GDILM_SEIRS_Sim_Par_Est {GDILM.SEIRS} | R Documentation |
GDILM SEIRS for a Simulation Study
Description
This function conducts a simulation study for the Geographically Dependent Individual Level Model (GDILM) of infectious disease transmission, incorporating reinfection dynamics within the Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) framework, using a user-defined grid size. It applies a likelihood based Monte Carlo Expectation Conditional Maximization (MCECM) algorithm to estimate model parameters and compute the AIC.
Usage
GDILM_SEIRS_Sim_Par_Est(
GridDim1,
GridDim2,
NPostPerGrid,
MaxTimePand,
tau0,
lambda0,
alphaS0,
delta0,
alphaT0,
PopMin,
PopMax,
InfFraction,
ReInfFraction,
InfPrd,
IncPrd,
NIterMC,
NIterMCECM
)
Arguments
GridDim1 |
First dimension of the grid |
GridDim2 |
Second dimension of the grid |
NPostPerGrid |
Number of postal codes per grid cell |
MaxTimePand |
Last time point of the pandemic |
tau0 |
Initial value for spatial precision |
lambda0 |
Initial value for spatial dependence |
alphaS0 |
Initial value for the susceptibility intercept |
delta0 |
Initial value for the spatial decay parameter |
alphaT0 |
Initial value for the infectivity intercept |
PopMin |
Minimum population per postal code |
PopMax |
Maximum population per postal code |
InfFraction |
Fraction of each grid cell's population to be infected |
ReInfFraction |
Fraction of each grid cell's population to be reinfected |
InfPrd |
Infectious period that can be obtained either from the literature or by fitting an SEIRS model to the data |
IncPrd |
Incubation period that can be obtained either from the literature or by fitting an SEIRS model to the data |
NIterMC |
Number of MCMC iterations |
NIterMCECM |
Number of MCECM iterations |
Value
alphaS
Estimate of alpha S
BetaCovInf
Estimate of beta vector for the individual level infection covariate
BetaCovSus
Estimate of beta vector for the areal susceptibility to first infection covariate
BetaCovSusReInf
Estimate of beta vector for the areal susceptibility to reinfection covariate
alphaT
Estimate of alpha T
delta
Estimate of delta
tau1
Estimate of tau
lambda1
Estimate of lambda
AIC
AIC of the fitted GDILM SEIRS
Examples
GDILM_SEIRS_Sim_Par_Est(5,5,10,30,0.7, 0.5, -1, 2.5, 0,40, 50,0.3,0.6, 3, 3, 10, 3)