Original DHI method for assessing epidemic hazards in transportation services

• Autorzy: Burdzik Rafał

Identyfikatory

DOI

10.20858/sjsutst.2023.121.3

• Języki publikacji: EN

Abstrakty

EN

In the situation of the global SARS-COV-2 coronavirus pandemic, epidemic threats are dominant and ubiquitous. The article attempted to estimate the hazards of virus transmission in various transport services. In the author's opinion, numerous and very serious problems in the transport sector and transport services are in this case the result of a lack of a methodical approach to the problem of epidemic threats, including infection in a global epidemic. The paper presents a proposal for an original DHI method for assessing epidemic hazards in transportation services, taking into account various hazards and routes of virus transmission (droplet and contact) based on dedicated scales of hazard evaluation and multi-criteria assessment. This methodology is named Deep Hazard Identification (DHI). The primary stage of the methodology is the identification and estimation of transmission mechanisms of pathogen that can occur in transport services. For this purpose 15 criteria and weighting factors were defined and used for a multi-criteria epidemic hazards assessment. It enables the determination of the matrix of hazard assessment separately for the passenger transport and freight transport groups, which allows for the comparison of the DHI hazard factor between different transport services.

Słowa kluczowe

EN

epidemic; hazard; risk; transport services; hazard identification

PL

epidemia; zagrożenie; ryzyko; usługi transportowe; identyfikacja zagrożeń

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Zeszyty Naukowe. Transport / Politechnika Śląska
• Rocznik: 2023
• Tom: z. 121
• Strony: 31--43
• Opis fizyczny: Bibliogr. 23 poz.

