epiBR0: Basic reproduction number (R0)
In EpiILM: Spatial and Network Based Individual Level Models for Epidemics

Description Usage Arguments Value Examples

Gives a Monte Carlo estimate of the basic reproduction number for a specified SIR model and data set

epiBR0 (x = NULL, y = NULL, contact = NULL, sus.par, trans.par = NULL, beta,

        spark = NULL, infperiod, Sformula = NULL, Tformula = NULL, tmax,

        niter)

`x`	X coordinates of individuals
`y`	Y coordinates of individuals
`contact`	Contact network(s)
`sus.par`	Susceptibility parameter(>0)
`trans.par`	Transmissibility parameter(>0)
`beta`	Spatial parameter(s) (>0) or network parameter (s) (>0) if contact is used
`spark`	Sparks parameter (>=0), representing infections unexplained by other parts of the model or infections coming in from outside the observed population, default value is zero
`infperiod`	Length of infectious period for each individual
`Sformula`	An object of class formula. See formula Individual-level covariate information associated with susceptibility can be passed through this argument. An expression of the form `~ model` is interpreted as a specification that the susceptibility function, Ω_S(i) is modelled by a linear predictor specified symbolically by the model term. Such a model consists of a series of terms separated by `+` and `-` operators. If there is no susceptibility covariate information, `Sformula` is null.
`Tformula`	An object of class formula. See formula Individual-level covariate information associated with transmissibility can be passed through this argument. An expression of the form `~ -1+model` is interpreted as a specification that the transmissibility function, Ω_T(j) is modelled by a linear predictor specified symbolically by the model terms without the incorporation of the intercept term. Such a model consists of a series of terms separated by `+` and `-` operators. If there is no transmissibility covariate information, `Tformula` is null.
`tmax`	The last time point of simulation
`niter`	Number of epidemic simulations to calculate basic reproduction number

A list is returned with the following components:

`BasicR0`	The basic reproduction number value
`simulated_BR0`	Number of infections per simulation

# generate 100 X-Y coordinates for a distance-based ILM

x <- runif(100, 0, 10)

y <- runif(100, 0, 10)

# Suppose we know the length of infectious period for each individual. Also, assume 
# susceptibility parameter = 1.5 and spatial parameter = 5 for this SIR model

infperiod <- rep(3, 100)

# For a 1000 iteration with a last observed time point 15, we can estimate the basic 
# reproduction number using Monte Carlo simulation

out <- epiBR0(x = x, y = y,  sus.par = 1.5,  beta = 5, infperiod= infperiod,  
     
               tmax = 15, niter = 1000)

out$BasicR0