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.Rd
The 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
number
specifying the R parameter (i.e. average secondary cases per infectious individual) for the wild-type pathogen.- R_mutant
A
number
or vector ofnumbers
specifying 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
number
specifying 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
number
for the tolerance of the numerical convergence. Default is1e-10
.- max_iter
A
number
for 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