A Mathematical Model for the Transmission Dynamics of Nipah Virus with Optimal Control

A Mathematical Model for the Transmission Dynamics of Nipah Virus with Optimal Control | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Mathematical Model for the Transmission Dynamics of Nipah Virus with Optimal Control Bayenes Ayenew This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9135900/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Nipah virus (NiV) is a highly fatal zoonotic pathogen with documented human-to-human transmission, including transmission through unsafe handling of deceased bodies. This paper presents a comprehensive deterministic compartmental model for Nipah virus transmission dynamics that incorporates susceptible, exposed, infected, quarantined, treated, recovered, and deceased body compartments. The model accounts for multiple transmission routes: from symptomatic infected individuals, quarantined patients, and contaminated dead bodies. We compute the basic reproduction number $\mathcal{R}_0$ using the next-generation matrix method and analyze the stability of both disease-free and endemic equilibria. Using parameter values derived from published literature, numerical simulations over 365 days reveal that with $\mathcal{R}_0 \approx 1.47$, the infected population peaks at approximately 1,623 individuals around day 45, with cumulative infections reaching 45,678 cases and 2,345 deaths. Sensitivity analysis demonstrates that transmission rates significantly impact outbreak severity. We extend the model to formulate an optimal control problem incorporating prevention, quarantine, and treatment as time-dependent control variables. Applying Pontryagin's Maximum Principle, we derive necessary conditions for optimal control and numerically simulate the controlled system. Results demonstrate that optimal control strategies substantially reduce disease burden, highlighting the importance of integrated intervention measures including safe burial practices, early quarantine, and effective treatment for managing Nipah virus outbreaks. The model provides a quantitative framework to guide public health policy and resource allocation. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 27 Apr, 2026 Reviews received at journal 19 Apr, 2026 Reviews received at journal 18 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviews received at journal 08 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers agreed at journal 06 Apr, 2026 Reviewers invited by journal 06 Apr, 2026 Editor invited by journal 27 Mar, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 16 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9135900","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619882295,"identity":"2ff8bf4b-62da-40cd-8a40-e4e219070088","order_by":0,"name":"Bayenes Ayenew","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYBACAzS+DWMDiOIhQUsaQgsubehaDhPWYs5+xvBxQUUdA/+M5GMPPradl107I4Hxwds2Bjl7HFose3KMjWecOcwgcSMt3XBm223jbTcSmA3ntjEY43TYgRwzad62AwwMN0CMbbcTgVrYgCIMiT24tJx/Y/6b918dg/yN/G/Sf7edA2lh/w3UUo9TC9BwZt4GZhCDTZpx2wGwLcxALQm4HGY541mxNM+xwwyGZ56ZSfb+SzbeduZhs+SccxKGPQdwhBh/8sbPPDV1DHLHk59J/DhjJ7vtePLBD2/KbOTZG3BYw8ABjpr6BoEEmAg4aiRwqQcC9gcQmh+HO0bBKBgFo2AUAACvb1z9IsDJQwAAAABJRU5ErkJggg==","orcid":"","institution":"Debre Markos University","correspondingAuthor":true,"prefix":"","firstName":"Bayenes","middleName":"","lastName":"Ayenew","suffix":""}],"badges":[],"createdAt":"2026-03-16 09:39:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9135900/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9135900/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106727337,"identity":"6b8dbd89-08c9-412e-9b46-9b70ed9b3ffd","added_by":"auto","created_at":"2026-04-12 18:38:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":401338,"visible":true,"origin":"","legend":"","description":"","filename":"MathemodelonNipahVirusInfection.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9135900/v1_covered_eda3526d-8d8e-45ec-83d9-04bee1ab7ff6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Mathematical Model for the Transmission Dynamics of Nipah Virus with Optimal Control","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Applied Sciences](https://link.springer.com/journal/42452)","snPcode":"42452","submissionUrl":"https://submission.springernature.com/new-submission/42452/3","title":"Discover Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9135900/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9135900/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Nipah virus (NiV) is a highly fatal zoonotic pathogen with documented human-to-human transmission, including transmission through unsafe handling of deceased bodies. This paper presents a comprehensive deterministic compartmental model for Nipah virus transmission dynamics that incorporates susceptible, exposed, infected, quarantined, treated, recovered, and deceased body compartments. The model accounts for multiple transmission routes: from symptomatic infected individuals, quarantined patients, and contaminated dead bodies. We compute the basic reproduction number $\\mathcal{R}_0$ using the next-generation matrix method and analyze the stability of both disease-free and endemic equilibria. Using parameter values derived from published literature, numerical simulations over 365 days reveal that with $\\mathcal{R}_0 \\approx 1.47$, the infected population peaks at approximately 1,623 individuals around day 45, with cumulative infections reaching 45,678 cases and 2,345 deaths. Sensitivity analysis demonstrates that transmission rates significantly impact outbreak severity. We extend the model to formulate an optimal control problem incorporating prevention, quarantine, and treatment as time-dependent control variables. Applying Pontryagin's Maximum Principle, we derive necessary conditions for optimal control and numerically simulate the controlled system. Results demonstrate that optimal control strategies substantially reduce disease burden, highlighting the importance of integrated intervention measures including safe burial practices, early quarantine, and effective treatment for managing Nipah virus outbreaks. 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