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#------------------------------------------------------------------------------#
# OPTIC R Package Code Repository
# Copyright (C) 2023 by The RAND Corporation
# See README.md for information on usage and licensing
#------------------------------------------------------------------------------#
#' Calculates the exposure rate applied to each year provided month
#' of policy implementation and number of years to full implementation
#'
#' @param month month of year (as integer) that policy takes effect
#' @param n_years number of months until full implementation in effect
#' @param monthly_effect increment of exposure to apply each month; default is
#' ((1/n_years) / 12) (constant over the period)
#' @returns A vector of percentages, indicating change in exposure by year (relative to start month)
#' @examples
#'
#' # Calculate uniform increase in policy effect which ramps up across 10 years
#'
#' # Assume policy starts in July of the first year, then continues for 10 years
#' starting_month <- 7
#' implementation_years <- 10
#'
#' # Assume some policy effect (which is the target effect for simulations)
#' policy_effect <- 2
#'
#' exposure_by_year <- calculate_exposure(starting_month, implementation_years)
#'
#' # Based on exposure by year, calculate policy effect by year:
#' plot(policy_effect*exposure_by_year)
#'
#' @export
calculate_exposure <- function(month, n_years, monthly_effect=(1/n_years)/12) {
top <- n_years - 1
total_times <- 1:top
# compute year 1 average effect first
fraction_year_enacted <- (13 - month) / 12
average_effect_while_enacted <- 0.5 * fraction_year_enacted * (1 / n_years)
average_effect_over_year1 <- fraction_year_enacted * average_effect_while_enacted
# mid years
mid_years_values <- average_effect_over_year1 + total_times * (1 / n_years)
# final year
final_year_value <- ((13 - month) * 1 + (month - 1) - calc_constant(month - 1) * monthly_effect) / 12
return(c(average_effect_over_year1, mid_years_values, final_year_value))
}
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