Calculate the probability a disease will emerge and cause a sustained outbreak (\(R > 1\)) based on R and initial cases
Source:R/probability_emergence.R
probability_emergence.RdThe method for the evolution of pathogen emergence described in
Antia et al. (2003) (doi:10.1038/nature02104
). The model is a multi-type
branching process model with an initial (wild-type) reproduction number,
usually below 1, and a evolved reproduction number that is
greater than 1, and thus can cause a sustained human-to-human epidemic.
The reproduction number for a pathogen changes at the mutation_rate.
Usage
probability_emergence(
R_wild,
R_mutant,
mutation_rate,
num_init_infect,
tol = 1e-10,
max_iter = 1000
)Arguments
- R_wild
A
numberspecifying the R parameter (i.e. average secondary cases per infectious individual) for the wild-type pathogen.- R_mutant
A
numberor vector ofnumbersspecifying the R parameter (i.e. average secondary cases per infectious individual) for the mutant pathogen(s). If there is more than one value supplied toR_mutant, then the first element is the reproduction number for \(m - 1\) mutant and the last element is the reproduction number for the \(m\) mutant (i.e. fully evolved).- mutation_rate
A
numberspecifying the mutation rate (\(\mu\)), must be between zero and one.- num_init_infect
An
integer(or at least "integerish" if stored as double) specifying the number of initial infections.- tol
A
numberfor the tolerance of the numerical convergence. Default is1e-10.- max_iter
A
numberfor the maximum number of iterations for the optimisation. Default is1000.
Details
Following Antia et al. (2003), we assume that the mutation rate for all variants is the same.
References
Antia, R., Regoes, R., Koella, J. & Bergstrom, C. T. (2003) The role of evolution in the emergence of infectious diseases. Nature 426, 658–661. doi:10.1038/nature02104