{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T08:21:45Z","timestamp":1761294105339,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T00:00:00Z","timestamp":1587340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Games"],"abstract":"<jats:p>Modeling the spread of infectious diseases and social responses is one method that can help public health policy makers improve the control of epidemic outbreaks and make better decisions about vaccination costs, the number of mandatory vaccinations, or investment in media efforts to inform the public of disease threats. Incubation period\u2014the period when an individual has been exposed to a disease and could be infectious but is not yet aware of it\u2014is one factor that can affect an epidemic outbreak, and considering it when modeling outbreaks can improve model accuracy. A change in outbreak activity can occur from the time a person becomes infected until they become aware of infection when they can transmit the disease but their social group considers them a susceptible individual and not an infectious one. This study evaluates the effect of this delay between the time of infection of an individual and the time of diagnosis of the infection (incubation period) in an epidemic outbreak. This study investigates the social dynamics of vaccination and transmission in such epidemic outbreaks, using a model of the public goods game.<\/jats:p>","DOI":"10.3390\/g11020020","type":"journal-article","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T05:48:52Z","timestamp":1587448132000},"page":"20","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Game Theoretic Modeling of Infectious Disease Transmission with Delayed Emergence of Symptoms"],"prefix":"10.3390","volume":"11","author":[{"given":"Marzieh","family":"Soltanolkottabi","sequence":"first","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, University of New Haven, New Haven, CT 06516, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8753-8799","authenticated-orcid":false,"given":"David","family":"Ben-Arieh","sequence":"additional","affiliation":[{"name":"Department of IMSE, Kansas State University, Manhattan, KS 66503, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9929-4421","authenticated-orcid":false,"given":"Chih-Hang","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of IMSE, Kansas State University, Manhattan, KS 66503, USA"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.envint.2015.09.007","article-title":"Impact of climate change on human infectious diseases: Empirical evidence and human adaptation","volume":"86","author":"Wu","year":"2016","journal-title":"Environ. 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