Evidence map›Paper›PMID 35194345›Full record

ArticleJournal of air transport management2022

The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia.

Pei-Fen Kuo, I Gede Brawiswa Putra, Faizal Azmi Setiawan, Tzai-Hung Wen, Chui-Sheng Chiu, Umroh Dian Sulistyah

Open access · greenAbstract read
In one paragraph

Article in Journal of air transport management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
7.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Pei-Fen KuoDepartment of Geomatics, National Cheng Kung University, Taiwan.
I Gede Brawiswa PutraDepartment of Geomatics, National Cheng Kung University, Taiwan.
Faizal Azmi SetiawanDepartment of Geomatics, National Cheng Kung University, Taiwan.
Tzai-Hung WenDepartment of Geography, National Taiwan University, Taiwan.
Chui-Sheng ChiuDepartment of Geomatics, National Cheng Kung University, Taiwan.
Umroh Dian SulistyahDepartment of Geomatics, National Cheng Kung University, Taiwan.
National Cheng Kung University · TWNational Taiwan University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing COVID-19 pandemic has posed a global threat to human health. In order to prevent the spread of this virus, many countries have imposed travel restrictions. This difficult situation has dramatically affected the airline industry by reducing the passenger volume, number of flights, airline flow patterns, and even has changed the entire airport network, especially in Northeast Asia (because it includes the original disease seed). However, although most scholars have used conventional statistical analysis to describe the changes in passenger volume before and during the COVID-19 outbreak, very few of them have applied statistical assessment or time series analysis, and have not even examined how the impact may be different from place to place. Therefore, the purpose of this study was to identify the impact of COVID-19 on the airline industry and affected areas (including the origin-destination flow and the airport network). First, a Clustering Large Applications (CLARA) algorithm was used to group numerous origin-destination (O-D) flow patterns based on their characteristics and to determine if these characteristics have changed the severity of the impact of each cluster during the COVID-19 outbreak. Second, two statistical tests (the paired

Indexed as

Airport networkCentralityCLARA clustering AlgorithmCOVID-19

Identifiers

PMID35194345
PMCPMC8849875
OpenAlexW4212920048

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.