Added viable_to_RNA distribution on Virus class
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2 changed files with 17 additions and 4 deletions
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@ -50,7 +50,6 @@ from .utils import method_cache
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from .dataclass_utils import nested_replace
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# Define types for items supporting vectorisation. In the future this may be replaced
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# by ``np.ndarray[<type>]`` once/if that syntax is supported. Note that vectorization
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# implies 1d arrays: multi-dimensional arrays are not supported.
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@ -429,6 +428,9 @@ class Virus:
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#: Dose to initiate infection, in RNA copies
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infectious_dose: _VectorisedFloat
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#: viable-to-RNA virus ratio as a function of the viral load
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viable_to_RNA: _VectorisedFloat
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#: Pre-populated examples of Viruses.
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types: typing.ClassVar[typing.Dict[str, "Virus"]]
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@ -465,19 +467,23 @@ Virus.types = {
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# as per https://www.dhs.gov/publication/st-master-question-list-covid-19
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# 50 comes from Buonanno et al.
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infectious_dose=50.,
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viable_to_RNA = 0.5,
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),
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'SARS_CoV_2_B117': SARSCoV2(
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# also called VOC-202012/01
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viral_load_in_sputum=1e9,
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infectious_dose=30.,
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viable_to_RNA = 0.5,
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),
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'SARS_CoV_2_P1': SARSCoV2(
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viral_load_in_sputum=1e9,
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infectious_dose=1/0.045,
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viable_to_RNA = 0.5,
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),
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'SARS_CoV_2_B16172': SARSCoV2(
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viral_load_in_sputum=1e9,
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infectious_dose=30/1.6,
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viable_to_RNA = 0.5,
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),
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}
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@ -677,8 +683,9 @@ class InfectedPopulation(Population):
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expiration: _ExpirationBase
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#: The percentage of host immunity
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host_immunity: float = 0.0
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host_immunity: float = 0.
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def emission_rate_when_present(self, cn_B: float = 0.06, cn_L: float = 0.2) -> _VectorisedFloat:
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"""
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The emission rate if the infected population is present.
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@ -891,11 +898,13 @@ class ExposureModel:
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def infection_probability(self) -> _VectorisedFloat:
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exposure = self.exposure()
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print('oi', self.concentration_model.infected.virus.viable_to_RNA)
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# Dose
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inf_aero = (
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self.exposed.activity.inhalation_rate *
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(1 - self.exposed.mask.inhale_efficiency()) *
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exposure * self.fraction_deposited
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exposure * self.fraction_deposited * (self.concentration_model.infected.virus.viable_to_RNA * (1 - self.concentration_model.infected.host_immunity))
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)
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# Probability of infection.
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@ -44,18 +44,22 @@ virus_distributions = {
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'SARS_CoV_2': mc.SARSCoV2(
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viral_load_in_sputum=symptomatic_vl_frequencies,
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infectious_dose=100,
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viable_to_RNA=Uniform(0.15, 0.45),
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),
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'SARS_CoV_2_B117': mc.SARSCoV2(
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viral_load_in_sputum=symptomatic_vl_frequencies,
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infectious_dose=60,
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viable_to_RNA=Uniform(0.15, 0.45),
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),
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'SARS_CoV_2_P1': mc.SARSCoV2(
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viral_load_in_sputum=symptomatic_vl_frequencies,
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infectious_dose=100/2.25,
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viable_to_RNA=Uniform(0.15, 0.45),
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),
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'SARS_CoV_2_B16172': mc.SARSCoV2(
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viral_load_in_sputum=symptomatic_vl_frequencies,
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infectious_dose=60/1.6,
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viable_to_RNA=Uniform(0.15, 0.45),
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),
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}
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@ -67,4 +71,4 @@ virus_distributions = {
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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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}
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