This function, that can be wrapped within nosoiSim, runs a single-host transmission chain simulation, with a discrete host population structure (e.g. spatial, socio-economic, etc.). The simulation stops either at the end of given time (specified by length.sim) or when the number of hosts infected threshold (max.infected) is crossed.

singleDiscrete(
  length.sim,
  max.infected,
  init.individuals,
  init.structure,
  structure.matrix,
  diff.pExit = FALSE,
  timeDep.pExit = FALSE,
  hostCount.pExit = FALSE,
  pExit,
  param.pExit,
  diff.pMove = FALSE,
  timeDep.pMove = FALSE,
  hostCount.pMove = FALSE,
  pMove,
  param.pMove,
  diff.nContact = FALSE,
  timeDep.nContact = FALSE,
  hostCount.nContact = FALSE,
  nContact,
  param.nContact,
  diff.pTrans = FALSE,
  timeDep.pTrans = FALSE,
  hostCount.pTrans = FALSE,
  pTrans,
  param.pTrans,
  prefix.host = "H",
  print.progress = TRUE,
  print.step = 10
)

Arguments

length.sim

specifies the length (in unit of time) over which the simulation should be run.

max.infected

specifies the maximum number of hosts that can be infected in the simulation.

init.individuals

number of initially infected individuals.

init.structure

in which state (e.g. location) the initially infected individuals are located.

structure.matrix

transition matrix (probabilities) to go from location A (row) to B (column)

diff.pExit

is pExit different between states of the structured population (TRUE/FALSE)

timeDep.pExit

is pExit dependent on the absolute time of the simulation? (TRUE/FALSE)

hostCount.pExit

does pExit varies with the host count in the state? (TRUE/FALSE); diff.pExit should be TRUE.

pExit

function that gives the probability to exit the simulation for an infected host (either moving out, dying, etc.).

param.pExit

parameter names (list of functions) for the pExit.

diff.pMove

is pMove different between states of the structured population (TRUE/FALSE)

timeDep.pMove

is pMove dependent on the absolute time of the simulation (TRUE/FALSE)

hostCount.pMove

does pMove varies with the host count in the state? (TRUE/FALSE); diff.pMove should be TRUE.

pMove

function that gives the probability of a host moving as a function of time.

param.pMove

parameter names (list of functions) for the pMove.

diff.nContact

is nContact different between states of the structured population (TRUE/FALSE)

timeDep.nContact

is nContact dependent on the absolute time of the simulation? (TRUE/FALSE)

hostCount.nContact

does nContact varies with the host count in the state? (TRUE/FALSE); diff.nContact should be TRUE.

nContact

function that gives the number of potential transmission events per unit of time.

param.nContact

parameter names (list of functions) for param.nContact.

diff.pTrans

is pTrans different between states of the structured population (TRUE/FALSE)

timeDep.pTrans

is pTrans dependent on the absolute time of the simulation? (TRUE/FALSE)

hostCount.pTrans

does pTrans varies with the host count in the state? (TRUE/FALSE); diff.pTrans should be TRUE.

pTrans

function that gives the probability of transmit a pathogen as a function of time since infection.

param.pTrans

parameter names (list of functions) for the pExit.

prefix.host

character(s) to be used as a prefix for the hosts identification number.

print.progress

if TRUE, displays a progress bar (current time/length.sim).

print.step

print.progress is TRUE, step with which the progress message will be printed.

Value

An object of class nosoiSim, containing all results of the simulation.

Details

The pExit and pTrans functions should return a single probability (a number between 0 and 1), and nContact a positive natural number (positive integer) or 0.

The param arguments should be a list of functions or NA. Each item name in the parameter list should have the same name as the argument in the corresponding function.

The use of timeDep (switch to TRUE) makes the corresponding function use the argument prestime (for "present time").

Structure Matrix

The structure matrix provided provided should of class matrix, with the same number of rows and columns, rows representing departure state and column the arrival state. All rows should add to 1.

Structure Parameters

The pMove function should return a single probability (a number between 0 and 1).

The use of diff (switch to TRUE) makes the corresponding function use the argument current.in (for "currently in"). Your function should in that case give a result for every possible discrete state.

The use of hostCount (switch to TRUE) makes the corresponding function use the argument host.count.

Order of Arguments

The user specified function's arguments should follow this order: t (mandatory), prestime (optional, only if timeDep is TRUE), current.in (optional, only if diff is TRUE), host.count (optional, only if hostCount is TRUE) and parameters specified in the list.

See also

For simulations with a structure in continuous space, see singleContinuous. For simulations without any structures, see singleNone.

Examples

# \donttest{ t_incub_fct <- function(x){rnorm(x,mean = 5,sd=1)} p_max_fct <- function(x){rbeta(x,shape1 = 5,shape2=2)} p_Exit_fct <- function(t){return(0.08)} p_Move_fct <- function(t){return(0.1)} proba <- function(t,p_max,t_incub){ if(t <= t_incub){p=0} if(t >= t_incub){p=p_max} return(p) } time_contact = function(t){round(rnorm(1, 3, 1), 0)} transition.matrix = matrix(c(0,0.2,0.4,0.5,0,0.6,0.5,0.8,0), nrow = 3, ncol = 3, dimnames=list(c("A","B","C"),c("A","B","C"))) set.seed(805) test.nosoiA <- nosoiSim(type="single", popStructure="discrete", length=20, max.infected=100, init.individuals=1, init.structure="A", structure.matrix=transition.matrix, pMove=p_Move_fct, param.pMove=NA, nContact=time_contact, param.nContact=NA, pTrans = proba, param.pTrans = list(p_max=p_max_fct, t_incub=t_incub_fct), pExit=p_Exit_fct, param.pExit=NA)
#> Starting the simulation #> Initializing ...
#> running ...
#> Time: 10 (50% of maximum length). Hosts count: 22 (22% of maximum infected hosts).
#> done. #> The simulation has run for 16 units of time and a total of 122 hosts have been infected.
# }