solveSIR: Solving SIR models

In TeaKov/serostat: Modeling Infectious Disease Parameters Based on Serological and Social Contact Data R Package

Description

Solves a mathematical SIR model, with or without vaccinated portion of newborns or constant force of infection, given timings, parameters and state.

Usage

solveSIR(t, parameters, state, fun)

Arguments

t	Timings of the integration.
parameters	Contains all the model parameters: natural mortality rate mu, disease-related mortality alpha, transmission parameter beta, recovery rate nu, portion of vaccinated newborns p, and total population size N. The parameter ndims specifies the number of row and columns of the subpopulation matrix, and nparams specifies the dimension of the ‘nu’ parameter (SIR_SubPop).
state	The initial values of the model: S are the susceptibles, I are the infected, and R are the immune or recovered.
fun	This specifies which SIR model you want to use: SIR_Vac is the SIR model with a portion of vaccinated newborns (Halloran), SIR_NoVac is the SIR model without any vaccinated portion, SIR_ConstFOI is the SIR model with constant force of infection at endemic state and without a portion of vaccinated newborns, and SIR_SubPop is the SIR model that uses a mixing matrix that specifies a subpopulation.

Examples

# Without portion of vaccinated newborns
t <- seq(0,1600,0.01)
state <- c(S=4999,I=1,R=0)
params <- c(mu=1/75,beta=0.0005,nu=1,N=5000,alpha=0)
result <- solveSIR(t, params, state, SIR_NoVac)
print(result)

# With portion of vaccinated newborns
t <- seq(0,1600,0.01)
state <- c(S=4999,I=1,R=0)
params <- c(mu=1/75,beta=0.0005,nu=1,N=5000,p=0.4,alpha=0)
result <- solveSIR(t, params, state, SIR_Vac)
print(result)

# With constant force of infection
t <- seq(0,90,by=0.01)
state <- c(s=0.99,i=0.01,r=0)
params <- c(lambda = 0.05, nu=1/(14/365))
result <- solveSIR(t, params, state, SIR_ConstFOI)
print(result)

# With subpopulation mixing matrix
t <- seq(0,10000,by=0.01)
state <- c(s=c(0.8,0.8),i=c(0.2,0.2), r=c(0.0,0.0))
params <- c(betatilde=c(0.05,0.0,0.0,0.05), nu=c(1/30,1/30), mu=0.001, ndims=2, nparams=2)
result <- solveSIR(t, params, state, SIR_SubPop)
print(result)

TeaKov/serostat documentation built on May 21, 2019, 1:21 p.m.