shibpur, Howrah 711103,","place":["India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2737-200X","authenticated-orcid":false,"given":"Mst","family":"Sebi Khatun","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Engineering Science and Technology 1 , Shibpur, Howrah 711103,","place":["India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1239-9840","authenticated-orcid":false,"given":"Pritha","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Engineering Science and Technology 1 , Shibpur, Howrah 711103,","place":["India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4832-5210","authenticated-orcid":false,"given":"Dibakar","family":"Ghosh","sequence":"additional","affiliation":[{"name":"Physics and Applied Mathematics Unit, Indian Statistical Institute 2 , 203 B. 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