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...

Full description

Saved in:
Bibliographic Details
Published inPloS one Vol. 16; no. 3; p. e0248361
Main Authors Meng, Fanyu, Gong, Wenwu, Liang, Jun, Li, Xian, Zeng, Yiping, Yang, Lili
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 16.03.2021
Public Library of Science (PLoS)
Subjects
Online AccessGet full text

Cover

Loading…
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.
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
BookMark eNqNk2uL1DAUhousuBf9B6IBQRScMUnbNNkPwjDeBhYWXHe_htM0ncnaSWqSqvsz_MdmbrKzLCL90HL6vO-5cM5xdmCd1Vn2lOAxySvy9toN3kI37lN4jGnBc0YeZEdE5HTEKM4Pbn0fZschXGNc5pyxR9lhnle0EIIdZb9nyx5URK5FjWlb7bWNSDkbvetQ7zqjjA6odR5Nz69m70dEIDfE2mv4hpxFcaERGI-iBxt65yNEk8LGNkOI_uYUTZJZyuBNSOFax59aWzRdGAtv1uLL8cUYgW3QhbFzSA76cfawhS7oJ9v3SXb58cPX6efR2fmn2XRyNlJVyeNIcaVKKoqS1QRTnDrlPMd1pau6JFCIHAtORV3iqlVAsNCUUqGaGpoCM13S_CR7vvHtOxfkdppB0hITnnNCeSJmG6JxcC17b5bgb6QDI9cB5-cSfDSq01IDY0AorTmjRc2EAOBNQSDVxAVlVfJ6t8021EvdqDRmD92e6f4faxZy7n7ISrAcF0UyeLU18O77oEOUSxOU7jqw2g3ruinFBS1Xdb-4g97f3ZaaQ2rA2NalvGplKiesLCnGZJ12fA-VnkYvTdoT3ZoU3xO83hOsdkn_inMYQpCziy__z55f7bMvb7ELDV1cBNcNq30L--Cz25P-O-LdzifgdAMo70LwupXKbPY2tWY6SbBcHdhuaHJ1YHJ7YElc3BHv_P8p-wPmbCfV
CitedBy_id crossref_primary_10_1016_j_trip_2022_100718
crossref_primary_10_1371_journal_pone_0267487
crossref_primary_10_1080_17938120_2023_2254187
crossref_primary_10_3390_ijerph191912287
crossref_primary_10_2139_ssrn_4070837
crossref_primary_10_1016_j_cstp_2024_101288
crossref_primary_10_1016_j_tranpol_2023_04_019
crossref_primary_10_1016_j_eiar_2022_106831
crossref_primary_10_2139_ssrn_4840751
crossref_primary_10_1016_j_fmre_2022_05_007
crossref_primary_10_3390_economies12100258
crossref_primary_10_3390_ijerph182312790
crossref_primary_10_1016_j_tranpol_2021_05_013
crossref_primary_10_1080_19475683_2024_2418584
crossref_primary_10_2139_ssrn_3911364
crossref_primary_10_1016_j_trd_2022_103206
crossref_primary_10_3233_JIFS_212862
crossref_primary_10_1080_24694452_2022_2130143
crossref_primary_10_3390_su15021525
crossref_primary_10_1371_journal_pone_0276276
crossref_primary_10_1007_s00285_024_02082_z
crossref_primary_10_2139_ssrn_4506956
crossref_primary_10_1016_j_ajsl_2023_10_003
crossref_primary_10_1016_j_retrec_2023_101298
crossref_primary_10_1016_j_tranpol_2025_01_022
Cites_doi 10.1198/106186005X77243
10.1111/j.1467-9892.2005.00466.x
10.1300/J098v08n01_04
10.1017/S0266466612000345
10.1073/pnas.2002616117
10.1016/j.jairtraman.2018.04.001
10.1016/j.enpol.2012.05.026
10.1089/hs.2018.0115
10.1016/S0261-5177(02)00009-2
10.2307/1912773
10.1016/S0167-7152(95)00233-2
10.1080/01621459.1975.10480264
10.1080/01621459.1962.10500812
10.1016/j.tranpol.2020.01.003
10.1111/risa.12679
10.1016/j.tre.2018.12.005
10.1504/IJIOME.2007.015282
10.1038/s41562-020-0896-8
10.3390/jcm9020462
10.1080/18128600802591210
10.1126/science.aba9757
10.1007/s11135-010-9338-4
10.1016/j.tourman.2013.10.008
10.1038/s41598-021-92399-2
10.1016/j.ijid.2020.03.031
10.1038/s41597-020-00734-5
10.1007/s11269-017-1825-0
10.1016/S0140-6736(20)30627-9
10.1016/j.jmva.2018.11.016
10.1080/10941661003630001
10.1126/science.abb4218
10.1016/j.tourman.2006.01.003
ContentType Journal Article
Copyright COPYRIGHT 2021 Public Library of Science
2021 Meng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2021 Meng et al 2021 Meng et al
Copyright_xml – notice: COPYRIGHT 2021 Public Library of Science
– notice: 2021 Meng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: 2021 Meng et al 2021 Meng et al
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
IOV
ISR
3V.
