Abstract
In this era of globalization, airline transportation has greatly increased international trade and travel within the World Airport Network (WAN). Unfortunately, this convenience has expanded the scope of infectious disease spread from a local to a worldwide occurrence. Thus, scholars have proposed several methods to measure the distances between airports and define the relationship between the distances and arrival times of infectious diseases in various countries. However, such studies suffer from the following limitations. (1) Only traditional statistical methods or graphical representations were utilized to show that the effective distance performed better than the geographical distance technique. Researchers seldom use the survival model to quantify the actual differences among arrival times via various distance methods. (2) Although scholars have found that most diseases tend to spread via the random walk rather than the shortest path method, this hypothesis may no longer be true because the network has been severally altered due to recent COVID-related travel reductions. Therefore, we used 2017 IATA (International Air Transport Association) to establish an airline network via various chosen path strategies (random walk and shortest path). Then, we employed these two networks to quantify each model’s predictive performance in order to estimate the importation probability function of COVID-19 into various countries. The effective distance model was found to more accurately predict arrival dates of COVID-19 than the geographical distance model. However, if pre-Covid airline data is included, the path of disease spread might not follow the random walk theory due to recent flight suspensions and travel restrictions during the epidemic. Lastly, when testing effective distance, the inverse distance survival model and the Cox model yielded very similar importation risk estimates. The results can help authorities design more effective international epidemic prevention and control strategies.
Highlights
The expansion of global business, recreational travel and the connection of regional economies have led to an increased demand for international travel
The Narita Airport and the Haneda Airport in Tokyo, Japan have a relatively close geographical distance ( 71 km), their effective distance is almost infinite because there are no regular flights between them, which makes it virtually impossible for COVID-19 to be transferred from these two airports by passenger plane
Two types of effective distance based on historical airline data (2017 International Air Transport Association (IATA)) and airport connection links were used to compare the predictability of the date of disease arrival
Summary
The expansion of global business, recreational travel and the connection of regional economies have led to an increased demand for international travel. The Narita Airport and the Haneda Airport in Tokyo, Japan have a relatively close geographical distance ( 71 km), their effective distance is almost infinite because there are no regular flights between them, which makes it virtually impossible for COVID-19 to be transferred from these two airports by passenger plane This new method allows researchers to convert airline passenger volume into a metric form that can be applied in epidemiological studies to predict the arrival dates of various types of diseases. It must be noted that due to the recent decrease in air traffic volume because of travel restrictions, the effective distance estimator and the random walk path may not be the most effective techniques for analysis of disease spread To account for these limitations, we compared the performance of various distances and path selection prediction models. To account for these limitations, we compared the performance of various distances and path selection prediction models. (1) The effective distance was calculated based on the IATA flight database, and the geographic distances was calculated among the WAN airports. (2) We utilized the different path approaches (random walk and shortest path) to establish the airport network. (3) two survival models were employed to quantify the prediction performance for importation risk
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