def apply(self, sim):
''' Perform vaccination '''
t = sim.t
if t < self.start_day:
return
elif self.end_day is not None and t > self.end_day:
return
# Check that there are still vaccines
rel_t = t - self.start_day
if rel_t < len(self.daily_vaccines):
n_vaccines = sc.randround(self.daily_vaccines[rel_t] /
sim.rescale_vec[t])
else:
return
vacc_probs = np.ones(
sim.n
) # Begin by assigning equal vaccine weight (converted to a probability) to everyone
if self.subtarget is not None:
subtarget_inds, subtarget_vals = get_subtargets(
self.subtarget, sim)
vacc_probs[
subtarget_inds] = subtarget_vals # People being explicitly subtargeted
# First dose
# Don't give dose to people who have had at least one dose
vacc_inds = cvu.true(self.vaccinations > 0)
vacc_probs[vacc_inds] = 0.0
# Now choose who gets vaccinated and vaccinate them
n_vaccines = min(n_vaccines, (vacc_probs != 0).sum())
all_vacc_inds = cvu.choose_w(probs=vacc_probs,
n=n_vaccines,
unique=True) # Choose who actually tests
sim.results['new_doses'][t] += len(all_vacc_inds)
self.vaccinations[all_vacc_inds] = 1
self.delay_days[all_vacc_inds] = self.delay
self.first_dates[all_vacc_inds] = sim.t
# Calculate the effect per person
vacc_eff = self.cumulative[0] # Pull out corresponding effect sizes
rel_sus_eff = 0.5 + 0.5 * self.rel_sus
rel_symp_eff = 0.5 + 0.5 * self.rel_symp
# Apply the vaccine to people
#sim.people.rel_sus[all_vacc_inds] *= rel_sus_eff
#sim.people.symp_prob[all_vacc_inds] *= rel_symp_eff
sim.people.rel_sus[
all_vacc_inds] = self.orig_rel_sus[all_vacc_inds] * rel_sus_eff
sim.people.symp_prob[
all_vacc_inds] = self.orig_symp_prob[all_vacc_inds] * rel_symp_eff
all_vacc_inds2 = cvu.true(
(self.vaccinations == 1) * (self.delay_days > 0) *
(self.first_dates > 0) *
(self.first_dates + self.delay_days == sim.t))
rel_sus_eff2 = self.rel_sus
rel_symp_eff2 = self.rel_symp
#sim.people.rel_sus[all_vacc_inds2] *= rel_sus_eff2
#sim.people.symp_prob[all_vacc_inds2] *= rel_symp_eff2
sim.people.rel_sus[
all_vacc_inds2] = self.orig_rel_sus[all_vacc_inds2] * rel_sus_eff2
sim.people.symp_prob[all_vacc_inds2] = self.orig_symp_prob[
all_vacc_inds2] * rel_symp_eff2
self.vaccinations[all_vacc_inds2] = 2
sim.results['new_doses'][t] += len(all_vacc_inds2)
def apply(self, sim):
''' Perform vaccination '''
if sim.t >= np.min(self.days):
# Vaccinate people with their first dose
vacc_inds = np.array(
[],
dtype=int) # Initialize in case no one gets their first dose
for ind in find_day(self.days, sim.t, interv=self, sim=sim):
vacc_probs = np.zeros(sim['pop_size'])
unvacc_inds = sc.findinds(~sim.people.vaccinated)
if self.subtarget is not None:
subtarget_inds, subtarget_vals = get_subtargets(
self.subtarget, sim)
if len(subtarget_vals):
vacc_probs[
subtarget_inds] = subtarget_vals # People being explicitly subtargeted
else:
vacc_probs[
unvacc_inds] = self.prob # Assign equal vaccination probability to everyone
vacc_probs[cvu.true(
sim.people.dead)] *= 0.0 # Do not vaccinate dead people
vacc_inds = cvu.true(cvu.binomial_arr(
vacc_probs)) # Calculate who actually gets vaccinated
if len(vacc_inds):
self.vaccinated[sim.t] = vacc_inds
sim.people.flows['new_vaccinations'] += len(vacc_inds)
sim.people.flows['new_vaccinated'] += len(vacc_inds)
if self.p.interval is not None:
next_dose_day = sim.t + self.p.interval
if next_dose_day < sim['n_days']:
self.second_dose_days[next_dose_day] = vacc_inds
next_nab_day = sim.t + self.p.nab_interval
if next_nab_day < sim['n_days']:
self.first_dose_nab_days[next_nab_day] = vacc_inds
else:
self.first_dose_nab_days[sim.t] = vacc_inds
# Also, if appropriate, vaccinate people with their second dose
vacc_inds_dose2 = self.second_dose_days[sim.t]
if vacc_inds_dose2 is not None:
next_nab_day = sim.t + self.p.nab_interval
if next_nab_day < sim['n_days']:
self.second_dose_nab_days[next_nab_day] = vacc_inds_dose2
vacc_inds = np.concatenate((vacc_inds, vacc_inds_dose2),
axis=None)
sim.people.flows['new_vaccinations'] += len(vacc_inds_dose2)
# Update vaccine attributes in sim
if len(vacc_inds):
sim.people.vaccinated[vacc_inds] = True
sim.people.vaccine_source[vacc_inds] = self.index
self.vaccinations[vacc_inds] += 1
self.vaccination_dates[vacc_inds] = sim.t
# Update vaccine attributes in sim
sim.people.vaccinations[vacc_inds] = self.vaccinations[
vacc_inds]
# check whose nabs kick in today and then init_nabs for them!
vaccine_nabs_first_dose_inds = self.first_dose_nab_days[sim.t]
vaccine_nabs_second_dose_inds = self.second_dose_nab_days[sim.t]
vaccine_nabs_inds = [
vaccine_nabs_first_dose_inds, vaccine_nabs_second_dose_inds
]
for vaccinees in vaccine_nabs_inds:
if vaccinees is not None:
sim.people.date_vaccinated[vaccinees] = sim.t
cvi.init_nab(sim.people, vaccinees, prior_inf=False)
return