calc_beta: Estimates beta from a given R0 (Raster)

In qleclerc/efficientspatial: Efficient Spatial Modelling of Epidemics

Description

Estimates beta for an epidemic with a given R0 in a specific population in a Rasterlayer object, and calculates the expanded kernel matrix D to use when simulating an epidemic.

Usage

calc_beta(rasterl, dist_kernel, contact_mat, R0 = 1.8, sigma = 1/2.6)

Arguments

rasterl	The RasterLayer object containing the population data.
dist_kernel	The distance kernel matrix.
contact_mat	The contact matrix for mixing between age groups.
R0	The desired value for R0.
sigma	The desired value for the recovery rate.

Details

This function is automatically executed when using the prep_simulation function. It uses the Next Generation Matrix approach to derive beta from R0.

Value

Returns the value of beta and assigns the D matrix to the global environment.

Examples

#Create a RasterLayer object:
test_data = raster(nrow=10, ncol=10, xmn=1, xmx=100000, ymn=1, ymx=100000)
values(test_data) = runif(100, 1, 1000)

#Calculate distance kernel matrix and load age mixing matrix:
dist_mat = calc_dist_mat(test_data)
dist_kernel = calc_dist_kernel(dist_mat, dist_c = 87, test_data, alpha=0.95, p=6.6, p2=1.53, aa=35)
load_contact_mat()

beta = calc_beta(test_data, dist_kernel, contact_mat, R0=1.8, sigma=1/2.6)

qleclerc/efficientspatial documentation built on May 23, 2019, 1:24 p.m.