reference short-range paper from Yuguo Li

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CERN\Andrejh 2022-05-30 17:33:37 +02:00
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commit 7850c91cee
4 changed files with 15 additions and 4 deletions

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@ -45,10 +45,12 @@ CARA COVID Airborne Risk Assessment tool
© Copyright 2020-2021 CERN. All rights not expressly granted are reserved.
**For use of the model**
**For use of the CARA model**
Henriques A, Mounet N, Aleixo L, Elson P, Devine J, Azzopardi G, Andreini M, Rognlien M, Tarocco N, Tang J. (2022). Modelling airborne transmission of SARS-CoV-2 using CARA: risk assessment for enclosed spaces. _Interface Focus 20210076_. https://doi.org/10.1098/rsfs.2021.0076
_Note that the short-range component of the model has not yet been published._
Reference on the Short-range expiratory jet model from:
Wei Jia, Jianjian Wei, Pan Cheng, Qun Wang, Yuguo Li. (2022). Exposure and respiratory infection risk via the short-range airborne route. _Building and Environment_ *219*: 109166.
https://doi.org/10.1016/j.buildenv.2022.109166
## Applications

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@ -19,7 +19,7 @@ CARA stands for COVID Airborne Risk Assessment and was developed in the spring o
The mathematical and physical model simulate the airborne spread of SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture and a two-stage exhaled jet model, and estimates the risk of COVID-19 airborne transmission therein. The results DO NOT include other known modes of SARS-CoV-2 transmission. Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as good hand hygiene and other barrier measures.<br>
<p>The methodology, mathematical equations and parameters of the model are published here in the CARA paper: <a href="https://doi.org/10.1098/rsfs.2021.0076"> Modelling airborne transmission of SARS-CoV-2 using CARA: risk assessment for enclosed spaces</a>.</p>
<p><i>Note that the short-range component of the model has not yet been published.</i></p>
<p>The short-range component of the model was adapted from <i>Wei et al. (2022)</i> <a href="https://doi.org/10.1016/j.buildenv.2022.109166"> Exposure and respiratory infection risk via the short-range airborne route</a> .</p>
The model used is based on scientific publications relating to airborne transmission of infectious diseases, virology, epidemiology and aerosol science. It can be used to compare the effectiveness of different airborne-related risk mitigation measures.

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@ -59,7 +59,14 @@
<li> Henriques A, Mounet N, Aleixo L, Elson P, Devine J, Azzopardi G, Andreini M, Rognlien M, Tarocco N, Tang J. (2022).
Modelling airborne transmission of SARS-CoV-2 using CARA: risk assessment for enclosed spaces.
<i>Interface Focus</i> <b>12</b>: 20210076. <a href=https://doi.org/10.1098/rsfs.2021.0076>doi.org/10.1098/rsfs.2021.0076</a> </li>
<a href=https://royalsocietypublishing.org/action/showCitFormats?doi=10.1098%2Frsfs.2021.0076><i>Download citation</i></a>
<a href=https://royalsocietypublishing.org/action/showCitFormats?doi=10.1098%2Frsfs.2021.0076><i>Download citation</i></a><br>
<b><i>Short-range expiratory jet model from:</i></b>
<ul>
<li> Wei Jia, Jianjian Wei, Pan Cheng, Qun Wang, Yuguo Li. (2022).
Exposure and respiratory infection risk via the short-range airborne route.
<i>Building and Environment</i> <b>219</b>: 109166. <a href=https://doi.org/10.1016/j.buildenv.2022.109166>doi.org/10.1016/j.buildenv.2022.109166</a>
</li>
</ul>
</ul>
<b>For use of the CARA web app:</b><br>
<ul>

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@ -1096,6 +1096,7 @@ class ShortRangeModel:
def dilution_factor(self) -> _VectorisedFloat:
'''
The dilution factor for the respective expiratory activity type.
Based on the two-stage (jet/puff) expiratory jet model by Wei et al (2022) - https://doi.org/10.1016/j.buildenv.2022.109166
'''
# Average mouth diameter
D = 0.02
@ -1158,6 +1159,7 @@ class ShortRangeModel:
concentration_model.infected.particle.diameter, long_range_normed_concentration)
# Short-range concentration formula. The long-range concentration is added in the concentration method (ExposureModel).
# based on continuum model proposed by
return ((1/dilution)*(jet_origin_concentration - long_range_normed_concentration_interpolated))
return 0.