Dynamical analysis and optimal control of the developed information transmission model
Information transmission significantly impacts social stability and technological advancement. This paper compares the phenomenon of "Super transmission" and "Asymptomatic infection" in COVID-19 transmission to information transmission. The former is similar to authoritative info...
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| Veröffentlicht in: | PloS one 2022-05, Vol.17 (5), p.e0268326-e0268326 |
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| creator | Kang, Sida Hou, Xilin Hu, Yuhan Liu, Hongyu |
| description | Information transmission significantly impacts social stability and technological advancement. This paper compares the phenomenon of "Super transmission" and "Asymptomatic infection" in COVID-19 transmission to information transmission. The former is similar to authoritative information transmission individuals, whereas the latter is similar to individuals with low acceptance in information transmission. It then constructs an S2EIR model with transmitter authority and individual acceptance levels. Then, it analyzes the asymptotic stability of information-free and information-existence equilibrium on a local and global scale, as well as the model's basic reproduction number, R0. Distinguished with traditional studies, the population density function and Hamiltonian function are constructed by taking proportion of "Super transmitter" and proportion of hesitant group turning into transmitters as optimization control variables. Based on the Pontryagin maximum principle, an optimal control strategy is designed to effectively facilitate information transmission. The numerical simulation corroborates the theoretical analysis results and the system's sensitivity to control parameter changes. The research results indicate that the authoritative "Super transmitter" has a beneficial effect on information transmission. In contrast, the "Asymptomatic infected individual" with poor individual acceptance level negatively affects information transmission. |
| doi_str_mv | 10.1371/journal.pone.0268326 |
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This paper compares the phenomenon of "Super transmission" and "Asymptomatic infection" in COVID-19 transmission to information transmission. The former is similar to authoritative information transmission individuals, whereas the latter is similar to individuals with low acceptance in information transmission. It then constructs an S2EIR model with transmitter authority and individual acceptance levels. Then, it analyzes the asymptotic stability of information-free and information-existence equilibrium on a local and global scale, as well as the model's basic reproduction number, R0. Distinguished with traditional studies, the population density function and Hamiltonian function are constructed by taking proportion of "Super transmitter" and proportion of hesitant group turning into transmitters as optimization control variables. Based on the Pontryagin maximum principle, an optimal control strategy is designed to effectively facilitate information transmission. The numerical simulation corroborates the theoretical analysis results and the system's sensitivity to control parameter changes. The research results indicate that the authoritative "Super transmitter" has a beneficial effect on information transmission. In contrast, the "Asymptomatic infected individual" with poor individual acceptance level negatively affects information transmission.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0268326</identifier><identifier>PMID: 35604920</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Asymptomatic infection ; Biology and Life Sciences ; Computer and Information Sciences ; Coronaviruses ; COVID-19 ; Dynamical systems ; Evaluation ; Hamiltonian functions ; Infectious diseases ; Information management ; Information processing ; Innovations ; Mathematical models ; Maximum principle ; Medicine and Health Sciences ; Numerical simulations ; Optimal control ; Optimization ; Parameter sensitivity ; Physical Sciences ; Population density ; Population studies ; Social networks ; Social Sciences ; Stability analysis ; Theoretical analysis ; Transmitters</subject><ispartof>PloS one, 2022-05, Vol.17 (5), p.e0268326-e0268326</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>2022 Kang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Kang et al 2022 Kang et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-53c465fc31a6b4ebdcbf43c6cdbd4b563364f4c23bbba661c8fb00ff3eb2e8433</citedby><cites>FETCH-LOGICAL-c692t-53c465fc31a6b4ebdcbf43c6cdbd4b563364f4c23bbba661c8fb00ff3eb2e8433</cites><orcidid>0000-0002-9980-2876</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9132490/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9132490/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35604920$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Abdo, Mohammed S.