Development of a dynamical model to enhance understanding of epidemiology of schistosomiasis in school-aged-children

Development of a dynamical model to enhance understanding of epidemiology of schistosomiasis in school-aged-children | 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 Development of a dynamical model to enhance understanding of epidemiology of schistosomiasis in school-aged-children Amber L Reed, Sekeleghe A Kayuni, Janelisa Musaya, J Russell Stothard, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6172898/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract School-aged-children are most vulnerable to schistosomiasis as exemplified by age-prevalence profiles although current understanding of these patterns needs improvement. Using epidemiological data from the southern shoreline of Lake Malawi, we investigated the dynamics of Schistosoma transmission and the main determinants of Schistosoma infection risk using a transmission dynamic model, considering urogenital and intestinal schistosomiasis respectively. Specifically, we assessed whether the proximity of primary schools to the immediate shoreline was a major geospatial and epidemiological determinant. Cross-sectional parasitology and malacological data previously collected and analysed was used, including age-infection profiles and interpolated predicted snail distributions for the southern part of Lake Malawi shoreline. A disease SEIRS ordinary differential equation model was created, and an observation prevalence model was formed using a binomial sampling distribution using the already published dataset. An optimisation using L-BFGS-B algorithm with upper/lower bounded box constraints was carried out to calibrate the model to find the best parameter values for each infection state transition given the disease model and dataset. The aim was to recapture the age-structure dynamics shown in the observation model representing the already published age-infection profiles. Concerning intestinal schistosomiasis, the best model for Biomphalaria sp. was the use of a single transmission rate for all the school's and no spatial effect. By contrast, for urogenital schistosomiasis, the best model for Bulinus spp. was found when using an independent transmission rate for each school and no spatial effect. There was some evidence that we were able to capture the age-structured dynamics of infection in SAC despite the expected outcome differing to statistical output due to sparse data. Within our study area, we found there was no significant effect on SAC exposure to Schistosoma infection risk based on school distance from the shoreline. Further, there was heterogeneity between schools in transmission rates estimated, although these did not have significantly different confidence intervals. However, schools considered in our study were all relatively close to cercaria infested shorelines. Further studies using a longitudinal cohort study could improve understanding of Schistosoma infection dynamics and allow for improved control method application. Health sciences/Diseases Physical sciences/Mathematics and computing Schistosomiasis Biomphalaria Bulinus Transmission dynamics Optimisation Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryDatasetS1.xls SupplementaryDatasetS2.xls Supplementaryinformation.pdf Cite Share Download PDF Status: Published Journal Publication published 22 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 11 Dec, 2025 Reviews received at journal 23 Nov, 2025 Reviews received at journal 21 Nov, 2025 Reviewers agreed at journal 18 Nov, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers invited by journal 12 Nov, 2025 Submission checks completed at journal 03 Nov, 2025 First submitted to journal 28 Oct, 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. 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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-6172898","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":544293537,"identity":"c3a917ac-5a6f-45e9-b91f-bfd53ab6199a","order_by":0,"name":"Amber L 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school-aged-children","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Schistosomiasis, Biomphalaria, Bulinus, Transmission dynamics, Optimisation","lastPublishedDoi":"10.21203/rs.3.rs-6172898/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6172898/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSchool-aged-children are most vulnerable to schistosomiasis as exemplified by age-prevalence profiles although current understanding of these patterns needs improvement. Using epidemiological data from the southern shoreline of Lake Malawi, we investigated the dynamics of \u003cem\u003eSchistosoma\u003c/em\u003e transmission and the main determinants of \u003cem\u003eSchistosoma\u003c/em\u003e infection risk using a transmission dynamic model, considering urogenital and intestinal schistosomiasis respectively. Specifically, we assessed whether the proximity of primary schools to the immediate shoreline was a major geospatial and epidemiological determinant. Cross-sectional parasitology and malacological data previously collected and analysed was used, including age-infection profiles and interpolated predicted snail distributions for the southern part of Lake Malawi shoreline. A disease SEIRS ordinary differential equation model was created, and an observation prevalence model was formed using a binomial sampling distribution using the already published dataset. An optimisation using L-BFGS-B algorithm with upper/lower bounded box constraints was carried out to calibrate the model to find the best parameter values for each infection state transition given the disease model and dataset. The aim was to recapture the age-structure dynamics shown in the observation model representing the already published age-infection profiles. Concerning intestinal schistosomiasis, the best model for \u003cem\u003eBiomphalaria\u003c/em\u003e sp. was the use of a single transmission rate for all the school's and no spatial effect. By contrast, for urogenital schistosomiasis, the best model for \u003cem\u003eBulinus\u003c/em\u003e spp. was found when using an independent transmission rate for each school and no spatial effect. There was some evidence that we were able to capture the age-structured dynamics of infection in SAC despite the expected outcome differing to statistical output due to sparse data. Within our study area, we found there was no significant effect on SAC exposure to \u003cem\u003eSchistosoma\u003c/em\u003e infection risk based on school distance from the shoreline. Further, there was heterogeneity between schools in transmission rates estimated, although these did not have significantly different confidence intervals. However, schools considered in our study were all relatively close to cercaria infested shorelines. Further studies using a longitudinal cohort study could improve understanding of \u003cem\u003eSchistosoma\u003c/em\u003e infection dynamics and allow for improved control method application.\u003c/p\u003e","manuscriptTitle":"Development of a dynamical model to enhance understanding of epidemiology of schistosomiasis in school-aged-children","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 15:54:57","doi":"10.21203/rs.3.rs-6172898/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-12-11T11:15:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T03:56:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-21T06:43:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257889708490644188731251515488123115571","date":"2025-11-18T06:35:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106193754088441302150209624732264881227","date":"2025-11-13T05:41:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-13T04:52:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-03T12:30:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-28T16:04:57+00:00","index":"","fulltext":""}],"status":"published","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}}],"origin":"","ownerIdentity":"d2c68286-2410-45b7-a64b-063b8069a991","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57909763,"name":"Health sciences/Diseases"},{"id":57909764,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2025-12-29T15:59:44+00:00","versionOfRecord":{"articleIdentity":"rs-6172898","link":"https://doi.org/10.1038/s41598-025-32664-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-22 15:57:15","publishedOnDateReadable":"December 22nd, 2025"},"versionCreatedAt":"2025-11-14 15:54:57","video":"","vorDoi":"10.1038/s41598-025-32664-w","vorDoiUrl":"https://doi.org/10.1038/s41598-025-32664-w","workflowStages":[]},"version":"v1","identity":"rs-6172898","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6172898","identity":"rs-6172898","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}