Scientists from Germany have developed a novel mathematical model to check the airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Scientists claim that the brand new model is effective in qualitatively evaluating the danger of exposure. The study is published within the journal PLOS ONE.

Study: Modelling airborne transmission of SARS-CoV-2 at a neighborhood scale. Image Credit: NIAID 

Background

SARS-CoV-2, the causative pathogen of coronavirus disease 2019 (COVID-19), is an enveloped RNA virus that primarily transmits between humans via respiratory droplets and aerosols.

Various mathematical models, including the compartmental Susceptible-Infected-Removed (SIR) model, network model, and agent-based model, have been developed throughout the pandemic to know the dynamics of SARS-CoV-2 transmission. Nevertheless, simulation approaches adopted in these models usually are not entirely suitable to find out airborne transmission that doesn’t all the time depend upon the proximity between infected and susceptible individuals.

Various studies have used macroscopic compartmental, agent-based, and computational fluid dynamics models to know the general dynamics of the COVID-19 pandemic. In contrast, microscopic models have been used to know SARS-CoV-2 transmission between individuals.   

In the present study, scientists have developed a latest mathematical model to explain the airborne transmission of SARS-CoV-2 between individuals in on a regular basis situations.

Study design

The scientists combined microscopic crowd simulation with the brand new model for disease transmission via aerosol clouds. They simulated a each day life situation wherein pedestrians walked in a line and used the model to judge SARS-CoV-2 transmission dynamics between pedestrians.  

Inspired by compartmental models, the scientists defined the health of a virtual pedestrian (model agent) as susceptible or infectious. Within the simulations, infectious agents release aerosol-bound SARS-CoV-2 within the air, inhaled by susceptible agents while walking through the aerosol clouds.

The degree of transmission is determined by the variety of viral particles within the aerosol cloud, which changes over time. Within the simulation, a susceptible agent who inhaled more pathogens was considered “high risk.”     

The transmission model was integrated into Vadere’s simulation loop, a scientific tool for investigating pedestrian dynamics. This integration helped enhance the model and incorporate additional features.

Reference situation to validate the model

A reference situation representing “close contact” was introduced within the model, wherein two virtual agents were kept in close proximity (lower than 1.5 m apart) for 10 minutes. The infected agent continually exhaled aerosol clouds, resulting in a rise in SARS-CoV-2 concentration. The susceptible agent was predicted to inhale roughly 3.2 ⋅ 103 viral particles inside 10 minutes. The susceptible agent was considered “high risk” if he/she inhaled a better than predicted dose of viral particles.

Validation of the model

The model was validated using the information obtained from two studies that investigated SARS-CoV-2 transmission in superspreading events.

The primary study involved ten people seated at adjoining tables at a restaurant, divided into three groups. The infectious person was present in a single group, which shared the restaurant with the opposite two groups for 53 minutes and 73 minutes, respectively. After the restaurant visit, all individuals tested positive for SARS-CoV-2.

Restaurant scenario. Model of restaurant topography, including tables and seats, in accordance with the seating chart. Susceptible (blue) individuals sit in groups A, B and C across the tables (grey). The infectious (red) person emits aerosol clouds (orange).

The identical situation was simulated in the brand new model to validate its efficacy. The model is taken into account to be qualitatively valid if it predicts lower numbers of infectious cases than that observed in the unique study.

In response to the model predictions, five individuals were exposed to the virus. Of them, three belonged to the primary group where the index person was present, and two belonged to the second group. None from the third group was exposed. These predictions indicate that the simulation is qualitatively valid.

The second study described one other superspreading event during a choir rehearsal, where 52 of 61 attendees became infected. The predictions obtained by simulating this case also validated the model’s efficacy.

Application of the model

The model was used to judge SARS-CoV-2 transmission in a queue in front of a service unit in an unventilated room. The simulation involved just one highly infectious person amongst many susceptible pedestrians. Because the room was not ventilated, it was expected that every one aerosol clouds would remain where they were initially situated.

The model predicted that higher viral concentrations occur where many clouds are superimposed. The individuals standing immediately behind the infectious person were predicted to have a high risk of exposure. These individuals were predicted to contain the identical variety of viral particles because the close contact within the reference situation. Moreover, it was predicted that the degree of exposure might be reduced by increasing the gap between individuals standing within the queue.

Study significance

The study describes the event and validation of a latest mathematical model suitable for qualitatively evaluating the danger of SARS-CoV-2 exposure.

In response to the model predictions, long queues in unventilated rooms pose a significantly high risk of exposure. Several individuals in a queue can reach high-risk exposure even in the event that they usually are not standing immediately after an infectious person.