7QG
7QL
7QO
7RV
7SN
7SS
7T5
7TG
7TM
7U9
7X2
7X7
7XB
88E
8AO
8C1
8FD
8FE
8FG
8FH
8FI
8FJ
8FK
ABJCF
ABUWG
AEUYN
AFKRA
ARAPS
ATCPS
AZQEC
BBNVY
BENPR
BGLVJ
BHPHI
C1K
CCPQU
COVID
D1I
DWQXO
FR3
FYUFA
GHDGH
GNUQQ
H94
HCIFZ
K9.
KB.
KB0
KL.
L6V
LK8
M0K
M0S
M1P
M7N
M7P
M7S
NAPCQ
P5Z
P62
P64
PATMY
PDBOC
PHGZM
PHGZT
PIMPY
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQQKQ
PQUKI
PTHSS
PYCSY
RC3
7X8
5PM
DOA
DOI 10.1371/journal.pone.0248361
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
Gale In Context: Opposing Viewpoints
Gale In Context: Science
ProQuest Central (Corporate)
Animal Behavior Abstracts
Bacteriology Abstracts (Microbiology B)
Biotechnology Research Abstracts
Nursing & Allied Health Database
Ecology Abstracts
Entomology Abstracts (Full archive)
Immunology Abstracts
Meteorological & Geoastrophysical Abstracts
Nucleic Acids Abstracts
Virology and AIDS Abstracts
Agricultural Science Collection
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Medical Database (Alumni Edition)
ProQuest Pharma Collection
Public Health Database
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Natural Science Collection
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
Materials Science & Engineering Collection
ProQuest Central (Alumni Edition)
ProQuest One Sustainability
ProQuest Central UK/Ireland
Advanced Technologies & Aerospace Collection
Agricultural & Environmental Science Collection
ProQuest Central Essentials
Biological Science Collection
ProQuest Central
Technology Collection
Natural Science Collection
Environmental Sciences and Pollution Management
ProQuest One Community College
Coronavirus Research Database
ProQuest Materials Science Collection
ProQuest Central Korea
Engineering Research Database
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
AIDS and Cancer Research Abstracts
SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
Materials Science Database
Nursing & Allied Health Database (Alumni Edition)
Meteorological & Geoastrophysical Abstracts - Academic
ProQuest Engineering Collection
ProQuest Biological Science Collection
Agricultural Science Database
Health & Medical Collection (Alumni Edition)
Medical Database
Algology Mycology and Protozoology Abstracts (Microbiology C)
Biological Science Database
Engineering Database
Nursing & Allied Health Premium
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
Biotechnology and BioEngineering Abstracts
Environmental Science Database
Materials Science Collection
ProQuest Central Premium
ProQuest One Academic (New)
Publicly Available Content Database
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
ProQuest One Health & Nursing
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
Engineering Collection
Environmental Science Collection
Genetics Abstracts
MEDLINE - Academic
PubMed Central (Full Participant titles)
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
Agricultural Science Database
Publicly Available Content Database
ProQuest Central Student
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
Nucleic Acids Abstracts
SciTech Premium Collection
Environmental Sciences and Pollution Management
ProQuest One Applied & Life Sciences
ProQuest One Sustainability
Health Research Premium Collection
Meteorological & Geoastrophysical Abstracts
Natural Science Collection
Health & Medical Research Collection
Biological Science Collection
ProQuest Central (New)
ProQuest Medical Library (Alumni)
Engineering Collection
Advanced Technologies & Aerospace Collection
Engineering Database
Virology and AIDS Abstracts
ProQuest Biological Science Collection
ProQuest One Academic Eastern Edition
Agricultural Science Collection
Coronavirus Research Database
ProQuest Hospital Collection
ProQuest Technology Collection
Health Research Premium Collection (Alumni)
Biological Science Database
Ecology Abstracts
ProQuest Hospital Collection (Alumni)
Biotechnology and BioEngineering Abstracts
Environmental Science Collection
Entomology Abstracts
Nursing & Allied Health Premium
ProQuest Health & Medical Complete
ProQuest One Academic UKI Edition
Environmental Science Database
ProQuest Nursing & Allied Health Source (Alumni)
