rtaCFR (which stands for real-time adjusted Case Fatality Rate) is a package that performs estimation of the real-time fatality rates with adjustment for reporting delay in deaths proposed by Qu et al. (2022) <DOI: 10.1038/s41598-022-23138-4>.
rtaCFR relies on the R-packages genlasso and Rtools, which are hosted on CRAN.
install.packages("devtools")
library(devtools)
source_url("https://github.com/lcyjames/rtaCFR/blob/main/CoreFunctions.R?raw=TRUE")
The package contains 2 functions:
| Functions | Description |
|---|---|
| rtaCFR.SIM | Generate a data set according to the simulation study in Qu et al. (2022) |
| rtaCFR.EST | Computation of the rtaCFR as proposed in Qu et al. (2022) |
rtaCFR.SIM
rtaCFR.SIM(ct, pt, seed = NA, F_mean = 15.43, F_shape = 2.03)
This function generates a data set according to the model in Qu et al. (2022) that takes the arguments:
ctis the number of confirmed cases, a vector of lengthNptis the proportion of confirmed cases who will eventually die from the disease, a vector of lengthNF_meanis the mean of the gamma distribution for the time from disease onset to deathF_shapeis the shape parameter of the gamma distribution for the time from disease onset to death
Take scenario (b) in the simulation study in Qu et al. (2022) as an example:
Data <- rtaCFR.SIM(ct = 3000-5*abs(100-c(1:200)), pt = 0.01*exp(0.012*c(1:200)), seed = 1)
head(Data)
# ct dt
#1 2505 0.1596081
#2 2510 0.6122235
#3 2515 1.3255914
#4 2520 2.2971944
#5 2525 3.4188380
#6 2530 4.6502343
This data structure is as follows:
ctis the number of confirmed casesdtis the number of deaths with reporting delay from disease onset to death
rtaCFR.EST
rtaCFR.EST(ct, dt, F_mean = 15.43, F_shape = 2.03, maxsteps = 10000)
This function computes the rtaCFR as proposed in Qu et al. (2022). The details of the arguments are as follows:
ctis the number of confirmed casesdtis the number of deathsF_meanis the mean of the gamma distribution for the time from disease onset to deathF_shapeis the shape parameter of the gamma distribution for the time from disease onset to deathmaxstepsis an integer specifying the maximum number of steps for the fused lasso to take before termination
Example:
Data <- rtaCFR.SIM(ct = 3000-5*abs(100-c(1:200)), pt = 0.01*exp(0.012*c(1:200)), seed = 1)
rt_fit <- rtaCFR.EST(ct = Data$ct, dt = Data$dt)
round(head(rt_fit$p_hat),4)
# [1] 0.0088 0.0096 0.0107 0.0131 0.0087 0.0134
round(tail(rt_fit$p_hat),4)
# [1] 0.1030 0.1131 0.1018 0.1135 0.1102 0.1024
plot(rt_fit$p_hat, type="b", pch = 19, ylab = "Fatality rates", xlab = "Time", col = "red", cex = 0.6)
lines(c(1:200), 0.01*exp(0.012*c(1:200)), lwd = 2)
legend("topleft", legend = c("rtaCFR", "true"), col = c("red", "black"), lty = c(1,1),lwd = c(1:2), pch = c(19,NA), cex = 0.8)
Lee Chun Yin, James <james-chun-yin.lee@polyu.edu.hk>
Qu, Y., Lee, C. Y., and Lam, K. F. (2022). A novel method to monitor COVID-19 fatality rate in real-time, a key metric to guide public health policy. Scientific Reports, 12(1), 18277. <DOI: 10.1038/s41598-022-23138-4>