initial_condition_sib_model: Provide Initial Condition for Function SIB_SS

In NetOrigin: Origin Estimation for Propagation Processes on Complex Networks

Provide Initial Condition for Function SIB_SS

Description

initial_condition_sib_model Compute Initial Condition for Function SIB_SS

Usage

initial_condition_sib_model(
  POP_node,
  sigma,
  mu_B,
  theta,
  node_in,
  in_prevalence = 0.001
)

Arguments

POP_node	vector, length represents number of cities/nodes; vector represents population at each node
sigma	symptomatic ratio, i.e., fraction of infected people that develop symptoms and are infective. (The remaining fraction enters directly the recovered compartment.)
mu_B	death rate of V.cholerae in the aquatic environment (day^-1)
theta	contamination rate
node_in	index/indices for initial infected node(s)
in_prevalence	initial prevalence of symptomatic infected in a node, default is 0.1%

Value

a 5 x number of nodes matrix, each row represents the following for all the nodes: Row 1: number of suspectible people, i.e., population excpect infected and recovered for each node; Row 2: number of infected people; Row 3: number of recovered people; Row 4: bacteria concentration in equilibrium with infected individuals; Row 2: number of infected people, but representing cumulative cases

Author(s)

Jun Li

Examples

set.seed(2020)
popu <- rep(20000, 10)
sigma <- 0.05
mu_B <- 0.2
theta_max <- 16
theta <- runif(10, 0.1, 0.9) * theta_max
y0 <- initial_condition_sib_model(popu, sigma, mu_B, theta, c(3))

NetOrigin documentation built on Sept. 8, 2023, 5:58 p.m.