Engineering Research Database
ProQuest One Academic
Meteorological & Geoastrophysical Abstracts - Academic
ProQuest One Academic (New)
Technology Collection
Technology Research Database
ProQuest One Academic Middle East (New)
Materials Science Collection
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Natural Science Collection
ProQuest Pharma Collection
ProQuest Central
ProQuest Health & Medical Research Collection
Genetics Abstracts
ProQuest Engineering Collection
Biotechnology Research Abstracts
Health and Medicine Complete (Alumni Edition)
ProQuest Central Korea
Bacteriology Abstracts (Microbiology B)
Algology Mycology and Protozoology Abstracts (Microbiology C)
Agricultural & Environmental Science Collection
AIDS and Cancer Research Abstracts
Materials Science Database
ProQuest Materials Science Collection
ProQuest Public Health
ProQuest Nursing & Allied Health Source
ProQuest SciTech Collection
Advanced Technologies & Aerospace Database
ProQuest Medical Library
Animal Behavior Abstracts
Materials Science & Engineering Collection
Immunology Abstracts
ProQuest Central (Alumni)
MEDLINE - Academic
DatabaseTitleList Agricultural Science Database
MEDLINE - Academic
MEDLINE





CrossRef
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 3
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
– sequence: 4
  dbid: 8FG
  name: ProQuest Technology Collection
  url: https://search.proquest.com/technologycollection1
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Sciences (General)
DocumentTitleAlternate Impact of different control measures for COVID-19 outbreak on the air transportation industry
EISSN 1932-6203
ExternalDocumentID 2501838128
oai_doaj_org_article_ea66a122b8624b699aa8d41a88389267
PMC7963044
A655200144
33724996
10_1371_journal_pone_0248361
Genre Research Support, Non-U.S. Gov't
Journal Article
Comparative Study
GeographicLocations United States
China
Singapore
United Kingdom--UK
Asia
United States--US
GeographicLocations_xml – name: Singapore
– name: China
– name: United States
– name: Asia
– name: United Kingdom--UK
– name: United States--US
GrantInformation_xml – fundername: ;
  grantid: 71771113
– fundername: ;
  grantid: 2019YFC0810705
– fundername: ;
  grantid: Y01621803
– fundername: ;
  grantid: 2018YFC0807000
GroupedDBID ---
123
29O
2WC
53G
5VS
7RV
7X2
7X7
7XC
88E
8AO
8C1
8CJ
8FE
8FG
8FH
8FI
8FJ
A8Z
AAFWJ
AAUCC
AAWOE
AAYXX
ABDBF
ABIVO
ABJCF
ABUWG
ACGFO
ACIHN
ACIWK
ACPRK
ACUHS
ADBBV
AEAQA
AENEX
AEUYN
AFKRA
AFPKN
AFRAH
AHMBA
ALIPV
ALMA_UNASSIGNED_HOLDINGS
AOIJS
APEBS
ARAPS
ATCPS
BAWUL
BBNVY
BCNDV
BENPR
BGLVJ
BHPHI
BKEYQ
BPHCQ
BVXVI
BWKFM
CCPQU
CITATION
CS3
D1I
D1J
D1K
DIK
DU5
E3Z
EAP
EAS
EBD
EMOBN
ESX
EX3
F5P
FPL
FYUFA
GROUPED_DOAJ
GX1
HCIFZ
HH5
HMCUK
HYE
IAO
IEA
IGS
IHR
IHW
INH
INR
IOV
IPY
ISE
ISR
ITC
K6-
KB.
KQ8
L6V
LK5
LK8
M0K
M1P
M48
M7P
M7R
M7S
M~E
NAPCQ
O5R
O5S
OK1
OVT
P2P
P62
PATMY
PDBOC
PHGZM
PHGZT
PIMPY
PQQKQ
PROAC
PSQYO
PTHSS
PV9
PYCSY
RNS
RPM
RZL
SV3
TR2
UKHRP
WOQ
WOW
~02
~KM
ADRAZ
CGR
CUY
CVF
ECM
EIF
IPNFZ
NPM
PJZUB
PPXIY
PQGLB
RIG
BBORY
PMFND
3V.
7QG
7QL
7QO
7SN
7SS
7T5
7TG
7TM
7U9
7XB
8FD
8FK
AZQEC
C1K
COVID
DWQXO
FR3
GNUQQ
H94
K9.
KL.
M7N
P64
PKEHL
PQEST
PQUKI
RC3
7X8
5PM
PUEGO
-
02
AAPBV
ABPTK
ADACO
BBAFP
KM
ID FETCH-LOGICAL-c758t-c8cc529456b10209328830b7e7b51a49309829b507fca109e2229cdbad406e523
IEDL.DBID M48
ISSN 1932-6203
IngestDate Fri Nov 26 17:12:47 EST 2021
Wed Aug 27 01:21:05 EDT 2025
Thu Aug 21 14:05:14 EDT 2025
Fri Jul 11 05:14:11 EDT 2025
Fri Jul 25 10:22:34 EDT 2025
Tue Jun 17 20:52:32 EDT 2025
Tue Jun 10 20:37:22 EDT 2025
Fri Jun 27 04:00:17 EDT 2025
Fri Jun 27 04:23:44 EDT 2025
Thu May 22 21:15:46 EDT 2025
Mon Jul 21 06:01:57 EDT 2025
Tue Jul 01 00:41:34 EDT 2025
Thu Apr 24 23:02:01 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
License This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Creative Commons Attribution License
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c758t-c8cc529456b10209328830b7e7b51a49309829b507fca109e2229cdbad406e523
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
Competing Interests: The authors have declared that no competing interests exist.
JL and XL also contributed equally to this work.
