Impact of different control policies for COVID-19 outbreak on the air transportation industry: A comparison between China, the U.S. and Singapore
Many countries have been implementing various control measures with different strictness levels to prevent the coronavirus disease 2019 (COVID-19) from spreading. With the great reduction in human mobility and daily activities, considerable impacts have been imposed on the global air transportation...
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Published in | PloS one Vol. 16; no. 3; p. e0248361 |
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Format | Journal Article |
Language | English |
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16.03.2021
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Abstract | Many countries have been implementing various control measures with different strictness levels to prevent the coronavirus disease 2019 (COVID-19) from spreading. With the great reduction in human mobility and daily activities, considerable impacts have been imposed on the global air transportation industry. This study applies a hybrid SARIMA-based intervention model to measure the differences in the impacts of different control measures implemented in China, the U.S. and Singapore on air passenger and air freight traffic. To explore the effect of time span for the measures to be in force, two scenarios are invented, namely a long-term intervention and a short-term intervention, and predictions are made till the end of 2020 for all three countries under both scenarios. As a result, predictive patterns of the selected metrics for the three countries are rather different. China is predicted to have the mildest economic impact on the air transportation industry in this year in terms of air passenger revenue and air cargo traffic, provided that the control measures were prompt and effective. The U.S. would suffer from a far-reaching impact on the industry if the same control measures are maintained. More uncertainties are found for Singapore, as it is strongly associated with international travel demands. Suggestions are made for the three countries and the rest of the world on how to seek a balance between the strictness of control measures and the potential long-term industrial losses. |
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AbstractList | [...]control measures such as travel restrictions, city lock-down, cordon sanitaire, and night curfew have been enforced in many countries. According to the predictions by International Air Transport Association (IATA), the COVID-19 pandemic may cause a total loss of 21.5 billion USD in 2020 for European airlines, and the predicted losses for Asia Pacific airline markets range from 47 billion to 57 billion USD for different scenarios of COVID-19 evolvements [11, 12]. [...]predicting the industrial losses is subject to quantitatively understanding the trade-offs between the strictness of different types of control policies and the duration that certain policies need to be implemented to be able to constrain local epidemic situation. [...]it is vital to quantitatively assess the differences in the impacts of different control policies (or confinement concepts) on the air transportation industry under different effective periods to guide the authorities to find the balance for their own benefits. According to the model results, China is predicted to undergo a relatively milder impact in air transportation industry in the long run, while Singapore and the U.S. would suffer a deeper and more confounding effects from the confinements. Many countries have been implementing various control measures with different strictness levels to prevent the coronavirus disease 2019 (COVID-19) from spreading. With the great reduction in human mobility and daily activities, considerable impacts have been imposed on the global air transportation industry. This study applies a hybrid SARIMA-based intervention model to measure the differences in the impacts of different control measures implemented in China, the U.S. and Singapore on air passenger and air freight traffic. To explore the effect of time span for the measures to be in force, two scenarios are invented, namely a long-term intervention and a short-term intervention, and predictions are made till the end of 2020 for all three countries under both scenarios. As a result, predictive patterns of the selected metrics for the three countries are rather different. China is predicted to have the mildest economic impact on the air transportation industry in this year in terms of air passenger revenue and air cargo traffic, provided that the control measures were prompt and effective. The U.S. would suffer from a far-reaching impact on the industry if the same control measures are maintained. More uncertainties are found for Singapore, as it is strongly associated with international travel demands. Suggestions are made for the three countries and the rest of the world on how to seek a balance between the strictness of control measures and the potential long-term industrial losses.Many countries have been implementing various control measures with different strictness levels to prevent the coronavirus disease 2019 (COVID-19) from spreading. With the great reduction in human mobility and daily activities, considerable impacts have been imposed on the global air transportation industry. This study applies a hybrid SARIMA-based intervention model to measure the differences in the impacts of different control measures implemented in China, the U.S. and Singapore on air passenger and air freight traffic. To explore the effect of time span for the measures to be in force, two scenarios are invented, namely a long-term intervention and a short-term intervention, and predictions are made till the end of 