Covid-19 Infection in a Boeing B737-800 Plane: Predicting the Secondary Infection using a Wells-Riley Approach

Authors

  • Nur Amira Nadia Mohd Ali Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, 70300 Seremban, Negeri Sembilan, Malaysia
  • Nur Intan Syafinaz Ahmad Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Bandar Seri Alam, 81750 Johor Bahru, Johor, Malaysia
  • Nurhazirah Mohamad Yunos Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Bandar Seri Alam, 81750 Johor Bahru, Johor, Malaysia
  • Aini Sahira Mohamad Razali Bodibasixs Manufacturing Sdn Bhd,, 41050 Klang, Selangor, Malaysia Department of Information Technology, 41050 Klang, Selangor, Malaysia
  • Siti Adiba Mahasan Prokhas Sdn Bhd, Bukit Damansara, 50490 Kuala Lumpur, Malaysia
  • Aishah Mahat Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Bandar Seri Alam, 81750 Johor Bahru, Johor, Malaysia
  • Azita Abd Aziz Malaysia Airlines Berhad Engineering Service (MABES) (Engineering Complex), South Support Zone, Kuala Lumpur International Airport, 64000 Sepang, Selangor, Malaysia
  • Siti Ramizah Jama Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, 78000 Alor Gajah, Melaka, Malaysia
  • Budi Halomoan Siregar Department of Education, Universitas Negeri Medan, Kabupaten Deli Serdang, Sumatera Utara 20221, Indonesia

DOI:

https://doi.org/10.37934/araset.61.1.95103

Keywords:

Airborne, Aircraft, Infection, Covid-19, Wells-Riley model

Abstract

In March 2020, the first covid-19 cases have been detected in Malaysia. Since then, number of Covid-19 infection in Malaysia has grown relatively until Malaysia become the highest number of positive cases in Southeast Asia. Previous studies have been done to analyse the airborne transmission of infection in different closed spaces. This information is important for many sectors to take any relevant action in order to minimize infection. This study is focusing on estimating the potential risk of Covid-19 infection among passengers on Boeing B737-800 aircraft. The aim of this study is to calculate secondary infection for Covid-19 virus in the Boeing B737-800 aircraft due to airborne transmission. Aircraft are preferred over other enclosed spaces like trains and buses because they require passengers to spend longer time in the enclosed spaces during flight without any interruption between the journeys. A major risk to passengers in a cabin could be posed by massive droplets and airborne transmissions given the high density and close proximity of passengers. The Wells-Riley model is used in this study because it has been frequently used for quantifying the infection risk assessment of infectious illnesses in indoor settings. In this study the secondary risk of infection is calculated for every susceptible passenger flying for one, two, three- and four-hour’s journey. The relationship between exposure time and number of infected people are positive linear relationships. This means that the longer time a passenger is exposed to the infected people in the cabin, the higher chance of the passenger getting infected by the virus. The reproduction number is estimated to be 2 passengers when the exposure duration is less than 2 hours for 80 passengers. This estimation indicates that the reproduction rate of secondary infection is high. Therefore, it can be concluded that there is a high chance passengers may get infected in the aircraft and the risk will increase when the exposure time is increasing. The best alternatives for protection are wearing mask and face shield, social distancing and sanitizing hands frequently. An improvement in ventilation also seems to be effective to prevent infection.

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Author Biographies

Nur Amira Nadia Mohd Ali, Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, 70300 Seremban, Negeri Sembilan, Malaysia

amiranadia868@gmail.com

Nur Intan Syafinaz Ahmad, Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Bandar Seri Alam, 81750 Johor Bahru, Johor, Malaysia

nurin395@uitm.edu.my

Nurhazirah Mohamad Yunos, Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Bandar Seri Alam, 81750 Johor Bahru, Johor, Malaysia

nurhazirah12394@uitm.edu.my

Aini Sahira Mohamad Razali, Bodibasixs Manufacturing Sdn Bhd,, 41050 Klang, Selangor, Malaysia Department of Information Technology, 41050 Klang, Selangor, Malaysia

ainisahirarazali@gmail.com

Siti Adiba Mahasan, Prokhas Sdn Bhd, Bukit Damansara, 50490 Kuala Lumpur, Malaysia

sitiadibamahasan@gmail.com

Aishah Mahat, Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Bandar Seri Alam, 81750 Johor Bahru, Johor, Malaysia

aishahmahat@uitm.edu.my

Azita Abd Aziz, Malaysia Airlines Berhad Engineering Service (MABES) (Engineering Complex), South Support Zone, Kuala Lumpur International Airport, 64000 Sepang, Selangor, Malaysia

azita.abdaziz@malaysiaairlines.com

Siti Ramizah Jama, Department of Mathematics, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, 78000 Alor Gajah, Melaka, Malaysia

ramizah@uitm.edu.my

Budi Halomoan Siregar, Department of Education, Universitas Negeri Medan, Kabupaten Deli Serdang, Sumatera Utara 20221, Indonesia

budihalomoan@unimed.ac.id

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Published

2024-10-08

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