Post by Nadica (She/Her) on Jun 18, 2024 4:44:15 GMT
A quantitative microbial risk assessment approach to estimate exposure to SARS-CoV-2 on a bus - Published June 15, 2024
Highlights
•Stochastic agent-based model of a bus and its passengers across a bus journey.
•Distribution of SARS-CoV-2 passengers' doses via airborne, close-range and fomite.
•Exploration of factors like loading, prevalence, masks, seating and ventilation.
•Prevalence and loading impact probability of receiving all three doses.
•Mask frequency reduces the magnitude of all three doses, especially close-range.
Abstract
Introduction
We adapt and extend the Transmission of Virus in Carriages (TVC) model, a Quantitative Microbial Risk Assessment (QMRA) computational model originally developed to estimate exposure risk to SARS-CoV-2 in a subway carriage, to estimate exposure risk on a bus. The aim is to analyse the relative importance of different behavioural and environmental factors influencing exposure in this public transport setting, especially exposure to large doses when considering viral load variability between infectious passengers.
Methods
The QMRA model considers individual exposure during a bus journey through three routes: close-range exposure to aerosols and droplets due to being at close proximity (
2m) of an infected passenger, long-range airborne exposure at long distances (
2m), and transmission via contaminated surfaces (fomite route).
Results
Model predictions show that disease prevalence and bus loading levels have a major impact both on the likelihood of exposure and probability of receiving a large dose. Mask wearing is predicted to greatly reduce the magnitude of doses received, especially from close-range exposure. Assumptions around viral load also have a major impact on doses received, with large long-range airborne doses only occurring under very wide viral load distributions. Doses are not uniform around the bus, with close-range dose being generally more likely in the middle of the bus and fomite doses depending on the types of available surfaces around passengers’ seated/standing positions. Surface contamination is predicted to be greatest on traversal poles that may be touched by many passengers while boarding and alighting.
Conclusions
These model predictions have implications on the effectiveness of various mitigations to SARS-CoV-2 transmission on buses.
Keywords: Modelling, Masks, Airborne, Fomite, public transit
Highlights
•Stochastic agent-based model of a bus and its passengers across a bus journey.
•Distribution of SARS-CoV-2 passengers' doses via airborne, close-range and fomite.
•Exploration of factors like loading, prevalence, masks, seating and ventilation.
•Prevalence and loading impact probability of receiving all three doses.
•Mask frequency reduces the magnitude of all three doses, especially close-range.
Abstract
Introduction
We adapt and extend the Transmission of Virus in Carriages (TVC) model, a Quantitative Microbial Risk Assessment (QMRA) computational model originally developed to estimate exposure risk to SARS-CoV-2 in a subway carriage, to estimate exposure risk on a bus. The aim is to analyse the relative importance of different behavioural and environmental factors influencing exposure in this public transport setting, especially exposure to large doses when considering viral load variability between infectious passengers.
Methods
The QMRA model considers individual exposure during a bus journey through three routes: close-range exposure to aerosols and droplets due to being at close proximity (
2m) of an infected passenger, long-range airborne exposure at long distances (
2m), and transmission via contaminated surfaces (fomite route).
Results
Model predictions show that disease prevalence and bus loading levels have a major impact both on the likelihood of exposure and probability of receiving a large dose. Mask wearing is predicted to greatly reduce the magnitude of doses received, especially from close-range exposure. Assumptions around viral load also have a major impact on doses received, with large long-range airborne doses only occurring under very wide viral load distributions. Doses are not uniform around the bus, with close-range dose being generally more likely in the middle of the bus and fomite doses depending on the types of available surfaces around passengers’ seated/standing positions. Surface contamination is predicted to be greatest on traversal poles that may be touched by many passengers while boarding and alighting.
Conclusions
These model predictions have implications on the effectiveness of various mitigations to SARS-CoV-2 transmission on buses.
Keywords: Modelling, Masks, Airborne, Fomite, public transit