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02_EPIESTIM_reports.R
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02_EPIESTIM_reports.R
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# Load required libraries
library(tidyverse)
# install.packages('EpiEstim', repos = c('https://mrc-ide.r-universe.dev', 'https://cloud.r-project.org'))
library(EpiEstim)
# Load data
url <- "https://raw.githubusercontent.com/cmilando/RtEval/main/all_data.RDS"
all_data <- readRDS(url(url))
# get incidence
incidence_df <- data.frame(
dates = all_data$cases$day,
I = as.vector(all_data$cases$daily_reports)
)
colnames(incidence_df) <- c('dates', 'I')
head(incidence_df)
tail(incidence_df)
dim(incidence_df)
# Serial interval from data PMF
si_distr <- as.matrix(all_data$serial$Px)
if (all_data$serial$Day[1] == 1) si_distr <- c(0, si_distr)
si_distr
# Estimate R DAILY
getR <- EpiEstim::estimate_R(
incid = incidence_df,
method = "non_parametric_si",
config = make_config(list(
si_distr = si_distr,
t_start = 2:nrow(incidence_df),
t_end = 2:nrow(incidence_df)
)),
backimputation_window = 10
)
#
INCUBATION_SHIFT = round(weighted.mean(x = all_data$incubation$Day,
w = all_data$incubation$Px))
REPORTINGDELAY_SHIFT = round(weighted.mean(x = all_data$reporting_delay$Day,
w = all_data$reporting_delay$Px))
# PLOT DATA
plot_data <- data.frame( ## ANNE
package = "EpiEstim",
date = all_data$cases$day[getR$R$t_end] - INCUBATION_SHIFT - REPORTINGDELAY_SHIFT,
Rt_median = getR$R$`Median(R)`,
Rt_lb = getR$R$`Quantile.0.025(R)`,
Rt_ub = getR$R$`Quantile.0.975(R)`
)
as_tibble(plot_data) %>%
ggplot() +
geom_hline(yintercept = 1, linetype = "11") +
# *******
# this is the true r(t), back-calculated
geom_line(aes(x = Day, y = Rt_calc), data = all_data$rt) +
# *******
geom_ribbon(aes(x = date, ymin = Rt_lb, ymax = Rt_ub, fill = package),
alpha = 0.25) +
geom_line(aes(x = date, y = Rt_median, color = package)) +
coord_cartesian(ylim = c(0, 5)) +
xlab("Days") +
ylab("Rt") +
theme(
axis.text = element_text(size = 10),
axis.title = element_text(size = 14)
)
saveRDS(plot_data, "plot_objects/plot_data_EpiEstim_reports.RDS")