Epidemic transmission modeling with fractional derivatives and environmental pathogens

dc.contributor.authorKhalighi, Moein
dc.contributor.authorNdaïrou, Faïçal
dc.contributor.authorLahti, Leo
dc.contributor.organizationfi=data-analytiikka|en=Data-analytiikka|
dc.contributor.organization-code1.2.246.10.2458963.20.68940835793
dc.converis.publication-id457935376
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/457935376
dc.date.accessioned2026-01-21T15:14:06Z
dc.date.available2026-01-21T15:14:06Z
dc.description.abstractThis research presents an advanced fractional-order compartmental model designed to delve into the complexities of COVID-19 transmission dynamics, specifically accounting for the influence of environmental pathogens on disease spread. By enhancing the classical compartmental framework, our model distinctively incorporates the effects of order derivatives and environmental shedding mechanisms on the basic reproduction numbers, thus offering a holistic perspective on transmission dynamics. Leveraging fractional calculus, the model adeptly captures the memory effect associated with disease spread, providing an authentic depiction of the virus's real-world propagation patterns. A thorough mathematical analysis confirming the existence, uniqueness and stability of the model's solutions emphasizes its robustness. Furthermore, the numerical simulations, meticulously calibrated with real COVID-19 case data, affirm the model's capacity to emulate observed transmission trends, demonstrating the pivotal role of environmental transmission vectors in shaping public health strategies. The study highlights the critical role of environmental sanitation and targeted interventions in controlling the pandemic's spread, suggesting new insights for research and policy-making in infectious disease management.
dc.identifier.eissn1793-7159
dc.identifier.jour-issn1793-5245
dc.identifier.olddbid214181
dc.identifier.oldhandle10024/197199
dc.identifier.urihttps://www.utupub.fi/handle/11111/56504
dc.identifier.urlhttps://www.worldscientific.com/doi/10.1142/S1793524524500852
dc.identifier.urnURN:NBN:fi-fe2025082790959
dc.language.isoen
dc.okm.affiliatedauthorKhalighi, Moein
dc.okm.affiliatedauthorLahti, Leo
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTD
dc.publisher.countrySingaporeen_GB
dc.publisher.countrySingaporefi_FI
dc.publisher.country-codeSG
dc.publisher.placeSINGAPORE
dc.relation.doi10.1142/S1793524524500852
dc.relation.ispartofjournalInternational Journal of Biomathematics
dc.source.identifierhttps://www.utupub.fi/handle/10024/197199
dc.titleEpidemic transmission modeling with fractional derivatives and environmental pathogens
dc.year.issued2024

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