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updated new cases method

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This commit is contained in:
Luis Aleixo 2024-05-17 17:05:10 +02:00
parent ed5b0d0e27
commit 04b8e91639
4 changed files with 16 additions and 13 deletions
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2
caimira/apps/calculator/report_generator.py
View file

@ -431,7 +431,7 @@ def manufacture_alternative_scenarios(form: VirusFormData) -> typing.Dict[str, m
scenarios['Neither ventilation nor masks'] = without_mask_or_vent.build_mc_model()
else:
no_short_range_alternative = dataclass_utils.replace(form, short_range_interactions=[])
no_short_range_alternative = dataclass_utils.replace(form, short_range_interactions=[], total_people=form.total_people - form.short_range_total_people)
scenarios['Base scenario without short-range interactions'] = no_short_range_alternative.build_mc_model()
return scenarios

9
caimira/apps/templates/base/calculator.report.html.j2
View file

@ -56,16 +56,15 @@
<div class="tab-pane show active" id="results" role="tabpanel" aria-labelledby="results-tab" style="padding: 1%">
{% set long_range_prob_inf = prob_inf %}
{% set long_range_expected_cases = expected_new_cases %}
{% set total_expected_new_cases = expected_new_cases %}
{# Update values if short range option is "short_range_yes" #}
{% if form.short_range_option == "short_range_yes" %}
{% set scenario = alternative_scenarios.stats.values() | first %}
{# Probability of infection values #}
{% set long_range_prob_inf = scenario.probability_of_infection %}
{% set long_range_expected_cases = scenario.expected_new_cases %}
{# Expected new case values #}
{% set total_expected_new_cases = scenario.expected_new_cases + expected_new_cases %}
{% set long_range_expected_cases = scenario.expected_new_cases %}
{% if form.exposure_option == 'p_probabilistic_exposure' %}
{% set long_range_prob_probabilistic_exposure = scenario.prob_probabilistic_exposure %}
{% endif %}
@ -134,12 +133,12 @@
{% block report_summary %}
<div class="flex-row align-self-center">
<div class="align-self-center alert alert-dark mb-0" role="alert">
Taking into account the uncertainties tied to the model variables, in this scenario and assuming all occupants are exposed equally (i.e. without short-range interactions), the <b>probability of one exposed occupant getting infected is {{ long_range_prob_inf | non_zero_percentage }}</b> and the <b>expected number of new cases is {{ total_expected_new_cases | float_format }}</b>*.
Taking into account the uncertainties tied to the model variables, in this scenario and assuming all occupants are exposed equally (i.e. without short-range interactions), the <b>probability of one exposed occupant getting infected is {{ long_range_prob_inf | non_zero_percentage }}</b> and the <b>expected number of new cases is {{ long_range_expected_cases | float_format }}</b>*.
</div>
{% if form.short_range_option == "short_range_yes" %}
<br>
<div class="align-self-center alert alert-dark mb-0" role="alert">
In this scenario, assuming <b>short-range interactions</b> occur, the <b>probability of one exposed occupant getting infected can go as high as {{ prob_inf | non_zero_percentage }}</b>.
In this scenario, assuming <b>short-range interactions</b> occur, the <b>probability of one exposed occupant getting infected can go as high as {{ prob_inf | non_zero_percentage }}</b> and the <b>expected number of new cases is {{ expected_new_cases | float_format }}</b>.
</div>
{% endif %}
{% block probabilistic_exposure_probability %}

4
caimira/apps/templates/cern/calculator.report.html.j2
View file

@ -70,7 +70,7 @@
<div class="alert alert-success mb-0" role="alert">
<strong>Acceptable:</strong>
{% endif %}
Taking into account the uncertainties tied to the model variables, in this scenario and assuming all occupants are exposed equally (i.e. without short-range interactions), the <b>probability of one exposed occupant getting infected is {{long_range_prob_inf | non_zero_percentage}}</b> and the <b>expected number of new cases is {{expected_new_cases | float_format}}</b>*.
Taking into account the uncertainties tied to the model variables, in this scenario and assuming all occupants are exposed equally (i.e. without short-range interactions), the <b>probability of one exposed occupant getting infected is {{long_range_prob_inf | non_zero_percentage}}</b> and the <b>expected number of new cases is {{ long_range_expected_cases | float_format }}</b>*.
</div>
{% if form.short_range_option == "short_range_yes" %}
<br>
@ -84,7 +84,7 @@
<div class="alert alert-success mb-0" role="alert">
<strong>Acceptable:</strong>
{% endif %}
In this scenario, assuming <b>short-range interactions</b> occur, the <b>probability of one exposed occupant getting infected can go as high as {{prob_inf | non_zero_percentage}}</b>.
In this scenario, assuming <b>short-range interactions</b> occur, the <b>probability of one exposed occupant getting infected can go as high as {{prob_inf | non_zero_percentage}}</b> and the <b>expected number of new cases is {{ expected_new_cases | float_format }}</b>.
</div>
{% endif %}

14
caimira/models.py
View file

@ -1817,13 +1817,17 @@ class ExposureModel:
"with dynamic occupancy")
"""
The expect_new_cases should always take the long-range infection_probability and multiply by the occupants exposed to long-range.
The expected_new_cases has two different use case scenarios:
1) Long-range only: take the infection_probability and multiply by the occupants exposed to long-range.
2) Short- and long-range: take the infection_probability of long-range multiplied by the occupants exposed to long-range only, added
to the infection_probability of short- and long-range multiplied by the occupants exposed to short-range only.
"""
# If short-range interaction are defined, the total exposed people
# is only those of the short-range interactions.
exposed = self.exposed_to_short_range if self.short_range != () else self.exposed.number
return self.infection_probability() * exposed / 100
if self.short_range != ():
new_cases_long_range = nested_replace(self, {'short_range': (),}).infection_probability() * (self.exposed.number - self.exposed_to_short_range)
return (new_cases_long_range + (self.infection_probability() * self.exposed_to_short_range)) / 100
return self.infection_probability() * self.exposed.number / 100
def reproduction_number(self) -> _VectorisedFloat:
"""