vaccinate_prob#
- class vaccinate_prob(vaccine, days, label=None, prob=None, subtarget=None, booster=False, **kwargs)[source]#
Bases:
BaseVaccination
Probability-based vaccination
This vaccine intervention allocates vaccines parametrized by the daily probability of being vaccinated.
- Parameters:
vaccine (dict/str) – which vaccine to use; see below for dict parameters
label (str) – if vaccine is supplied as a dict, the name of the vaccine
days (int/arr) – the day or array of days to apply the interventions
prob (float) – probability of being vaccinated (i.e., fraction of the population)
booster (bool) – whether it’s a booster (i.e. targeted to vaccinated people) or not
subtarget (dict) – subtarget intervention to people with particular indices (see test_num() for details)
kwargs (dict) – passed to Intervention()
If
vaccine
is supplied as a dictionary, it must have the following parameters:nab_eff
: the waning efficacy of neutralizing antibodies at preventing infectionnab_init
: the initial antibody level (higher = more protection)nab_boost
: how much of a boost being vaccinated on top of a previous dose or natural infection providesdoses
: the number of doses required to be fully vaccinatedinterval
: the interval between doses (integer)entries for efficacy against each of the strains (e.g.
b117
)
See
parameters.py
for additional examples of these parameters.Example:
pfizer = cv.vaccinate_prob(vaccine='pfizer', days=30, prob=0.7) cv.Sim(interventions=pfizer, use_waning=True).run().plot()
Methods