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Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia
In 2020, with a substantial decline in tourist arrivals slightly before the time of COVID-19, the innovative econometric approach predicted possible responses between the spread of human microbes (bacteria/viruses) and tourist arrivals. The article developed a conceptually tested econometric model f...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603530/ https://www.ncbi.nlm.nih.gov/pubmed/36294060 http://dx.doi.org/10.3390/ijerph192013482 |
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author | Gričar, Sergej Bojnec, Štefan |
author_facet | Gričar, Sergej Bojnec, Štefan |
author_sort | Gričar, Sergej |
collection | PubMed |
description | In 2020, with a substantial decline in tourist arrivals slightly before the time of COVID-19, the innovative econometric approach predicted possible responses between the spread of human microbes (bacteria/viruses) and tourist arrivals. The article developed a conceptually tested econometric model for predicting an exogenous shock on tourist arrivals driven by the spread of disease using a time series approach. The reworked study is based on an autoregressive integrated moving average (ARIMA) model to avoid spurious results. The periods of robust empirical study were obtained from the data vectors i) from January 2008 to December 2018 and ii) from January 2008 to December 2020. The data were obtained from the National Institute of Public Health (NIPH) and the Statistical Office of the Republic of Slovenia. The ARIMA model predicted the number of declines in tourist arrivals for the approaching periods due to the spread of viruses. Before the outbreak of COVID-19, pre-pandemic results confirmed a one-fifth drop in tourist arrivals in the medium term. In the short term, the decline could be more than three-quarters. A further shock can be caused by forecasted bacterial infections; less likely to reduce tourist demand in the long term. The results can improve the evidence for public health demand in risk reduction for tourists as possible patients. The data from the NIPH are crucial for monitoring public health and tourism management as a base for predictions of unknown events. |
format | Online Article Text |
id | pubmed-9603530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96035302022-10-27 Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia Gričar, Sergej Bojnec, Štefan Int J Environ Res Public Health Article In 2020, with a substantial decline in tourist arrivals slightly before the time of COVID-19, the innovative econometric approach predicted possible responses between the spread of human microbes (bacteria/viruses) and tourist arrivals. The article developed a conceptually tested econometric model for predicting an exogenous shock on tourist arrivals driven by the spread of disease using a time series approach. The reworked study is based on an autoregressive integrated moving average (ARIMA) model to avoid spurious results. The periods of robust empirical study were obtained from the data vectors i) from January 2008 to December 2018 and ii) from January 2008 to December 2020. The data were obtained from the National Institute of Public Health (NIPH) and the Statistical Office of the Republic of Slovenia. The ARIMA model predicted the number of declines in tourist arrivals for the approaching periods due to the spread of viruses. Before the outbreak of COVID-19, pre-pandemic results confirmed a one-fifth drop in tourist arrivals in the medium term. In the short term, the decline could be more than three-quarters. A further shock can be caused by forecasted bacterial infections; less likely to reduce tourist demand in the long term. The results can improve the evidence for public health demand in risk reduction for tourists as possible patients. The data from the NIPH are crucial for monitoring public health and tourism management as a base for predictions of unknown events. MDPI 2022-10-18 /pmc/articles/PMC9603530/ /pubmed/36294060 http://dx.doi.org/10.3390/ijerph192013482 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gričar, Sergej Bojnec, Štefan Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia |
title | Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia |
title_full | Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia |
title_fullStr | Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia |
title_full_unstemmed | Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia |
title_short | Did Human Microbes Affect Tourist Arrivals before the COVID-19 Shock? Pre-Effect Forecasting Model for Slovenia |
title_sort | did human microbes affect tourist arrivals before the covid-19 shock? pre-effect forecasting model for slovenia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603530/ https://www.ncbi.nlm.nih.gov/pubmed/36294060 http://dx.doi.org/10.3390/ijerph192013482 |
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