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This is a generic implementation of a combined vaccine and vaccine efficacy modelling framework first proposed in White et al (2015). Please cite this work if you use this vaccine model.

The model consists of two parts. The first predicts antibody titres over time following initital dose(s) and subsequent booster doses.

titre(t)=titredose(ρdoseerdoses(ttdose)+(1ρdose)erdosel(ttdose)) titre(t) = titre_{dose} \left( \rho_{dose} e^{-r_{dose}^s (t - t_{dose})} + (1 - \rho_{dose}) e^{-r_{dose}^l (t - t_{dose})} \right)

Where subscript dosedose indexes for the primary series dose(s) or subsequent booster doses, titretitre is the maximum titre on receipt of a dose or booster, rhorho the proportion of the response that is short-lived and rs=loge(2)dsr^s = \frac{\log_e(2)}{d^s} and rl=loge(2)dlr^l = \frac{\log_e(2)}{d^l} where dsd^s and dld^l are the half-lives of the short and long lived components of the antibody response respectively.

The second translates antibody titre to vaccine efficacy using a parameterised dose response curve.

V(t)=Vmax(111+(titre(t)β)α) V(t) = V_{max} \left( 1 - \frac{1}{1 + \left( \frac{titre(t)}{\beta} \right)^\alpha } \right)

Where VmaxV_{max} is the maximum vaccine efficacy, alphaalpha the shape parameter and betabeta the scale parameter

Installation

You can install boostr from github with:

pak::pkg_install("mrc-ide/boostr")