</contributor><creatorcontrib>Kang, Sida</creatorcontrib><creatorcontrib>Hou, Xilin</creatorcontrib><creatorcontrib>Hu, Yuhan</creatorcontrib><creatorcontrib>Liu, Hongyu</creatorcontrib><title>Dynamical analysis and optimal control of the developed information transmission model</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Information transmission significantly impacts social stability and technological advancement. This paper compares the phenomenon of "Super transmission" and "Asymptomatic infection" in COVID-19 transmission to information transmission. The former is similar to authoritative information transmission individuals, whereas the latter is similar to individuals with low acceptance in information transmission. It then constructs an S2EIR model with transmitter authority and individual acceptance levels. Then, it analyzes the asymptotic stability of information-free and information-existence equilibrium on a local and global scale, as well as the model's basic reproduction number, R0. Distinguished with traditional studies, the population density function and Hamiltonian function are constructed by taking proportion of "Super transmitter" and proportion of hesitant group turning into transmitters as optimization control variables. Based on the Pontryagin maximum principle, an optimal control strategy is designed to effectively facilitate information transmission. The numerical simulation corroborates the theoretical analysis results and the system's sensitivity to control parameter changes. The research results indicate that the authoritative "Super transmitter" has a beneficial effect on information transmission. In contrast, the "Asymptomatic infected individual" with poor individual acceptance level negatively affects information transmission.</description><subject>Asymptomatic infection</subject><subject>Biology and Life Sciences</subject><subject>Computer and Information Sciences</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Dynamical systems</subject><subject>Evaluation</subject><subject>Hamiltonian functions</subject><subject>Infectious diseases</subject><subject>Information management</subject><subject>Information processing</subject><subject>Innovations</subject><subject>Mathematical models</subject><subject>Maximum principle</subject><subject>Medicine and Health Sciences</subject><subject>Numerical simulations</subject><subject>Optimal control</subject><subject>Optimization</subject><subject>Parameter sensitivity</subject><subject>Physical Sciences</subject><subject>Population density</subject><subject>Population studies</subject><subject>Social 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one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kang, Sida</au><au>Hou, Xilin</au><au>Hu, Yuhan</au><au>Liu, Hongyu</au><au>Abdo, Mohammed S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamical analysis and optimal control of the developed information transmission model</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2022-05-23</date><risdate>2022</risdate><volume>17</volume><issue>5</issue><spage>e0268326</spage><epage>e0268326</epage><pages>e0268326-e0268326</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Information transmission significantly impacts social stability and technological advancement. This paper compares the phenomenon of "Super transmission" and "Asymptomatic infection" in COVID-19 transmission to information transmission. The former is similar to authoritative information transmission individuals, whereas the latter is similar to individuals with low acceptance in information transmission. It then constructs an S2EIR model with transmitter authority and individual acceptance levels. Then, it analyzes the asymptotic stability of information-free and information-existence equilibrium on a local and global scale, as well as the model's basic reproduction number, R0. Distinguished with traditional studies, the population density function and Hamiltonian function are constructed by taking proportion of "Super transmitter" and proportion of hesitant group turning into transmitters as optimization control variables. Based on the Pontryagin maximum principle, an optimal control strategy is designed to effectively facilitate information transmission. The numerical simulation corroborates the theoretical analysis results and the system's sensitivity to control parameter changes. The research results indicate that the authoritative "Super transmitter" has a beneficial effect on information transmission. In contrast, the "Asymptomatic infected individual" with poor individual acceptance level negatively affects information transmission.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>35604920</pmid><doi>10.1371/journal.pone.0268326</doi><tpages>e0268326</tpages><orcidid>https://orcid.org/0000-0002-9980-2876</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Asymptomatic infection Biology and Life Sciences Computer and Information Sciences Coronaviruses COVID-19 Dynamical systems Evaluation Hamiltonian functions Infectious diseases Information management Information processing Innovations Mathematical models Maximum principle Medicine and Health Sciences Numerical simulations Optimal control Optimization Parameter sensitivity Physical Sciences Population density Population studies Social networks Social Sciences Stability analysis Theoretical analysis Transmitters |
| title | Dynamical analysis and optimal control of the developed information transmission model |
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