person("Waleed", "Almutiry", email = "wkmtierie@qu.edu.sa", role = c("aut", "cre")),
person("Rob", "Deardon", role = c("aut", "ths")),
person("Vineetha", "Warriyar K. V.", role = "ctb")
Depends: graphics, stats, utils, coda, parallel, R (>= 3.5.0)

Description: Provides tools for simulating from continuous-time individual level models of disease transmission, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based and/or contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed (SINR) compartmental frameworks. An overview of the implemented continuous-time individual level models for epidemics is given by Almutiry and Deardon (2019) <doi:10.1515/ijb-2017-0092>.

Description: Provides tools for simulating from continuous-time individual level models of disease transmission, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based and/or contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed (SINR) compartmental frameworks. <doi:10.18637/jss.v098.i10>.

Title: Estimation of Time Varying Reproduction Numbers and Restored
Incidence Curves Using Variational Techniques
Authors@R: c(person("Luis", "Alvarez", email = "lalvarez@ulpgc.es", role = c("aut", "cre"),
person("Jean-David", "Morel", role = "ctb", comment = c(ORCID = "0000-0002-7122-9924")),
person("Jean-Michel", "Morel", role = "ctb", comment = c(ORCID = "0000-0002-6108-897X"))
Description: Estimation,  by inverting a renewal equation,
of time-varying reproduction numbers and restored incidence curves with
festive days and weekly biases corrected as described in
Suggests: knitr, ggplot2, grid, dplyr, testthat (>= 3.0.0), rmarkdown
Author: Luis Alvarez [aut, cre] (<https://orcid.org/0000-0002-8443-9162>),

Author: Luis Alvarez [aut, cre] (<https://orcid.org/0000-0002-6953-9587>),

Alvarez et al. (2022) <doi:10.3390/biology11040540>. EpiInvert can manage
daily incidence data and weekly aggregated incidence data. This version of the
package also includes EpiInvertForecast, a learning method for the short time
forecast of the restored incidence curve.