Stefano Maria Iacus, Fabrizio Natale, Carlos Satamaria, Spyridon Spyratos, Michele Vespe
arXiv 17 Apr 2020 · Statistics — Applications · publishedSafety Science (2020) · 358 citations (OpenAlex)
arXiv:2004.08460 · PDF · DOI · OpenAlex · Extracted main text
The main focus of this study is to collect and prepare data on air passengers traffic worldwide with the scope of analyze the impact of travel ban on the aviation sector. Based on historical data from January 2010 till October 2019, a forecasting model is implemented in order to set a reference baseline. Making use of airplane movements extracted from online flight tracking platforms and on-line booking systems, this study presents also a first assessment of recent changes in flight activity around the world as a result of the COVID-19 pandemic. To study the effects of air travel ban on aviation and in turn its socio-economic, several scenarios are constructed based on past pandemic crisis and the observed flight volumes. It turns out that, according to this hypothetical scenarios, in the first Quarter of 2020 the impact of aviation losses could have negatively reduced World GDP by 0.02% to 0.12% according to the observed data and, in the worst case scenarios, at the end of 2020 the loss could be as high as 1.41-1.67% and job losses may reach the value of 25-30 millions. Focusing on EU27, the GDP loss may amount to 1.66-1.98% by the end of 2020 and the number of job losses from 4.2 to 5 millions in the worst case scenarios. Some countries will be more affected than others in the short run and most European airlines companies will suffer from the travel ban.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | IATA (2020) What can we learn from past pandemic episodes? | 0.644 | 2 | 2 | 100% |
| 2 | JRC-Unit-B5 (2020) Flash estimates of the potential effects on gdp of the 30-day travel ban for non-eu residents to fight against the covid19 spread | 0.644 | 2 | 2 | 100% |
| 3 | Iacus, S. M., F. Natale, and M. Vespe (2020) Flight restrictions from china during the covid-2019 coronavirus outbreak self | 0.644 | 2 | 2 | 100% |
| 4 | IATA (2019) Aviation benefits report | 0.585 | 3 | 1 | 100% |
| 5 | ATAG (2018) Aviation benefits beyond borders | 0.405 | 1 | 1 | 100% |
| 6 | Iacus, S. M. and N. Yoshida (2018) Simulation and inference for stochastic processes with YUIMA: a comprehensive R framework for SDEs and other stochastic processes self | 0.405 | 1 | 1 | 100% |
| 7 | Kissler, S. M., C. Tedijanto, M. Lipsitch, and Y. Grad (2020) Social distancing strategies for curbing the covid-19 epidemic | 0.405 | 1 | 1 | 100% |
| 8 | Matthias Schäfer, Martin Strohmeier, V. L. I. M. M. W. (2014, April) (2014) Bringing up opensky: A large-scale ads-b sensor network for research | 0.405 | 1 | 1 | 100% |
| 9 | Eurocontrol (2018) Covid-19: latest air traffic situation | 0.405 | 1 | 1 | 100% |
| 10 | Gabrielli, L., E. Deutschmann, F. Natale, E. Recchi, and M. Vespe (2019) Dissecting global air traffic data to discern different types and trends of transnational human mobility | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 12 scored citations.