Optimal Control for Stochastic SIR model of Dengue with Brownian Motion

Optimal Control for Stochastic SIR model of Dengue with Brownian Motion | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 29 January 2026 V1 Latest version Share on Optimal Control for Stochastic SIR model of Dengue with Brownian Motion Authors : Md. Abdullah Bin Masud 0000-0001-7713-8110 [email protected] , Tania Annur , and Mostak Ahmed 0000-0002-7023-9071 Authors Info & Affiliations https://doi.org/10.22541/au.176969356.61322514/v1 116 views 69 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract In this study, we develop a model for dengue that incorporates spatial diffusion and Brownian motion to explore the stationary distribution and optimal control strategies for a stochastic dengue model. We begin by demonstrating the existence of a globally positive solution by constructing a Lyapunov function. We then determine sufficient conditions under which a stationary distribution exists and is unique for this positive solution. Following this, we implement control strategies to reduce the number of infected individuals and apply mosquito insecticides. By utilizing Pontryagin's maximum principle and the Euler-Maruyama method, we implement control strategies to reduce the number of infected individuals and apply mosquito insecticides. Finally, we conduct numerical simulations to validate our analytical findings. The simulations confirm the presence of a stationary distribution and reveal variations in the stationary distribution solutions across different spatial domains. Additionally, we examine the impact of varying noise intensities on the stationary distribution and assess the effectiveness of various control strategies for managing stochastic dengue fever. Supplementary Material File (manuscript.pdf) Download 3.10 MB Information & Authors Information Version history V1 Version 1 29 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords and optimal control brownian motion dengue fever pontryagin’s maximum principle stochastic model Authors Affiliations Md. Abdullah Bin Masud 0000-0001-7713-8110 [email protected] Jagannath University View all articles by this author Tania Annur Shanto Mariam University of Creative Technology View all articles by this author Mostak Ahmed 0000-0002-7023-9071 Jagannath University View all articles by this author Metrics & Citations Metrics Article Usage 116 views 69 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Md. Abdullah Bin Masud, Tania Annur, Mostak Ahmed. Optimal Control for Stochastic SIR model of Dengue with Brownian Motion. Authorea . 29 January 2026. DOI: https://doi.org/10.22541/au.176969356.61322514/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.176969356.61322514/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe60399ac9606d3',t:'MTc3OTIyNDI0Nw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();