Compute the overall infectivity
compute_lambda(incid, si_distr)a list (as obtained from function `process_I_multivariant`) of two multidimensional arrays ("local" and "imported") containing values of the incidence for each time step (1st dimension), location (2nd dimension) and pathogen/strain/variant (3rd dimension)
a matrix where each column contains the probability mass function for the discrete serial interval for each of the pathogen/strain/variants, starting with the probability mass function for day 0 in the first row, which should be 0. Each column in the matrix should sum to 1
a multidimensional array containing values of the overall infectivity for each time step (1st dimension), location (2nd dimension) and pathogen/strain/variant (3rd dimension). The overall infectivity for a given location and pathogen/strain/variant represents the sum of the incidence for that location and that pathogen/strain/variant at all previous time steps, weighted by the current infectivity of those past incident cases. Pre-calculating the overall infectivity makes the algorithm much faster
n_v <- 2
n_loc <- 3 # 3 locations
T <- 100 # 100 time steps
priors <- default_priors()
# constant incidence 10 per day everywhere
incid <- array(10, dim = c(T, n_loc, n_v))
incid <- process_I_multivariant(incid)
# arbitrary serial interval, same for both variants
w_v <- c(0, 0.2, 0.5, 0.3)
si_distr <- cbind(w_v, w_v)
lambda <- compute_lambda(incid, si_distr)