Merge branch 'feature/masks_efficiency' into 'master'
Inward efficiency of masks See merge request cara/cara!250
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commit
0414e15e4b
4 changed files with 31 additions and 3 deletions
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@ -11,7 +11,7 @@ from cara import data
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import cara.data.weather
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import cara.monte_carlo as mc
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from .. import calculator
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from cara.monte_carlo.data import activity_distributions, virus_distributions
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from cara.monte_carlo.data import activity_distributions, virus_distributions, mask_distributions
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LOG = logging.getLogger(__name__)
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@ -359,7 +359,10 @@ class FormData:
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def mask(self) -> models.Mask:
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# Initializes the mask type if mask wearing is "continuous", otherwise instantiates the mask attribute as
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# the "No mask"-mask
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mask = models.Mask.types[self.mask_type if self.mask_wearing_option == "mask_on" else 'No mask']
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if self.mask_wearing_option == 'mask_on':
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mask = mask_distributions[self.mask_type]
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else:
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mask = models.Mask.types['No mask']
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return mask
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def infected_population(self) -> mc.InfectedPopulation:
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@ -71,3 +71,6 @@ We wish to thank CERN’s HSE Unit, Beams Department, Experimental Physics Depar
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[54] Leung, N.H.L et al. Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med (2020). 10.1038/s41591-020-0843-2.<br>
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[55] Asadi, S., Cappa, C.D., Barreda, S. et al. Efficacy of masks and face coverings in controlling outward aerosol particle emission from expiratory activities. Sci Rep 10, 15665 (2020). https://doi.org/10.1038/s41598-020-72798-7.<br>
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[56] Endo A, Abbott S et al. Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China [version 3; peer review: 2 approved]. Wellcome Open Res 2020, 5:67. doi:10.12688/wellcomeopenres.15842.3.<br>
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[57] Jin Pan, Charbel Harb, Weinan Leng & Linsey C. Marr (2021) Inward and outward effectiveness of cloth masks, a surgical mask, and a face shield, Aerosol Science and Technology, 55:6, 718-733, doi: 10.1080/02786826.2021.1890687.<br>
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[58] C. Makison Booth, M. Clayton, B. Crook, J.M. Gawn, Effectiveness of surgical masks against influenza bioaerosols, Journal of Hospital Infection, Volume 84, Issue 1, 2013, Pages 22-26, https://doi.org/10.1016/j.jhin.2013.02.007.<br>
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[59] Riediker, M., Monn, C. (2021). Simulation of SARS-CoV-2 Aerosol Emissions in the Infected Population and Resulting Airborne Exposures in Different Indoor Scenarios. Aerosol Air Qual. Res. 21, 200531. https://doi.org/10.4209/aaqr.2020.08.0531.<br>
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@ -1,7 +1,7 @@
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import numpy as np
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import cara.monte_carlo as mc
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from cara.monte_carlo.sampleable import Normal,LogNormal,LogCustomKernel
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from cara.monte_carlo.sampleable import Normal,LogNormal,LogCustomKernel, Uniform
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# From CERN-OPEN-2021-04 and refererences therein
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@ -58,3 +58,13 @@ virus_distributions = {
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infectious_dose=60/1.6,
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),
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}
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# From:
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# https://doi.org/10.1080/02786826.2021.1890687
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# https://doi.org/10.1016/j.jhin.2013.02.007
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# https://doi.org/10.4209/aaqr.2020.08.0531
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mask_distributions = {
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'Type I': mc.Mask(Uniform(0.25, 0.80)),
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'FFP2': mc.Mask(Uniform(0.83, 0.91)),
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}
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@ -28,6 +28,18 @@ class Normal(SampleableDistribution):
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return np.random.normal(self.mean, self.standard_deviation, size=size)
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class Uniform(SampleableDistribution):
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"""
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Defines a continuous uniform distribution
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"""
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def __init__(self, low: float, high: float):
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self.low = low
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self.high = high
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def generate_samples(self, size: int) -> float_array_size_n:
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return np.random.uniform(self.low, self.high, size=size)
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class LogNormal(SampleableDistribution):
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"""
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Defines a lognormal distribution (i.e. Gaussian distribution vs. the
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