Open richfitz opened 1 year ago
Starting from the base sir model in examples
r_SI <- beta * S * I / N deriv(S) <- -r_SI deriv(I) <- r_SI - sigma * I deriv(R) <- sigma * I initial(S) <- N - I0 initial(I) <- I0 initial(R) <- 0 N <- 1e7 I0 <- user(1) beta <- user(24) sigma <- 12 delta <- 1 / 5
add cumulative infections
initial(total_infected) <- 0 deriv(total_infected) <- r_SI
and from that, we want to do a comparison against data for which we have incidence
incidence_observed <- data() compare(incidence_observed) ~ poisson(incidence_modelled + rexp(exp_noise)) exp_noise <- 1e8
which means we need an incidence measure, which we could write as
incidence_modelled <- total_infected - delay(total_infected, 7) # with t in days, this is weekly incidence
Starting from the base sir model in examples
add cumulative infections
and from that, we want to do a comparison against data for which we have incidence
which means we need an incidence measure, which we could write as