License

This model is distributed under the GNU Public License https://www.gnu.org/licenses/gpl-3.0.en.html
The theory is mostly based on the COVID-19 Aerosol Transmission Estimator by Dr. Jimenez, JL.

"Disclaimer*

* This tool is provided for informational and educational purposes only. It is intended to offer guidance regarding questions about best practices regarding the general selection of portable air cleaners in schools in an effort to reduce the risk of disease transmission. Adherence to any information included in this tool will not ensure successful treatment in every situation, and the user should acknowledge that there is no “zero risk” scenario, that each building and situation are unique and some of the guidance contained in this document will not apply to all buildings, or countries outside Canada.

Nothing in this tool can modify or replace the applicable governmental guidelines issued regularly about controlling the spread of Covid-19 which should be followed by all users.

"Simplicity and uncertainties - IMPORTANT, PLEASE READ*

* The model is kept simple so that it can be understood and changed easily. The goal is to get the order-of-magnitude of the effects quickly, and to explore the trends.Several parameters are uncertain, and have been estimated based on current knowledge. Alternative estimates can be entered to explore their effect in the results.More complex and realistic models can be built, however the parametric uncertainty may still dominate the total uncertainty. Parameters based on new research can be incorporated as they become available.This model is our best scientific estimate, based on the information currently available. It is provided in the hope that it will be useful to others, based on us receiving a large number of requests for this type of information. We trust most the relative risk estimates (when changing parameters such as wearing a mask or not) of two runs of the model. We also trust the order-of-magnitude of the risk estimates, if the inputs are correct. The exact numerical results for a given case have more uncertainty. For example if you obtain a 1% chance of infection, in reality it could be 0.2% or 5%. But it won't be 0.001% or 100%. Results also have to be interpreted statistically, i.e. the result is the average number of transmission cases, across many realizations of a given event. I.e. if 1000 similar events were conducted, this would be the average probability. Any one event may have much fewer or many more transmission cases.

Modeling Indoor Airborne Virus Transmission Risk and Reduced Probability of Infection in an Urban Scale By CityRPI (City Reduced Probability of Infection for indoor airborne virus transmission)

Model Assumptions and Limitations

• The indoor airborne aerosol infection risk model is based on a standard aerosol infection model, the Wells-Riley model [1], modified for the transient modeling of the SARS-CoV-2 (COVID-19) [2].
• This model is NOT an epidemiological model but can take input from such models for the average rate of infection for a given location and time period, e.g., city prevalence of infection, and infected rates for a given location.
• This model does NOT include droplet or contact transmission and assumes that 6 ft/2 m social distancing is respected. Otherwise, the higher transmission will result.
• The occupancy number in a building is calculated based on occupants’ density.
• The indoor airborne aerosol transmission model is based on the well-mixed assumption: the emissions are entirely mixed in an indoor space within a one-time step.

While non-well-mixed models have not been available, this is an approximation that allows easy calculation, which is approximately acceptable as long as near-field effects are avoided by social distancing [2 and 3].

Reference

[1] Riley EC, Murphy G, Riley RL. Airborne spread of measles in a suburban elementary school. American journal of epidemiology. 1978 May 1;107(5):421-32.

[2] Miller SL, Nazaroff WW, Jimenez JL, Boerstra A, Buonanno G, Dancer SJ, Kurnitski J, Marr LC, Morawska L, Noakes C. Transmission of SARS-CoV-2 by inhalation of respiratory aerosol in the Skagit Valley Chorale super spreading event. MedRxiv. 2020 Jan 1.

[3] COVID-19 Aerosol Transmission Estimator, Jimenez JL.

[4] US Environmental Protection Agency. Exposure Factors Handbook: 2011 Edition. US Environ Prot Agency 2011. doi:EPA/600/R-090/052F.

[5] Buonanno G, Stabile L, Morawska L. Estimation of airborne viral emission: quanta emission rate of SARS-CoV-2 for infection risk assessment. Environment International. 2020 May 11:105794.

[6] Buonanno G, Morawska L, Stabile L. Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: prospective and retrospective applications. medRxiv. 2020 Jan 1.

[7] ANSI. ANSI/ASHRAE Standard 62.1-2010, Ventilation for Acceptable Indoor Air Quality. Ashrae 2007. doi:ANSI/ASHRAE Standard 62.1-2004.

[8]https://santemontreal.qc.ca/en/public/coronavirus-covid-19/situation-of-the-coronavirus-covid-19-in-montreal/