GDILM.SEIRS (version 0.0.6)

GDILM_SEIRS_Par_Est: GDILM SEIRS for Real Data

Description

This function applies the Geographically Dependent Individual Level Model (GDILM) for infectious disease transmission, incorporating reinfection dynamics within the Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) framework, to real data. It employs a likelihood based Monte Carlo Expectation Conditional Maximization (MCECM) algorithm for parameter estimation and AIC calculation. This function requires two dataframes, named data and adjacency_matrix, along with the necessary parameters. Detailed information on the structure of these two datasets is provided in the package.

Usage

GDILM_SEIRS_Par_Est(
  data,
  adjacency_matrix,
  DimCovInf,
  DimCovSus,
  DimCovSusReInf,
  tau0,
  lambda0,
  alphaS0,
  delta0,
  alphaT0,
  InfPrd,
  IncPrd,
  NIterMC,
  NIterMCECM
)

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

Arguments

data

Dataset. The dataset should exactly match the data file in the data folder, including all the columns with the same names.

adjacency_matrix

Adjacency matrix representing the regions in the study area (0 if no connection between regions)

DimCovInf

Dimensions of the individual infectivity covariate

DimCovSus

Dimensions of the area-level susceptibility to initial infection covariate

DimCovSusReInf

Dimensions of the area-level susceptibility to reinfection covariate

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

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

Examples

# \donttest{
data(data)
data(adjacency_matrix)
GDILM_SEIRS_Par_Est(data,adjacency_matrix,2,2,2,0.5, 0.5, 1, 2, 1, 1, 1, 20, 2)
# }