R/predict_tungro.R

In adamhsparks/epirice: Simulation Modelling of Crop Diseases Using a Susceptible-Exposed-Infectious-Removed (SEIR) Model

#' Predict Rice Tungro Disease Incidence
#'
#' A dynamic mechanistic simulation of tungro disease of rice, causal agents
#' _Rice Tungro Spherical Virus_ and _Rice Tungro Bacilliform Virus_.
#' The model is driven by daily weather data, which can easily be accessed using
#'[get_wth()] to download weather data from \acronym{NASA} \acronym{POWER} using
#'\CRANpkg{nasapower}.
#'
#' @details
#' The model represents site size as 1 rice plant.
#'
#' Default values for this disease model are derived from Table 2 (Savary *et
#' al.* 2012).
#'
#' @note Adapted from \pkg{cropsim} package version 0.2.0-5 by Adam H. Sparks,
#' Department of Primary Industries and Regional Development, WA, AU.
#' Original model development: Serge Savary & Rene Pangga (IRRI).
#' Original \R implementation by Robert J. Hijmans, Rene Pangga, & Jorrel
#' Aunario (IRRI).
#'
#' @note
#' If the `wth` object provides _LAT_ and _LON_ columns, these will be included
#' in the output for mapping purposes. Both values must be present. These
#' columns are provided by default when using [get_wth()].
#'
#' @inherit predict_bacterial_blight
#'
#' @return A [data.table::data.table()] of disease intensity and infection
#' sites.  See [SEIR()] for a full description of the column values.
#'
#' @examplesIf interactive()
#'
#' # get weather for IRRI Zeigler Experiment Station in wet season 2000
#' wth <- get_wth(
#'   lonlat = c(121.25562, 14.6774),
#'   dates = c("2000-06-30", "2000-12-31")
#' )
#' tg <- predict_tungro(wth, emergence = "2000-07-01")
#' plot(x = tg$dates, y = tg$intensity, type = "l")
#'
#' @author Serge Savary, Ireneo Pangga, Robert Hijmans, Jorrel Khalil Aunario
#' and Adam H. Sparks
#'
#' @references Ling, K.C., and Tiongco, E.R., 1976. Effect of temperature on the
#' transmission of rice tungro virus by _Nephotettix virescens_.
#' Philippine Phytopathology 11:46-57.
#'
#' Ling, K.C., Palomar, M.K., 1966. Studies on rice plants infected with the
#' tungro virus at different ages. Philippines Agriculturist 50:165-177.
#'
#' Rivera, C.T. and Ou, S.H., 1965. Leafhopper transmission of tungro disease of
#' rice. Plant Disease Reporter 49:127-131.
#'
#' Savary, S., Nelson, A., Willocquet, L., Pangga, I., and Aunario, J.
#' Modeling and mapping potential epidemics of rice diseases globally. Crop
#' Protection, Volume 34, 2012, Pages 6-17, ISSN 0261-2194 DOI:
#' \doi{10.1016/j.cropro.2011.11.009}.
#'
#' Tiongco, E.R., Cabunagan, R.C., Flores, Z.M., Hibino, H., and Koganezawa, H.,
#' 1993. Serological monitoring of rice tungro disease development in the field:
#' its implication in disease management. Plant Disease 77:877-882. DOI:
#' \doi{10.1094/PD-77-0877}.
#'
#' @family predict functions
#'
#' @seealso
#' [SEIR()]
#'
#' @export
predict_tungro <- function(wth, emergence) {
  return(
    SEIR(
      wth = wth,
      emergence = emergence,
      onset = 25L,
      duration = 120L,
      rhlim = 90L,
      rainlim = 5L,
      H0 = 100L,
      I0 = 1L,
      RcA = cbind(
        c(0L, 15L, 30L, 45L, 60L, 75L, 90L, 105L, 120L),
        c(1.0, 1.0, 0.98, 0.73, 0.51, 0.34, 0, 0, 0)
      ),
      RcT =     cbind(
        c(
          9,
          10,
          13.1111,
          16.2222,
          19.3333,
          22.4444,
          25.5555,
          28.6666,
          31.7777,
          34.8888,
          37.9999,
          40
        ),
        c(0, 0.13, 0.65, 0.75, 0.83, 0.89, 0.93, 0.97, 1.0, 0.96, 0.93, 0)
      ),
      RcOpt = 0.18,
      p = 6L,
      i = 120L,
      Sx = 100L,
      a = 1L,
      RRS = 0.01,
      RRG = 0.1
    )
  )
}