Merge remote-tracking branch 'origin/feature/virions_plot' into feature/virions_plot

cara/models.py

@@ -50,7 +50,6 @@ from .utils import method_cache
 
 from .dataclass_utils import nested_replace
 
-
 # Define types for items supporting vectorisation. In the future this may be replaced
 # by ``np.ndarray[<type>]`` once/if that syntax is supported. Note that vectorization
 # implies 1d arrays: multi-dimensional arrays are not supported.
@@ -429,6 +428,9 @@ class Virus:
     #: Dose to initiate infection, in RNA copies
     infectious_dose: _VectorisedFloat
 
+    #: viable-to-RNA virus ratio as a function of the viral load
+    viable_to_RNA: _VectorisedFloat
+
     #: Pre-populated examples of Viruses.
     types: typing.ClassVar[typing.Dict[str, "Virus"]]
 
@@ -465,19 +467,23 @@ Virus.types = {
         # as per https://www.dhs.gov/publication/st-master-question-list-covid-19
         # 50 comes from Buonanno et al.
         infectious_dose=50.,
+        viable_to_RNA = 0.5,
     ),
     'SARS_CoV_2_B117': SARSCoV2(
         # also called VOC-202012/01
         viral_load_in_sputum=1e9,
         infectious_dose=30.,
+        viable_to_RNA = 0.5,
     ),
     'SARS_CoV_2_P1': SARSCoV2(
         viral_load_in_sputum=1e9,
         infectious_dose=1/0.045,
+        viable_to_RNA = 0.5,
     ),
     'SARS_CoV_2_B16172': SARSCoV2(
         viral_load_in_sputum=1e9,
         infectious_dose=30/1.6,
+        viable_to_RNA = 0.5,
     ),
 }
 
@@ -539,7 +545,7 @@ class _ExpirationBase:
     #: Pre-populated examples of Expirations.
     types: typing.ClassVar[typing.Dict[str, "_ExpirationBase"]]
 
-    def aerosols(self, mask: Mask):
+    def aerosols(self, mask: Mask, cn_B: float, cn_L: float):
         """
         total volume of aerosols expired per volume of air (mL/cm^3).
         """
@@ -608,9 +614,9 @@ class MultipleExpiration(_ExpirationBase):
             raise ValueError("expirations and weigths should contain the"
                              "same number of elements")
 
-    def aerosols(self, mask: Mask):
+    def aerosols(self, mask: Mask, cn_B: float, cn_L: float):
         return np.array([
-            weight * expiration.aerosols(mask) / sum(self.weights)
+            weight * expiration.aerosols(mask, cn_B, cn_L) / sum(self.weights)
             for weight,expiration in zip(self.weights,self.expirations)
         ]).sum(axis=0)
 
@@ -676,7 +682,11 @@ class InfectedPopulation(Population):
     #: The type of expiration that is being emitted whilst doing the activity.
     expiration: _ExpirationBase
 
-    def emission_rate_when_present(self, cn_B: float, cn_L: float) -> _VectorisedFloat:
+    #: The percentage of host immunity
+    host_immunity: float = 0.
+
+   
+    def emission_rate_when_present(self, cn_B: float = 0.06, cn_L: float = 0.2) -> _VectorisedFloat:
         """
         The emission rate if the infected population is present.
 
@@ -718,7 +728,7 @@ class InfectedPopulation(Population):
         # with a declaration of state change time, as is the case for things
         # like Ventilation.
 
-        return self.emission_rate_when_present()
+        return self.emission_rate_when_present(cn_B=0.06, cn_L=0.2)
 
     def emission_rate(self, time) -> _VectorisedFloat:
         """
@@ -888,11 +898,13 @@ class ExposureModel:
 
     def infection_probability(self) -> _VectorisedFloat:
         exposure = self.exposure()
+        print('oi', self.concentration_model.infected.virus.viable_to_RNA)
 
+        # Dose
         inf_aero = (
             self.exposed.activity.inhalation_rate *
             (1 - self.exposed.mask.inhale_efficiency()) *
-            exposure * self.fraction_deposited
+            exposure * self.fraction_deposited * (self.concentration_model.infected.virus.viable_to_RNA * (1 - self.concentration_model.infected.host_immunity))
         )
 
         # Probability of infection.

cara/monte_carlo/data.py

@@ -44,18 +44,22 @@ virus_distributions = {
     'SARS_CoV_2': mc.SARSCoV2(
                 viral_load_in_sputum=symptomatic_vl_frequencies,
                 infectious_dose=100,
+                viable_to_RNA=Uniform(0.15, 0.45),
                 ),
     'SARS_CoV_2_B117': mc.SARSCoV2(
                 viral_load_in_sputum=symptomatic_vl_frequencies,
                 infectious_dose=60,
+                viable_to_RNA=Uniform(0.15, 0.45),
                 ),
     'SARS_CoV_2_P1': mc.SARSCoV2(
                 viral_load_in_sputum=symptomatic_vl_frequencies,
                 infectious_dose=100/2.25,
+                viable_to_RNA=Uniform(0.15, 0.45),
                 ),
     'SARS_CoV_2_B16172': mc.SARSCoV2(
                 viral_load_in_sputum=symptomatic_vl_frequencies,
                 infectious_dose=60/1.6,
+                viable_to_RNA=Uniform(0.15, 0.45),
                 ),
 }
 
@@ -67,4 +71,4 @@ virus_distributions = {
 mask_distributions = {
     'Type I': mc.Mask(Uniform(0.25, 0.80)),
     'FFP2': mc.Mask(Uniform(0.83, 0.91)),
-}
+}