Mathematical modeling of public health policy for international travelers (PHPIT): a case study of the COVID-19 pandemic in Thailand

dc.contributor.authorMahd-Adam V.
dc.contributor.authorRotejanaprasert C.
dc.contributor.authorLawpoolsri S.
dc.contributor.authorThammawijaya P.
dc.contributor.authorPan-ngum W.
dc.contributor.correspondenceMahd-Adam V.
dc.contributor.otherMahidol University
dc.date.accessioned2026-02-06T18:32:40Z
dc.date.available2026-02-06T18:32:40Z
dc.date.issued2026-12-01
dc.description.abstractBackground: Following border closures implemented during the COVID-19 pandemic, Thailand subsequently reopened its international borders, employing public health policy for international travelers (PHPIT) to mitigate the importation of COVID-19 cases and minimize potential missed cases. These measures included departure country risk classification, vaccination certificate requirement, pre-departure and entry testing, and quarantine. Methods: To assess the effectiveness of these interventions, we developed a cross-border control model, which integrates cluster analysis and mathematical modeling to estimate reductions in missed cases in Thailand under various scenarios. Results: Our findings indicated that, as a single measure, when compared with implementing no interventions, quarantine for 1, 3, 5, 7, 10, and 14 days reduced missed cases by 45%, 58%, 72%, 80%, 88%, and 94%, respectively. Departure country risk classification reduced missed cases by up to 72% and vaccination certificate requirement by up to 24%. Testing once at 72, 48, 24, or 0 h pre-departure reduced missed cases by 5%, 7%, 10%, and 14% respectively. Entry testing (the “test-and-go” policy) reduced missed cases by 29%. Strategically combining quarantine with other PHPIT measures could achieve a 46–98% reduction in missed cases, with the maximum reduction in missed cases when implementing 14-day quarantine together with pre-departure testing. Conclusions: Quarantine could serve as a standard measure to minimize missed cases and be optimized by a vaccination certificate requirement. Meanwhile, testing and departure country risk classification could be withdrawn due to their minimal effectiveness and potential for discrimination, respectively. The combinations and their optimization should be guided by domestic transmission dynamics, healthcare system capacities, societal perspectives, and economic adaptability. Future PHPIT implementation should incorporate pre-evaluation to balance intervention effectiveness, equity for international travelers, and public health and economic security.
dc.identifier.citationBMC Public Health Vol.26 No.1 (2026)
dc.identifier.doi10.1186/s12889-025-25811-5
dc.identifier.eissn14712458
dc.identifier.pmid41327120
dc.identifier.scopus2-s2.0-105026868720
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/114775
dc.rights.holderSCOPUS
dc.subjectMedicine
dc.titleMathematical modeling of public health policy for international travelers (PHPIT): a case study of the COVID-19 pandemic in Thailand
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105026868720&origin=inward
oaire.citation.issue1
oaire.citation.titleBMC Public Health
oaire.citation.volume26
oairecerif.author.affiliationFaculty of Tropical Medicine, Mahidol University
oairecerif.author.affiliationThailand Ministry of Public Health
oairecerif.author.affiliationMahidol Oxford Tropical Medicine Research Unit

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