OpenAccessLink https://www.proquest.com/docview/2501838128?pq-origsite=%requestingapplication%
PMID 33724996
PQID 2501838128
PQPubID 1436336
PageCount e0248361
ParticipantIDs plos_journals_2501838128
doaj_primary_oai_doaj_org_article_ea66a122b8624b699aa8d41a88389267
pubmedcentral_primary_oai_pubmedcentral_nih_gov_7963044
proquest_miscellaneous_2502204258
proquest_journals_2501838128
gale_infotracmisc_A655200144
gale_infotracacademiconefile_A655200144
gale_incontextgauss_ISR_A655200144
gale_incontextgauss_IOV_A655200144
gale_healthsolutions_A655200144
pubmed_primary_33724996
crossref_citationtrail_10_1371_journal_pone_0248361
crossref_primary_10_1371_journal_pone_0248361
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2021-03-16
PublicationDateYYYYMMDD 2021-03-16
PublicationDate_xml – month: 03
  year: 2021
  text: 2021-03-16
  day: 16
PublicationDecade 2020
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: San Francisco
– name: San Francisco, CA USA
PublicationTitle PloS one
PublicationTitleAlternate PLoS One
PublicationYear 2021
Publisher Public Library of Science
Public Library of Science (PLoS)
Publisher_xml – name: Public Library of Science
– name: Public Library of Science (PLoS)
References Jong-Min Kim (pone.0248361.ref026) 2020
S Mehdizadeh (pone.0248361.ref022) 2017; 32
Yu Wei Chang (pone.0248361.ref033) 2010; 15
CR Wells (pone.0248361.ref003) 2020; 117
pone.0248361.ref028
HJ Wu (pone.0248361.ref052) 2020; 82
pone.0248361.ref045
pone.0248361.ref046
Ching-Fu Chen (pone.0248361.ref032) 2009; 5
pone.0248361.ref047
pone.0248361.ref004
pone.0248361.ref048
Zudi Lu (pone.0248361.ref021) 1996; 30
Carey Goh (pone.0248361.ref031) 2002; 23
Shuojiang Xu (pone.0248361.ref014) 2019; 122
Erdogan Koc (pone.0248361.ref036) 2007; 28
M Chinazzi (pone.0248361.ref051) 2020; 368
N Gershenfeld (pone.0248361.ref016)
Ying-Chih Chen (pone.0248361.ref041) 2008; 8
A Remuzzi (pone.0248361.ref002) 2020; 395
Shuying Li (pone.0248361.ref040) 2017; 37
E Shim (pone.0248361.ref013) 2020; 93
pone.0248361.ref012
YC Chang (pone.0248361.ref053) 2020; 87
Xingyu Zhang (pone.0248361.ref034) 2014; 2
B Xu (pone.0248361.ref044) 2020; 7
Wai Hong Kan Tsui (pone.0248361.ref018) 2014; 42
pone.0248361.ref010
pone.0248361.ref011
Marc C. Gelhausen (pone.0248361.ref035) 2018; 71
MUG Kraemer (pone.0248361.ref009) 2020; 368
G. E. P. Box (pone.0248361.ref039) 1975; 70
pone.0248361.ref050
Yuanyuan Wang (pone.0248361.ref017) 2012; 48
Brooks Chris (pone.0248361.ref027)
James E. Payne (pone.0248361.ref042) 2007; 2
George E. P. Box (pone.0248361.ref038) 1976
Heesoo Joo (pone.0248361.ref030) 2019; 17
pone.0248361.ref005
Friedman Milton (pone.0248361.ref015) 1962; 57
Robert F Engle (pone.0248361.ref020) 1982; 50
pone.0248361.ref049
pone.0248361.ref007
pone.0248361.ref008
B Tang (pone.0248361.ref043) 2020; 9
pone.0248361.ref023
DB Guan (pone.0248361.ref001) 2020; 4
S Hörmann (pone.0248361.ref025) 2013; 29
Peter C. B. Phillips (pone.0248361.ref037) 2006; 27
Paul Fearnhead (pone.0248361.ref024) 2005; 14
Jennifer C. H. Min (pone.0248361.ref029) 2011; 45
Y Kang (pone.0248361.ref006) 2020; 7
Kantz Holger (pone.0248361.ref019)
References_xml – volume: 14
  start-page: 751
  issue: 4
  year: 2005
  ident: pone.0248361.ref024
  article-title: Using random Quasi-Monte-Carlo within particle Filters, with application to financial time series
  publication-title: Journal of Computational and Graphical Statistics
  doi: 10.1198/106186005X77243
– volume: 27
  start-page: 289
  issue: 2
  year: 2006
  ident: pone.0248361.ref037
  article-title: Inference in autoregression under heteroskedasticity
  publication-title: Journal of Time Series Analysis
  doi: 10.1111/j.1467-9892.2005.00466.x
– volume: 8
  start-page: 31
  issue: 1
  year: 2008
  ident: pone.0248361.ref041
  article-title: A study on the impact of SARS on the forecast of visitor arrivals to China
  publication-title: Journal of Asia-Pacific Business
  doi: 10.1300/J098v08n01_04
– volume: 29
  start-page: 267
  issue: 2
  year: 2013
  ident: pone.0248361.ref025
  article-title: A functional version of the ARCH model
  publication-title: Econometric Theory
  doi: 10.1017/S0266466612000345
– volume: 117
  start-page: 7504
  issue: 13
  year: 2020
  ident: pone.0248361.ref003
  article-title: Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak
