No impact from changing the “nab_eff” parameter
EMDominic opened this issue · 1 comments
EMDominic commented
Describe the bug
The docstring for the probability-based vaccination function states that if ‘vaccine’ is supplied as a dictionary, it must have the following parameters: nab_eff, nab_init, nab_boost, doses, interval and entries for efficacy against each of the strains. In implementing a custom vaccine, we included the parameter ‘nab_eff’. However, we found that changing the ‘nab_eff’ parameter values made no difference to the simulation results.
To reproduce
Steps to reproduce the behavior:
- Define a custom vaccine. 2. Configure the simulation 3. Run the simulation
import covasim as cv
custom_vaccine1 = dict(nab_eff=dict(alpha_inf=1.08,
alpha_inf_diff=1.812,
beta_inf=0.967,
alpha_symp_inf=-0.739, beta_symp_inf=0.038,
alpha_sev_symp=-0.014, beta_sev_symp=0.079),
nab_init=dict(dist='normal', par1=-1, par2=2),
nab_boost=4,
doses=2,
interval=21)
custom_vaccine2 = dict(nab_eff=dict(alpha_inf=2,
alpha_inf_diff=2,
beta_inf=2,
alpha_symp_inf=-1, beta_symp_inf=1,
alpha_sev_symp=-0.1, beta_sev_symp=1),
nab_init=dict(dist='normal', par1=-1, par2=2),
nab_boost=4,
doses=2,
interval=21)
# Define probability based vaccination
vaccinate1 = cv.vaccinate_prob(vaccine=custom_vaccine1, days=[range(20,100)], prob=0.8)
vaccinate2= cv.vaccinate_prob(vaccine=custom_vaccine2, days=[range(20,100)], prob=0.8)
pars = dict(
pop_size = 50e3,
pop_infected = 100,
start_day = '2020-04-01',
end_day = '2021-04-01')
sim1 = cv.Sim(pars=pars, interventions=vaccinate1)
sim2 = cv.Sim(pars=pars, interventions=vaccinate2)
msim = cv.MultiSim([sim1, sim2])
msim.run()
Platform:
- Covasim version: 3.1.2 (2022-01-16)
cliffckerr commented
Thanks @EMDominic and sorry for the extremely slow reply! We'll take a look at this in the 3.1.5 release of Covasim.