Multi-agent simulation model updating and forecasting for the evaluation of COVID-19 transmission

Multi-agent simulation model updating and forecasting for the evaluation of COVID-19 transmission | 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 Article Multi-agent simulation model updating and forecasting for the evaluation of COVID-19 transmission Brenno Moura Castro, Marcelo de Miranda Reis, Ronaldo Moreira Salles This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1778885/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Agent-based models have been an emerging approach in epidemiological modelling, specifically in investigating the COVID-19 virus. However, there are challenges to its validation due to the absence of real data on specific socio-economic and cognitive aspects. Therefore, this work aims to present a strategy for updating, verifying and validating these models based on applying the particle swarm optimization algorithm to better model a real case. For such application, this work also presents a new framework based on multi-agents that allows estimating the evolution of the pandemic, predicting hospital resources, and estimating adaptive population immunization and population density in specific areas. Evaluation metrics such as the data's Shape Factor (SF), Mean Square Error (RMSE), and statistical and sensitivity analyses of the responses obtained were applied for comparison with the real data. The Brazilian municipality of Passa Vinte, located in the State of Minas Gerais (MG), was used as a case study. The model was updated in cumulative cases until the 365th day of the pandemic. The results obtained in the statistical and sensitivity analysis showed similar patterns around the actual data up to the 500th day of the pandemic. Their mean values ​​of SF and RMSE were 0.96 and 7.22, respectively, showing good predictability and consistency, serving as an adequate tool for decision-making in health policies. COVID-19 Multi-agent model Epidemiological model Model updating Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 05 Sep, 2022 Reviews received at journal 26 Jul, 2022 Reviewers agreed at journal 25 Jul, 2022 Reviewers agreed at journal 10 Jul, 2022 Reviewers invited by journal 09 Jul, 2022 Editor assigned by journal 01 Jul, 2022 Editor invited by journal 28 Jun, 2022 Submission checks completed at journal 28 Jun, 2022 First submitted to journal 20 Jun, 2022 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. We do this by developing innovative software and high quality services for the global research community. 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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-1778885","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":116890364,"identity":"d583faff-99d9-45f7-b72b-cf318e7acf07","order_by":0,"name":"Brenno Moura Castro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACA1RuhQSIZGNgbCBKCzMQnyFZC2MbA2Et5tKHjz0uqGCQ5+8/f+zDx3kW0fwMzMceMO64h1OLZV9auvGMMwyGM24kM8+cuU0id2YDW7oB45li3A47w2MmzdvGkMBwg5mZmReoZcMBHjMJxrYEPFr4v4G1yJ8/DNQyRyJ3/wH+bwS08LCBtRgcSAZqaQDawsDDhleLZQ+bmTTPGQnDjTeSjRlnHJPInXGYzdwg8QxuLeY8zM+keSps5OXOH3zM8KGmLre/vfnZg487cGuBAgkkNihKCWoYBaNgFIyCUYAXAAC+zkiAmh47YQAAAABJRU5ErkJggg==","orcid":"","institution":"Military Institute of Engineering","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Brenno","middleName":"Moura","lastName":"Castro","suffix":""},{"id":116890365,"identity":"258ff7b5-e7af-42f2-84c8-eaf6c9e69258","order_by":1,"name":"Marcelo de Miranda Reis","email":"","orcid":"","institution":"Military Institute of Engineering","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marcelo","middleName":"de Miranda","lastName":"Reis","suffix":""},{"id":116890366,"identity":"882d1403-2f65-4d31-bbe5-f264bc2b920b","order_by":2,"name":"Ronaldo Moreira Salles","email":"","orcid":"","institution":"Military Institute of Engineering","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ronaldo","middleName":"Moreira","lastName":"Salles","suffix":""}],"badges":[],"createdAt":"2022-06-21 04:14:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1778885/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1778885/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23484061,"identity":"6b1fddf1-6c5f-496a-b899-319e83560ce8","added_by":"auto","created_at":"2022-07-05 19:14:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2101540,"visible":true,"origin":"","legend":"","description":"","filename":"MANUSCRIPTCOVID19CASTROScientificReports.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1778885/v1_covered.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multi-agent simulation model updating and forecasting for the evaluation of COVID-19 transmission","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1778885/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Multi-agent model, Epidemiological model, Model updating","lastPublishedDoi":"10.21203/rs.3.rs-1778885/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1778885/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Agent-based models have been an emerging approach in epidemiological modelling, specifically in investigating the COVID-19 virus. 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