  publication-title: Proceedings of the National Academy of Sciences of the United States of America
  doi: 10.1073/pnas.2002616117
– ident: pone.0248361.ref012
– volume: 71
  start-page: 140
  year: 2018
  ident: pone.0248361.ref035
  article-title: A new direct demand model of long-term forecasting air passengers and air transport movements at German airports
  publication-title: Journal of Air Transport Management
  doi: 10.1016/j.jairtraman.2018.04.001
– volume: 7
  start-page: 1
  issue: 1
  year: 2020
  ident: pone.0248361.ref044
  article-title: Epidemiological data from the COVID-19 outbreak, real-time case information
  publication-title: Scientific data
– volume: 48
  start-page: 284
  year: 2012
  ident: pone.0248361.ref017
  article-title: Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China
  publication-title: Energy Policy
  doi: 10.1016/j.enpol.2012.05.026
– volume: 17
  start-page: 100
  issue: 2
  year: 2019
  ident: pone.0248361.ref030
  article-title: Economic Impact of the 2015 MERS Outbreak on the Republic of Korea’s Tourism-Related Industries
  publication-title: Health Security
  doi: 10.1089/hs.2018.0115
– ident: pone.0248361.ref050
– volume: 23
  start-page: 499
  issue: 5
  year: 2002
  ident: pone.0248361.ref031
  article-title: Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention
  publication-title: Tourism Management
  doi: 10.1016/S0261-5177(02)00009-2
– ident: pone.0248361.ref048
– volume: 50
  start-page: 987
  issue: 4
  year: 1982
  ident: pone.0248361.ref020
  article-title: Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
  publication-title: Econometrica
  doi: 10.2307/1912773
– volume: 30
  start-page: 305
  issue: 4
  year: 1996
  ident: pone.0248361.ref021
  article-title: A note on geometric ergodicity of autoregressive conditional heteroscedasticity (ARCH) model
  publication-title: Statistics and Probability Letters
  doi: 10.1016/S0167-7152(95)00233-2
– volume: 70
  start-page: 70
  issue: 349
  year: 1975
  ident: pone.0248361.ref039
  article-title: Intervention analysis with applications to economic and environmental problems
  publication-title: Journal of the American Statistical Association
  doi: 10.1080/01621459.1975.10480264
– volume: 57
  start-page: 729
  issue: 300
  year: 1962
  ident: pone.0248361.ref015
  article-title: The interpolation of time series by related series
  publication-title: Journal of the American Statistical Association
  doi: 10.1080/01621459.1962.10500812
– volume: 87
  start-page: 51
  year: 2020
  ident: pone.0248361.ref053
  article-title: Identifying competitive position for ten Asian aviation hubs
  publication-title: Transport Policy
  doi: 10.1016/j.tranpol.2020.01.003
– volume: 37
  start-page: 1287
  issue: 7
  year: 2017
  ident: pone.0248361.ref040
  article-title: Dynamic forecasting conditional probability of bombing attacks based on time-series and intervention analysis
  publication-title: Risk Analysis
  doi: 10.1111/risa.12679
– ident: pone.0248361.ref011
– volume: 122
  start-page: 169
  year: 2019
  ident: pone.0248361.ref014
  article-title: Forecasting the demand of the aviation industry using hybrid time series SARIMA-SVR approach
  publication-title: Transportation Research Part E: Logistics and Transportation Review
  doi: 10.1016/j.tre.2018.12.005
– ident: pone.0248361.ref005
– ident: pone.0248361.ref047
– start-page: 185
  volume-title: Nonlinear time series analysis
  ident: pone.0248361.ref019
– volume: 2
  start-page: 167
  issue: 2
  year: 2007
  ident: pone.0248361.ref042
  article-title: Modelling and forecasting airport passengers: a case study for an introductory forecasting course
  publication-title: International Journal of Information and Operations Management Education
  doi: 10.1504/IJIOME.2007.015282
– volume: 4
  start-page: 577
  issue: 6
  year: 2020
  ident: pone.0248361.ref001
  article-title: Global supply-chain effects of COVID-19 control measures
  publication-title: Nature Human Behaviour. Nature Human Behaviour
  doi: 10.1038/s41562-020-0896-8
– volume: 9
  issue: 2
  year: 2020
  ident: pone.0248361.ref043
  article-title: Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions
  publication-title: Journal of Clinical Medicine
  doi: 10.3390/jcm9020462
– volume: 5
  start-page: 125
  issue: 2
  year: 2009
  ident: pone.0248361.ref032
