Evidence map›Paper›PMID 41327120›Full record

ArticleBMC public health2025

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

Vidhyakorn Mahd-Adam, Chawarat Rotejanaprasert, Saranath Lawpoolsri, Panithee Thammawijaya, Wirichada Pan-Ngum

Abstract read
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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Vidhyakorn Mahd-AdamDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand.
Chawarat RotejanaprasertDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand.
Saranath LawpoolsriDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand.
Panithee ThammawijayaDivision of Epidemiology, Department of Disease Control, Ministry of Public Health, Nonthaburi, 11000, Thailand.
Wirichada Pan-NgumDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand. pan@tropmedres.ac.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFollowing 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.

methodsTo 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.

resultsOur 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.

conclusionsQuarantine 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.

Indexed as

COVID-19Health PolicyModels, TheoreticalPandemicsTravelHumansQuarantineSARS-CoV-2ThailandAir travelCOVID-19International travelersMathematical modelPre-implementation evaluationPublic health policyTest-and-goThailand

Identifiers

PMID41327120
PMCPMC12777338

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.