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

TL;DR
This study evaluates Thailand's public health policies for international travelers during the pandemic to reduce missed COVID-19 cases.
Contribution
A cross-border control model integrating cluster analysis and mathematical modeling is introduced to assess the effectiveness of various public health interventions.
Findings
A 14-day quarantine reduced missed cases by 94%, the highest among single interventions.
Combining quarantine with pre-departure testing could reduce missed cases by up to 98%.
Testing and country risk classification had limited effectiveness and potential drawbacks.
Abstract
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. 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. 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…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Travel-related health issues · Viral Infections and Outbreaks Research