  article-title: Seasonal ARIMA forecasting of inbound air travel arrivals to Taiwan
  publication-title: Transportmetrica
  doi: 10.1080/18128600802591210
– ident: pone.0248361.ref010
– volume: 368
  start-page: 395
  issue: 6489
  year: 2020
  ident: pone.0248361.ref051
  article-title: The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
  publication-title: Science
  doi: 10.1126/science.aba9757
– volume: 45
  start-page: 91
  year: 2011
  ident: pone.0248361.ref029
  article-title: Intervention analysis of SARS on Japanese tourism demand for Taiwan
  publication-title: Quality Quantity
  doi: 10.1007/s11135-010-9338-4
– start-page: 461
  volume-title: Introductory econometrics for finance
  ident: pone.0248361.ref027
– ident: pone.0248361.ref004
– volume: 42
  start-page: 62
  year: 2014
  ident: pone.0248361.ref018
  article-title: Forecasting of Hong Kong airport’s passenger throughput
  publication-title: Tourism Management
  doi: 10.1016/j.tourman.2013.10.008
– volume-title: Time series analysis: Forecasting and control
  year: 1976
  ident: pone.0248361.ref038
– ident: pone.0248361.ref008
  doi: 10.1038/s41598-021-92399-2
– volume: 93
  start-page: 339
  year: 2020
  ident: pone.0248361.ref013
  article-title: Transmission potential and severity of COVID-19 in South Korea
  publication-title: International Journal of Infectious Diseases
  doi: 10.1016/j.ijid.2020.03.031
– volume: 7
  year: 2020
  ident: pone.0248361.ref006
  article-title: Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic
  publication-title: Sci Data
  doi: 10.1038/s41597-020-00734-5
– ident: pone.0248361.ref046
– volume: 82
  year: 2020
  ident: pone.0248361.ref052
  article-title: Does a reward program affect customers’ behavioural intention of visiting the airport? A case study of Singapore Changi Airport
  publication-title: Journal of Air Transport Management
– start-page: 205
  volume-title: The nature of mathematical modeling
  ident: pone.0248361.ref016
– volume: 32
  start-page: 527
  year: 2017
  ident: pone.0248361.ref022
  article-title: New approaches for estimation of monthly rainfall based on GEP-ARCH and ANN-ARCH hybrid models
  publication-title: Water Resource Manage
  doi: 10.1007/s11269-017-1825-0
– volume: 395
  start-page: 1225
  issue: 10231
  year: 2020
  ident: pone.0248361.ref002
  article-title: COVID-19 and Italy: what next?
  publication-title: The Lancet
  doi: 10.1016/S0140-6736(20)30627-9
– year: 2020
  ident: pone.0248361.ref026
  article-title: Functional ARCH directional dependence via copula for intraday volatility from high-frequency financial time series
  publication-title: Applied Economics
– ident: pone.0248361.ref028
– ident: pone.0248361.ref049
– ident: pone.0248361.ref023
  doi: 10.1016/j.jmva.2018.11.016
– volume: 15
  start-page: 215
  issue: 2
  year: 2010
  ident: pone.0248361.ref033
  article-title: A seasonal ARIMA model of tourism forecasting: the case of Taiwan
  publication-title: Asia Pacific Journal of Tourism Research
  doi: 10.1080/10941661003630001
– volume: 368
  start-page: 493
  issue: 6490
  year: 2020
  ident: pone.0248361.ref009
  article-title: The effect of human mobility and control measures on the COVID-19 epidemic in China
  publication-title: Science
  doi: 10.1126/science.abb4218
– volume: 2
  start-page: 1
  issue: 9
  year: 2014
  ident: pone.0248361.ref034
  article-title: Applications and comparisons of four time series models in epidemiological surveillance data
  publication-title: PLOS ONE
– volume: 28
  start-page: 227
  issue: 1
  year: 2007
  ident: pone.0248361.ref036
  article-title: An analysis of seasonality in monthly per person tourist spending in Turkish inbound tourism from a market segmentation perspective
  publication-title: Tourism Management
  doi: 10.1016/j.tourman.2006.01.003
– ident: pone.0248361.ref045
– ident: pone.0248361.ref007
SSID ssj0053866
Score 2.4707248
Snippet Many countries have been implementing various control measures with different strictness levels to prevent the coronavirus disease 2019 (COVID-19) from...
[...]control measures such as travel restrictions, city lock-down, cordon sanitaire, and night curfew have been enforced in many countries. According to the...
[...]control measures such as travel restrictions, city lock-down, cordon sanitaire, and night curfew have been enforced in many countries. According to the...
