Evidence map›Paper›PMID 37672489›Full record

ArticlePloS one2023

Tourism during health disasters: Exploring the role of health system quality, transport infrastructure, and environmental expenditures in the revival of the global tourism industry.

Yu Xiong, Xiaohan Tang

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yu XiongSchool of Environmental and Chemical Engineering, Foshan University, Foshan, 528000, Guangdong, China.ORCID 0009-0000-0529-1175
Xiaohan TangDecision Consulting Department, Party School of the Zhongshan Municipal Committee of the Communist Party of China, Zhongshan, 528403, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tourism is one of the most important promoters of sustainable development in many nations and regions around the globe. Tourism expansion has been a significant contributor to social and economic growth, particularly in developing economies. It is, however, vulnerable to all kinds of health crises and natural disasters, no matter how small they are. The primary purpose of this study is to acquire an empirical understanding of the effects of health crises and disasters on international tourism. The SYS-GMM was used to examine the impact of health calamities and crises, carbon footprints from transportation, and green finance on the tourism of 51 countries between 2007 and 2020. The results showed that health crises and natural disasters have a big effect on international tourism. Alternatively, the presence of eco-friendly and secure transportation at tourist destinations has a positive effect on the tourism industry. The results also showed that environmental expenditures have positive short- and long-term effects on international tourism. Furthermore, the sensitivity of travelers to health crises and natural disasters varies over the short and long term. The study also showed that compared to normal times, international tourism dropped by more than 67% during COVID-19. Consequently, this research assists us in comprehending, predicting, and preventing the potential adverse effects of COVID-19 and other similar economic, health disasters and crises that could occur in the future and harm the tourism industry.

Indexed as

COVID-19DisastersIsoflavonesNatural DisastersHealth ExpendituresHumansSoybean ProteinsTourismIsoflavonesSoybean Proteins

Identifiers

PMID37672489
PMCPMC10482304

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.