Chan, Chun-HsiangChun-HsiangChanWen, Tzai-HungTzai-HungWen2025-12-102025-12-102025-10https://www.scopus.com/pages/publications/85215420099https://scholars.lib.ntu.edu.tw/handle/123456789/734497Air travel is one of the main ways in which contagious diseases spread across regions. State-of-the-art platforms and apps cannot timely and customized estimate exposure risk for air passengers. This study integrated time-varying flight schedules, connecting airports, and epidemic situations in airport catchment areas for estimating a traveler's exposure risk during the user-defined flight journey and applying to the timely exposure risk during air travel (TERAT) for a spatial decision support system (SDSS). We leveraged epidemic information and dynamic flight schedules to estimate personalized and timely exposure risk. Flight frequency and arrival time of all inbound flights within 6 h before and after the current time were encompassed to determine the potentially infected passenger sources. We estimated the timely airport exposure risk for the user's destination airport and its top 10 importation risk origin airports and demonstrated the top 10 risk final destination airports from the user's destination airport. Two real-world scenarios showed that direct flight and transfer air passengers were exposed to time-varying risks at different travel stages; additionally, all high-risk exposure routes were highlighted. To our knowledge, TERAT is the first attempt to leverage real-world dynamic epidemiological data and flight schedules to estimate time-varying exposure risk for user-defined routes. We further converted airport exposure risk into four levels for determining the personal protection measures to facilitate the usage of exposure risk applications. Therefore, air passengers can protect themselves when facing passengers from high-risk areas in advance.air travelAirport catchment areaconnecting airportpersonalized risktimely exposure risk estimationjournal article10.1109/tcss.2024.3523336