Analyzing the spatiotemporal effects of meteorological factors on hand, foot and mouth disease using mixed geographically and temporally weighted autoregressive models

Analyzing the spatiotemporal effects of meteorological factors on hand, foot and mouth disease using mixed geographically and temporally weighted autoregressive models | 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 Analyzing the spatiotemporal effects of meteorological factors on hand, foot and mouth disease using mixed geographically and temporally weighted autoregressive models Huiguo Zhang, Geng Chen, Mengqi Chen, Si ang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5578964/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Spatial autocorrelation is an important epidemiological feature of hand, foot, and mouth disease (HFMD). However, few studies have included this feature in the regression relationship between HFMD incidence and driving factors to explore its impact on incidence. In this paper, we propose a mixed geographically and temporally weighted autoregressive (MGTWAR) model to explore the impact of spatial autocorrelation and meteorological factors on the incidence of HFMD among children in Inner Mongolia, China, in 2016. The bootstrap test method was introduced to identify the spatial autocorrelation of HFMD and the meteorological factors that have a global impact on the incidence of HFMD. The results of the analysis show that the spatial autocorrelation of HFMD in children in Inner Mongolia has significant statistical significance, and it has a significant promoting effect on the increase of incidence of HFMD. The impacts of air temperature (AT), air pressure (AP), and average wind speed (AW) on the incidence of HFMD have significant spatiotemporal heterogeneity, and relative humidity (RH) has a global positive influence on HFMD incidence. Overall, the degree of influence of meteorological factors on the incidence of HFMD is in the order of AT > AP > RH > AW. The results show that the influence of spatial autocorrelation on HFMD can not be ignored when exploring the driving factors of HFMD incidence and formulating preventive measures. Health sciences/Medical research/Epidemiology Health sciences/Diseases/Infectious diseases Health sciences/Diseases/Respiratory tract diseases Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 14 May, 2025 Reviews received at journal 08 May, 2025 Reviews received at journal 23 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviewers invited by journal 12 Apr, 2025 Submission checks completed at journal 08 Apr, 2025 First submitted to journal 29 Mar, 2025 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-5578964","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":442131535,"identity":"eae7a4e6-d69c-4c4d-94ef-1b2ce436a22f","order_by":0,"name":"Huiguo Zhang","email":"","orcid":"","institution":"Xinjiang University","correspondingAuthor":false,"prefix":"","firstName":"Huiguo","middleName":"","lastName":"Zhang","suffix":""},{"id":442131536,"identity":"cee50c5c-0f7c-405b-a8a7-e7ae57ea34e5","order_by":1,"name":"Geng Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIie3PsQrCMBCA4TsCukRcz8lXuCziUPBBXCJCuigIroKRDl18gIpP0TcoBJwE17oJBec8gIOCi1vjJphvvp+7A4iiHzQUkHrPtN3lNjBROdyxWCWY7avQNRe8C+kN5oUOLDAT5ibZid6hKWvYJNPWpCs6KRO7zuBo1mM4maVt3yI1MTupjosRoXXtCbi+J82OJtdzcAKGKjaMhQxMVAZzZTnRuH/9okN+GfarWfN4kMbclbXfJAGHfWDS34y/k2+LKIqi//AExDg/uPPVVB8AAAAASUVORK5CYII=","orcid":"","institution":"Xinjiang University","correspondingAuthor":true,"prefix":"","firstName":"Geng","middleName":"","lastName":"Chen","suffix":""},{"id":442131537,"identity":"c2687503-e3ea-4a8a-b4db-fba4d4685c91","order_by":2,"name":"Mengqi Chen","email":"","orcid":"","institution":"Xinjiang University","correspondingAuthor":false,"prefix":"","firstName":"Mengqi","middleName":"","lastName":"Chen","suffix":""},{"id":442131538,"identity":"5ef0b7fc-2e67-46ed-99d0-458c87060d03","order_by":3,"name":"Si ang Wang","email":"","orcid":"","institution":"Xinjiang University","correspondingAuthor":false,"prefix":"","firstName":"Si","middleName":"ang","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-12-04 10:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5578964/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5578964/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-07936-0","type":"published","date":"2025-07-01T15:57:42+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86181098,"identity":"1fa3faa7-e92b-46d0-b154-9d1c03555129","added_by":"auto","created_at":"2025-07-07 16:23:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1914138,"visible":true,"origin":"","legend":"","description":"","filename":"Reports0408.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5578964/v1_covered_8be3d52f-a381-4ff6-879e-964429aed0fc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analyzing the spatiotemporal effects of meteorological factors on hand, foot and mouth disease using mixed geographically and temporally weighted autoregressive models","fulltext":[],"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":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-5578964/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5578964/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Spatial autocorrelation is an important epidemiological feature of hand, foot, and mouth disease (HFMD). However, few studies have included this feature in the regression relationship between HFMD incidence and driving factors to explore its impact on incidence. In this paper, we propose a mixed geographically and temporally weighted autoregressive (MGTWAR) model to explore the impact of spatial autocorrelation and meteorological factors on the incidence of HFMD among children in Inner Mongolia, China, in 2016. The bootstrap test method was introduced to identify the spatial autocorrelation of HFMD and the meteorological factors that have a global impact on the incidence of HFMD. The results of the analysis show that the spatial autocorrelation of HFMD in children in Inner Mongolia has significant statistical significance, and it has a significant promoting effect on the increase of incidence of HFMD. The impacts of air temperature (AT), air pressure (AP), and average wind speed (AW) on the incidence of HFMD have significant spatiotemporal heterogeneity, and relative humidity (RH) has a global positive influence on HFMD incidence. Overall, the degree of influence of meteorological factors on the incidence of HFMD is in the order of AT \u003e AP \u003e RH \u003e AW. 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