SourceID plos
doaj
pubmedcentral
proquest
gale
pubmed
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage e0248361
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
SummonAdditionalLinks – databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Rb9MwELZQn_aCGAMWNuBASIBEusRJHJu3MphWJJhE6bS3yHFSqJiSakkf-Bn8Y-4cJ1rQpPHAY-tz1N6dz98pd98x9hJvBFnwnGqq4gQTFCl8RAloEK4TaWKjREINzp-_iNNl_Okiubg26otqwjp64E5xR6UWQoec59TJkAultJZFHGop8arlwvaR453XJ1NdDMZTLIRrlIvS8MjZZbqpq3JKLF6RCEcXkeXrH6LyZHNZNzdBzr8rJ69dRSf32F2HIWHW_fZddqes7rNdd0obeO2opN_ssd9z2wQJ9Qr6SSgtuOp0oPkMuKcBxK1wfHY-_-CHCupti1my_gl1BQgOQa-voO0Z0K0ZYd2N-_j1DmZghjmG4Eq-wI7kfms3L6eLKeiqgAVN3sYnlA_Y8uTjt-NT3w1h8A2mEq1vpDEJV4izcsQiARlSRkGelmmehDpWUaAkVznCypXRYaBKGhBuilwXCBVKTHMfskmFat9nUBQmTcNCFoJY7OJYpRo_BDrhZWJEEnos6i2SGcdQToMyLjP72i3FTKVTcEZ2zJwdPeYPuzYdQ8ct8u_J2IMs8WvbL9DrMud12W1e57Fn5CpZ16w6RIlsJhLiscIs1WMvrARxbFRUxPNdb5smm5-d_4PQ4utI6JUTWtWoDqNd4wT-J-LuGkkejiQxUpjR8j45dq-VJuPE5oiQjUvc2Tv7zcvPh2V6KBXmVWW9tTKcU-BHmUfd2Rg0G0UpJvdKeCwdnZqR6scr1fqHpThP8V4I4vjx_7DVAdvhVIhERZjikE3aq235BJFkmz-1QeMP6shuEA
  priority: 102
  providerName: Directory of Open Access Journals
– databaseName: Health & Medical Collection
  dbid: 7X7
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3db9MwELegvPCCGF_rGHAgJEAiXeIkdswLKoNpRYJJlE57ixwnHRVTUpr0gT-D_5g7xwkETcBj43PU3Pm-krvfMfYUPUKS84xqqqIYE5REeBgloEC4jhMTGSVianD-8FEcL6L3Z_GZe-FWu7LKziZaQ51Xht6RH3BCnkP3wpPX628eTY2ir6tuhMZVdo2gy6ikS571CRfqshCuXS6UwYGTzmRdlcWEsLxCEQzckUXt723zaH1R1ZcFnn_WT_7mkI5ushsukoRpK_oddqUob7Edp6s1PHeA0i9usx8z2woJ1RK6eSgNuBp1oCkNuKcGjF7h8OR09tYLFFTbBnNl_RWqEjBEBL3aQNPhoFthwqod-vH9FUzB9NMMwRV-gR3M_dJuXkzmE9BlDnOav413KO6wxdG7z4fHnhvF4BlMKBrPJMbEXGG0lWFE4pM4k9DPZCGzONCRCn2VcJVhcLk0OvBVQWPCTZ7pHAOGApPdu2xUItt3GeS5kTLIk1wQll0UKanxh69jXsRGxMGYhZ1EUuNwymlcxkVqP75JzFdaBqckx9TJccy8fte6xen4B_0bEnZPSyjb9kK1OU-d0qaFFkIHnGfURZMJpbRO8ijQ-OyJ4kKO2SM6KmnbstrbinQqYkKzwlx1zJ5YCkLaKKmU51xv6zqdnZz-B9H804DomSNaVsgOo137BD4TIXgNKPcHlGgvzGB5lw52x5U6_aVZuLM77JcvP-6X6aZUnlcW1dbScE7mH2nutbrRczYMJab4SoyZHGjNgPXDlXL1xQKdS_QOfhTt_f1v3WfXORUaUZGl2GejZrMtHmCk2GQPrTn4CTLBZnk
  priority: 102
  providerName: ProQuest
Title Impact of different control policies for COVID-19 outbreak on the air transportation industry: A comparison between China, the U.S. and Singapore
URI https://www.ncbi.nlm.nih.gov/pubmed/33724996
https://www.proquest.com/docview/2501838128
https://www.proquest.com/docview/2502204258
https://pubmed.ncbi.nlm.nih.gov/PMC7963044
https://doaj.org/article/ea66a122b8624b699aa8d41a88389267
http://dx.doi.org/10.1371/journal.pone.0248361
Volume 16
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3db9MwELdG98ILYnytYxSDkACJVImT2AkSQl1pWZG2oZVOfYscJx0VVVKaVGIv_A_8x9w5TkTQ-Hix1PpsyXc--y6--x0hz-BGCBIWY0yV54ODEnALrAQQCJN-oDwVch8TnE9O-fHM-zD35zukrtlqGFhc69phPanZZtX_9vXqLSj8G121QTj1oP46z9I-YnS56A_twt0kUFVPvOZdAbRbv16i1WJxZrsmme5Ps7QuK43p35zcnfUqL64zS3-PrvzluhrfJreMnUkH1cbYIztpdofsGU0u6AsDN_3yLvkx0YmSNF_QulpKSU0EO8UaDjCmoGDb0uHZxeSd5YQ035bgScsvNM8oGJBULje0rFHStajpsioJcvWaDqhqah1SExZGddnuV3rwrD_tU5kldIrVuWGG9B6ZjUefhseWKdRgKXA3SksFSvksBFssBnvFRmEHrh2LVMS-I73QtcOAhTGYngslHTtMsYi4SmKZgDmRgit8n3QyYPs-oUmihHCSIOGIdOd5oZDww5Y-S33FfadL3FoikTIo5lhMYxXppzkB3kzF4AjlGBk5donVjFpXKB7_oD9CYTe0iMGt_8g3l5FR6SiVnEuHsRhzbGIehlIGiedIWHsQMi665DFulahKaG1OkmjAfcS6Ak-2S55qCsThyDDQ51JuiyKanF38B9H0vEX03BAtcmCHkia5AtaE-F4tysMWJZwmqtW9jxu75koRMUR8BLOOBTCy3uzXdz9punFSDN7L0nyraRjDywFoHlS60XDWdQUDp5t3iWhpTYv17Z5s-VnDoAu4O2zPO_j7gh6SmwzDkDAEkx-STrnZpo_AjizjHrkh5gLaYOhgO37fI7tHo9OP5z39Zaanjw5sv49-AlwjdCw