2020 for all three countries under both scenarios. As a result, predictive patterns of the selected metrics for the three countries are rather different. China is predicted to have the mildest economic impact on the air transportation industry in this year in terms of air passenger revenue and air cargo traffic, provided that the control measures were prompt and effective. The U.S. would suffer from a far-reaching impact on the industry if the same control measures are maintained. More uncertainties are found for Singapore, as it is strongly associated with international travel demands. Suggestions are made for the three countries and the rest of the world on how to seek a balance between the strictness of control measures and the potential long-term industrial losses. Many countries have been implementing various control measures with different strictness levels to prevent the coronavirus disease 2019 (COVID-19) from spreading. With the great reduction in human mobility and daily activities, considerable impacts have been imposed on the global air transportation industry. This study applies a hybrid SARIMA-based intervention model to measure the differences in the impacts of different control measures implemented in China, the U.S. and Singapore on air passenger and air freight traffic. To explore the effect of time span for the measures to be in force, two scenarios are invented, namely a long-term intervention and a short-term intervention, and predictions are made till the end of 2020 for all three countries under both scenarios. As a result, predictive patterns of the selected metrics for the three countries are rather different. China is predicted to have the mildest economic impact on the air transportation industry in this year in terms of air passenger revenue and air cargo traffic, provided that the control measures were prompt and effective. The U.S. would suffer from a far-reaching impact on the industry if the same control measures are maintained. More uncertainties are found for Singapore, as it is strongly associated with international travel demands. Suggestions are made for the three countries and the rest of the world on how to seek a balance between the strictness of control measures and the potential long-term industrial losses. [...]control measures such as travel restrictions, city lock-down, cordon sanitaire, and night curfew have been enforced in many countries. According to the predictions by International Air Transport Association (IATA), the COVID-19 pandemic may cause a total loss of 21.5 billion USD in 2020 for European airlines, and the predicted losses for Asia Pacific airline markets range from 47 billion to 57 billion USD for different scenarios of COVID-19 evolvements [11, 12]. [...]predicting the industrial losses is subject to quantitatively understanding the trade-offs between the strictness of different types of control policies and the duration that certain policies need to be implemented to be able to constrain local epidemic situation. [...]it is vital to quantitatively assess the differences in the impacts of different control policies (or confinement concepts) on the air transportation industry under different effective periods to guide the authorities to find the balance for their own benefits. According to the model results, China is predicted to undergo a relatively milder impact in air transportation industry in the long run, while Singapore and the U.S. would suffer a deeper and more confounding effects from the confinements. |
Audience | Academic |
Author | Yang, Lili Meng, Fanyu Gong, Wenwu Li, Xian Zeng, Yiping Liang, Jun |
AuthorAffiliation | University of Rochester, UNITED STATES 3 School of International Development, University of East Anglia, Norwich, United Kingdom 1 Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, People’s Republic of China 2 Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, People’s Republic of China |
AuthorAffiliation_xml | – name: 1 Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, People’s Republic of China – name: University of Rochester, UNITED STATES – name: 3 School of International Development, University of East Anglia, Norwich, United Kingdom – name: 2 Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, People’s Republic of China |
Author_xml | – sequence: 1 givenname: Fanyu surname: Meng fullname: Meng, Fanyu – sequence: 2 givenname: Wenwu surname: Gong fullname: Gong, Wenwu – sequence: 3 givenname: Jun surname: Liang fullname: Liang, Jun – sequence: 4 givenname: Xian surname: Li fullname: Li, Xian – sequence: 5 givenname: Yiping surname: Zeng fullname: Zeng, Yiping – sequence: 6 givenname: Lili surname: Yang fullname: Yang, Lili |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33724996$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Air transportation Air transportation industry Aircraft Aircraft - economics Airlines Aviation China Coronaviruses COVID-19 COVID-19 - pathology COVID-19 - transmission COVID-19 - virology Databases, Factual Disease Outbreaks Disease transmission Earth Sciences Economic aspects Engineering and Technology Epidemics Humans Industry International aspects Medicine and Health Sciences Mobility Models, Statistical Pandemics People and Places Physical Sciences Policies Policy Research and Analysis Methods SARS-CoV-2 - isolation & purification Severe acute respiratory syndrome coronavirus 2 Singapore Social aspects Social Sciences Software Supervision Time series Transportation industry Transportation services Travel United States Viral diseases |
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Title | Impact of different control policies for COVID-19 outbreak on the air transportation industry: A comparison between China, the U.S. and Singapore |
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