shorten precision
@@ -71,14 +71,7 @@ def make_pars(set_prognoses=False, prog_by_age=True, version=None, **kwargs):
pars['nab_decay'] = dict(form='nab_growth_decay', growth_time=22, decay_rate1=np.log(2)/100, decay_time1=250, decay_rate2=np.log(2)/3650, decay_time2=365)
pars['nab_kin'] = None # Constructed during sim initialization using the nab_decay parameters
pars['nab_boost'] = 1.5 # Multiplicative factor applied to a person's nab levels if they get reinfected. # TODO: add source
- pars['nab_eff'] = dict( # Parameters to map nabs to efficacy
- alpha_inf=2.1238829151987986,
- beta_inf=0.605829675352584,
- alpha_symp_inf=-1.9999999981702656,
- beta_symp_inf=1.6107573711547896,
- alpha_sev_symp=1.0266617843930277,
- beta_sev_symp=0.03960555611994232
- )
+ pars['nab_eff'] = dict(alpha_inf=2.12, beta_inf=0.61, alpha_symp_inf=-2.0, beta_symp_inf=1.61, alpha_sev_symp=1.03, beta_sev_symp=0.04) # Parameters to map nabs to efficacy for natural infection -- see below for vaccine-derived
pars['rel_imm_symp'] = dict(asymp=0.85, mild=1, severe=1.5) # Relative immunity from natural infection varies by symptoms
pars['immunity'] = None # Matrix of immunity and cross-immunity factors, set by init_immunity() in immunity.py
@@ -530,12 +523,12 @@ def get_vaccine_dose_pars(default=False):
# Default vaccine NAb efficacy is nearly identical to infection -- only alpha_inf differs
default_nab_eff = dict(
- alpha_inf = 1.161680688637602,
- beta_inf = 0.605829675352584,
- alpha_symp_inf = -1.9999999981702656,
- beta_symp_inf = 1.6107573711547896,
- alpha_sev_symp = 1.0266617843930277,
- beta_sev_symp = 0.03960555611994232
+ alpha_inf = 1.16,
+ beta_inf = 0.61,
+ alpha_symp_inf = -2.0,
+ beta_symp_inf = 1.61,
+ alpha_sev_symp = 1.03,
+ beta_sev_symp = 0.04,
)
pars = dict(
