adamkucharski

adamkucharski

# Correcting for real-time CFR bias -------------------------------------------------
# This script builds on the theory outlined in this vignette:
# https://epiverse-trace.github.io/cfr/articles/estimate_from_individual_data.html


# Load packages
library(cfr)
library(dplyr)
library(ggplot2)
library(gridExtra)

adamkucharski

# Define delay params
param_1 <- log(5)
param_2 <- 1

# Onsets at time 0
initial_onsets <- 100

# CFR
cfr <- 0.5

adamkucharski

# Define R0
r_number <- 1.4

# Final size model
attack_rate <- finalsize::final_size(r_number)$n_infected

print(attack_rate)

# Calculate total exposures over the whole epidemic
# (note: later in epidemic, now-immune people will be re-exposed)

adamkucharski

# Define parameters
xx <- 1e3 # Number of values to simulate from positive and negative distribution
xx_pos <- xx; xx_neg <- xx

set.seed(1)

# Set up plot
par(mfcol=c(2,2),mgp=c(2,0.7,0),mar = c(3,3,1,3))

for(kk in 1:2){

adamkucharski

# Define parameters
bkg_val <- 15 # background value
xx <- 1e3 # Number of values to simulate from positive and negative distribution
xx_pos <- xx; xx_neg <- xx

set.seed(1)

# Set up plot
par(mfcol=c(2,2),mgp=c(2,0.7,0),mar = c(3,3,1,3))

adamkucharski

# Analysis of VE during epidemic when vaccine protection < infection protection -------------------------------------------------------------
# Adam Kucharski (2024)


# Define assumptions about exposure over time in epidemic -----------------

xx <- seq(0,6,1/30) # time points for model
peak_time <- 3 # peak in months post-vaccine campaign
peak_width <- 0.8 # variance in epidemic width (i.e. sd of distribution)
exposure_prop <- 0.6 # proportion of population exposure during wave

adamkucharski

adamkucharski

# Example code for simulation recovery of infection dynamics from deaths for COVID -----------------------------------------

# Load libraries:

# install.packages("EpiNow2", repos = "https://epiforecasts.r-universe.dev")
library(EpiNow2)

# Simulate data and delays -----------------------------------------

# Simulate infections with a sharp drop

adamkucharski

# - - - - - - - - - - - - - - - - - - - - - - - 
# Code by Adam Kucharski to accompany post 'Counting current COVID infections' (2nd Jan 2024)
# Post is available at: https://kucharski.substack.com
# Code in this file is shared under an MIT license (https://opensource.org/license/mit/)
# - - - - - - - - - - - - - - - - - - - - - - - 

# Load libraries
library(dplyr)
library(readr)