Twórcy

autor

Burdzik Rafał

• Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland

• https://orcid.org/0000-0003-0360-8559

Bibliografia

• 1. Devleesschauwer Brecht, Sara M. Pires, Barbara B. Kowalcyk, Robert L. Scharff, Arie H. Havelaar, Niko Speybroeckl. 2020. Risk Metrics Quantifying the Impact of Adverse Health Effects. In: Risk Assessment Methods for Biological and Chemical Hazards in Food: 50-82. Edited by Fernando Pérez-Rodríguez. USA: Boca Raton, Taylor & Francis Group CRC Press. ISBN: 9780429083525.
• 2. Burdzik Rafał. 2021. Epidemic Risk Analysis and Assessment in Transport Services. New York, USA: Taylor & Francis Group CRC Press. ISBN: 978-1-032-06961-6. DOI: https://doi.org/10.1201/9781003204732.
• 3. Tirachini Alejandro, Oded Cats. 2020. “Covid-19 and Public Transportation: Current Assessment, Prospects, and Research Needs”. Journal of Public Transportation 22(1): 1-21. DOI: https://doi.org/10.5038/2375-0901.22.1.1.
• 4. Dávid Andrej, Andrea Galieriková, Peter Mako. 2022. “Application of Anti-Epidemiological Measures and Covidautomat in Public Water Transport”. Transport Problems 17(2): 189-97. DOI: https://doi.org/10.20858/tp.2022.17.2.16.
• 5. Ramajo Damian E., Santiago Corzo. 2022. “Airborne Transmission Risk in Urban Buses: A Computational Fluid Dynamics Study”. Aerosol and Air Quality Research 22(8): 210334. DOI: https://doi.org/10.4209/aaqr.210334.
• 6. Corzo Santiago Francisco, Dario Martin Godino, Damian Enrique Ramajo. 2022. “Air Circulation Study inside and Outside of Urban Buses Induced by the Opening of Windows”. Environmental Science and Pollution Research 30(8): 20821-20832. DOI: https://doi.org/10.1007/s11356-022-23369-y.
• 7. Benmalek Elmehdi, Jamal Elmhamdi, Abdelilah Jilbab, Atman Jbari. 2023. “A cough-based Covid-19 detection with gammatone and mel-frequency cepstral coefficients”. Diagnostyka 24(2): 2023214. DOI: https://doi.org/10.29354/diag/166330.
• 8. García de Abajo, F. Javier, Rufino Javier Hernández, Ido Kaminer, Andreas Meyerhans, Joan Rosell-Llompart, Tilman Sanchez-Elsner. 2020. “Back to Normal: An Old Physics Route to Reduce SARS-COV-2 Transmission in Indoor Spaces”. ACS Nano 14(7): 7704-13. DOI: https://doi.org/10.1021/acsnano.0c04596.
• 9. Smieszek Timo. 2009. “A Mechanistic Model of Infection: Why Duration and Intensity of Contacts Should Be Included in Models of Disease Spread”. Theoretical Biology and Medical Modelling 6(1): 25. DOI: https://doi.org/10.1186/1742-4682-6-25.
• 10. Smieszek Timo, Lena Fiebig, Roland W Scholz. 2009. “Models of Epidemics: When Contact Repetition and Clustering Should Be Included”. Theoretical Biology and Medical Modelling 6(1): 11. DOI: https://doi.org/10.1186/1742-4682-6-11.
• 11. Smieszek Timo, Gianrocco Lazzari, Marcel Salathé. 2019. “Assessing the Dynamics and Control of Droplet- and Aerosol-Transmitted Influenza Using an Indoor Positioning System”. Scientific Reports 9(1): 2185. DOI: https://doi.org/10.1038/s41598-019-38825-y.
• 12. Schultz Michael, Jörg Fuchte. 2020. “Evaluation of Aircraft Boarding Scenarios Considering Reduced Transmissions Risks”. Sustainability 12(13): 5329. DOI: https://doi.org/10.3390/su12135329.
• 13. Burdzik, Rafał, Niko Speybroeck. 2023. „Study on the Estimation of SARS-CoV-2 Virus Pathogens’ Transmission Probabilities for Different Public Bus Transport Service Scenarios”. Transport Problems 18(3): 200-211. DOI: https://doi.org/10.20858/tp.2023.18.3.17.
• 14. Di Carlo Piero, Piero Chiacchiaretta, Bruna Sinjari, Eleonora Aruffo, Liborio Stuppia, Vincenzo De Laurenzi, Pamela Di Tomo, et al. 2020. “Air and Surface Measurements of SARS-COV-2 inside a Bus during Normal Operation”. PLOS ONE 15(11): e0235943. DOI: https://doi.org/10.1371/journal.pone.0235943.
• 15. Burdzik, Rafał. 2023. „An Application of the DHI Methodology for a Comparison of SARS-CoV-2 Epidemic Hazards in Customer Delivery Services of Smart Cities”. Smart Cities 6(2): 965-986. DOI: https://doi.org/10.3390/smartcities6020047.
• 16. Staniuk Wiesław, Michał Staniuk, Norbert Chamier-Gliszczynski, Marianna Jacyna, Michał Kłodawski. 2022. “Decision-Making under the Risk, Uncertainty and Covid-19 Pandemic Conditions Applying the PL9A Method of Logistics Planning – Case Study”. Energies 15(2): 639. DOI: https://doi.org/10.3390/en15020639.
• 17. Burdzik Rafał, Wongelawit Petros Chema, Ireneusz Celiński. 2023. „A Study on Passenger Flow Model and Simulation in Aspect of COVID-19 Spreading on Public Transport Bus Stops”. Journal of Public Transportation 25: 1-18. DOI: https://doi.org/10.1016/j.jpubtr.2023.100063.
• 18. Zafri Niaz Mahmud, Asif Khan, Shaila Jamal, Bhuiyan Monwar Alam. 2022. “Risk Perceptions of COVID-19 Transmission in Different Travel Modes”. Transportation Research Interdisciplinary Perspectives 13: 100548. DOI: https://doi.org/10.1016/j.trip.2022.100548.
• 19. Librantz André Felipe, Fábio Cosme dos Santos, Cleber Gustavo Dias, Adriana Cristina da Cunha, Ivanir Costa, Mauro de Mesquita Spinola. 2016. “AHP Modelling and Sensitivity Analysis for Evaluating the Criticality of Software Programs”. In: Advances in Production Management Systems. Initiatives for a Sustainable World. APMS 2016. IFIP Advances in Information and Communication Technology 488: 248-255. Springer, Cham. ISBN: 978-3-319-51133-7. DOI https://doi.org/10.1007/978-3-319-51133-7_30.
• 20. Sharifi Ayyoob, Amir Reza Khavarian-Garmsir, Rama Krishna Kummitha. 2021. “Contributions of Smart City Solutions and Technologies to Resilience against the COVID-19 Pandemic: A Literature Review”. Sustainability 13(14): 8018. DOI: https://doi.org/10.3390/su13148018.
• 21. Saaty Thomas L. 2009. Theory and applications of the analytic network process: Decision making with benefits, opportunities, costs, and risks. Pittsburgh, PA: RWS Publ. ISBN: 978-1-8886031-6-3.
• 22. Kukulski Jacek, Konrad Lewczuk, Ignacy Góra, Mariusz Wasiak. 2023. “Methodological aspects of risk mapping in multimode transport systems”. Eksploatacja i Niezawodność – Maintenance and Reliability 25(1): 19. DOI: https://doi.org/10.17531/ein.2023.1.19.
• 23. Niewczas Andrzej, Łukasz Mórawski, Joanna Rymarz, Ewa Dębicka, Piotr Hołyszko. 2023. „Operational Risk Assessment Model for City Buses”. Eksploatacja i Niezawodność – Maintenance and Reliability 25(1): 14. DOI: https://doi.org/10.17531/ein.2023.1.14