linkProvider Scholars Portal
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9NAEF5V6QEuiPJqoNAFgQAJp_ba3rWREAotVUJfEmmq3Nz12ilRKzvEjlB_Bn-E38jMem0wqoBLj8nOWvbM7DzsmW8IeQ4eIUhYjDVVng8JSsAtiBJAIEz6gfJUyH1scD445IOx92niT1bIj7oXBssqa5uoDXWSK3xHvsUQeQ7cCwvez79aODUKv67WIzQqtdhLL79Byla8G-6AfF8wtvvxeHtgmakCloLYuLRUoJTPQggcYnCuNt5Z4NqxSEXsO9ILXTsMWBhDnDRV0rHDFCdeqySWCfi-1EegAzD5q-B4bTxRYtIkeGA7ODftea5wtow29OZ5lvYQO8zlTsv96SkBjS_ozC_y4qpA9896zd8c4O5tcstErrRfqdoaWUmzO2TN2IaCvjIA1q_vku9D3XpJ8ymt56-U1NTEU5wKAXsKCtEy3T46Ge5YTkjzZQm5uTyneUYhJKVytqBljbuulYfOqiEjl29pn6pmeiI1hWZUDwJ_ozePe6MelVlCRzjvG66Q3iPjaxHSfdLJgO3rhCaJEsJJgoQjdp7nhULCD1v6LPUV950ucWuJRMrgouN4jotIf-wTkB9VDI5QjpGRY5dYza55hQvyD_oPKOyGFlG99R_54iwyRiJKJefSYSzGrp2Yh6GUQeI5Ep49CBkXXbKJqhJVLbKNbYr63Ef0LMiNu-SZpkBkjwxLh87ksiii4dHJfxCNPreIXhqiaQ7sUNK0a8AzIWJYi3KjRQn2SbWW11Gxa64U0a-TDDtrZb96-WmzjBfFcsAszZeahjF0N0DzoDobDWddVzBI43mXiNapabG-vZLNvmhgdQHeyPa8h3-_rU1yY3B8sB_tDw_3HpGbDIucsMCTb5BOuVimjyFKLeMn2jRQcnrdtugno2WhMg
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1fb9MwELemIiFeEOPfCoMZBAIk0iZOYidICJWVamWwIbpOfQuOk46KKSlNKrSPwdfh03HnOIGgCXjZY-tzlNyd709y9ztCHoFHCBIWY02V50OCEnALogQQCJN-oDwVch8bnN8f8L2p93bmzzbIj7oXBssqa5uoDXWSK3xH3meIPAfuhQX9uSmL-DAcvVp-tXCCFH5prcdpVCqyn559g_SteDkegqwfMzZ6c7S7Z5kJA5aCOLm0VKCUz0IIImJwtDbeZeDasUhF7DvSC107DFgYQ8w0V9KxwxSnX6sklgn4wdRH0AMw_5eE6zt4xsSsSfbAjnBuWvVc4fSNZvSWeZb2EEfM5U7LFeqJAY1f6CxP8-K8oPfP2s3fnOHoGrlqolg6qNRuk2yk2XWyaexEQZ8aMOtnN8j3sW7DpPmc1rNYSmrq4ylOiIA9BYXIme4eHo-HlhPSfF1Cni6_0DyjEJ5SuVjRssZg14pEF9XAkbMXdEBVM0mRmqIzqoeCP9ebp71Jj8osoROc_Q1XSG-S6YUI6RbpZMD2LUKTRAnhJEHCEUfP80Ih4YctfZb6ivtOl7i1RCJlMNJxVMdppD_8CciVKgZHKMfIyLFLrGbXssII-Qf9axR2Q4sI3_qPfHUSGYMRpZJz6TAWYwdPzMNQyiDxHAnPHoSMiy7ZQVWJqnbZxk5FA-4jkhbkyV3yUFMgykeG5-VErosiGh8e_wfR5GOL6IkhmufADiVN6wY8E6KHtSi3W5Rgq1RreQsVu-ZKEf061bCzVvbzlx80y3hRLA3M0nytaRhD1wM0t6uz0XDWdQWDlJ53iWidmhbr2yvZ4rMGWRfgmWzPu_P329ohl8EKRe_GB_t3yRWG9U5Y68m3SadcrdN7ELCW8X1tGSj5dNGm6CdrVKVo
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Impact+of+different+control+policies+for+COVID-19+outbreak+on+the+air+transportation+industry%3A+A+comparison+between+China%2C+the+U.S.+and+Singapore&rft.jtitle=PloS+one&rft.au=Meng%2C+Fanyu&rft.au=Gong%2C+Wenwu&rft.au=Liang%2C+Jun&rft.au=Li%2C+Xian&rft.date=2021-03-16&rft.pub=Public+Library+of+Science&rft.issn=1932-6203&rft.eissn=1932-6203&rft.volume=16&rft.issue=3&rft.spage=e0248361&rft_id=info:doi/10.1371%2Fjournal.pone.0248361&rft.externalDocID=A655200144
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1932-6203&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1932-6203&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1932-6203&client=summon