From e1c61de5a0e693e2f24a1c4a10336e2a1c4563cb Mon Sep 17 00:00:00 2001 From: Naeem Model Date: Wed, 10 Jan 2024 14:50:22 +0000 Subject: Rename ID and IDEA --- R/ID.R | 46 ---------------------------------------------- 1 file changed, 46 deletions(-) delete mode 100644 R/ID.R (limited to 'R/ID.R') diff --git a/R/ID.R b/R/ID.R deleted file mode 100644 index 7e8a04d..0000000 --- a/R/ID.R +++ /dev/null @@ -1,46 +0,0 @@ -#' ID method -#' -#' This function implements a least squares estimation method of R0 due to -#' Fisman et al. (PloS One, 2013). See details for implementation notes. -#' -#' The method is based on a straightforward incidence decay model. The estimate -#' of R0 is the value which minimizes the sum of squares between observed case -#' counts and cases counts 'expected' under the model. -#' -#' This method is based on an approximation of the SIR model, which is most -#' valid at the beginning of an epidemic. The method assumes that the mean of -#' the serial distribution (sometimes called the serial interval) is known. The -#' final estimate can be quite sensitive to this value, so sensitivity testing -#' is strongly recommended. Users should be careful about units of time (e.g., -#' are counts observed daily or weekly?) when implementing. -#' -#' @param NT Vector of case counts. -#' @param mu Mean of the serial distribution. This needs to match case counts -#' in time units. For example, if case counts are weekly and the -#' serial distribution has a mean of seven days, then \code{mu} should -#' be set to one. If case counts are daily and the serial distribution -#' has a mean of seven days, then \code{mu} should be set to seven. -#' -#' @return \code{ID} returns a single value, the estimate of R0. -#' -#' @examples -#' # Weekly data: -#' NT <- c(1, 4, 10, 5, 3, 4, 19, 3, 3, 14, 4) -#' -#' # Obtain R0 when the serial distribution has a mean of five days. -#' ID(NT, mu = 5 / 7) -#' -#' # Obtain R0 when the serial distribution has a mean of three days. -#' ID(NT, mu = 3 / 7) -#' -#' @export -ID <- function(NT, mu) { - NT <- as.numeric(NT) - TT <- length(NT) - s <- (1:TT) / mu - y <- log(NT) / s - - R0_ID <- exp(sum(y) / TT) - - return(R0_ID) -} -- cgit v1.2.3