replace child chunks for set 2

Author: avallecam

instructors/02-practical-tutors.qmd

@@ -182,216 +182,15 @@ Write your answers to the questions above:
 
 ##### Ebola (sample)
 
-```{r}
-#| warning: false
-#| eval: false
-
-# Load packages -----------------------------------------------------------
-library(epiparameter)
-library(EpiNow2)
-library(tidyverse)
-
-# Read reported cases -----------------------------------------------------
-dat_ebola <- readr::read_rds(
-  "https://epiverse-trace.github.io/tutorials-middle/data/ebola_35days.rds"  #<DIFFERENT PER GROUP>
-) %>%
-  dplyr::select(date, confirm = cases)
-
-# Define a generation time from {epiparameter} to {EpiNow2} ---------------
-
-# access a serial interval
-ebola_serialint <- epiparameter::epiparameter_db(
-  disease = "ebola",
-  epi_name = "serial",
-  single_epiparameter = TRUE
-)
-
-# extract parameters from {epiparameter} object
-ebola_serialint_params <- epiparameter::get_parameters(ebola_serialint)
-
-# adapt {epiparameter} to {EpiNow2} distribution inferfase
-# preferred
-ebola_generationtime <- EpiNow2::Gamma(
-  shape = ebola_serialint_params["shape"],
-  scale = ebola_serialint_params["scale"]
-)
-# or
-ebola_generationtime <- EpiNow2::Gamma(
-  mean = ebola_serialint$summary_stats$mean,
-  sd = ebola_serialint$summary_stats$sd
-)
-
-
-# Define the delays from infection to case report for {EpiNow2} -----------
-
-# define delay from symptom onset to case report
-# or reporting delay
-ebola_reportdelay <- EpiNow2::LogNormal(
-  meanlog = EpiNow2::Normal(mean = 1.4, sd = 0.5),
-  sdlog = EpiNow2::Normal(mean = 0.25, sd = 0.2),
-  max = 5
-)
-
-# define a delay from infection to symptom onset
-# or incubation period
-ebola_incubationtime <- epiparameter::epiparameter_db(
-  disease = "ebola",
-  epi_name = "incubation",
-  single_epiparameter = TRUE
-)
-
-# incubation period: extract distribution parameters
-ebola_incubationtime_params <- epiparameter::get_parameters(
-  ebola_incubationtime
-)
-
-# incubation period: discretize and extract maximum value (p = 99%)
-# preferred
-ebola_incubationtime_max <- ebola_incubationtime %>%
-  epiparameter::discretise() %>%
-  quantile(p = 0.99)
-# or
-ebola_incubationtime_max <- ebola_incubationtime %>%
-  quantile(p = 0.99) %>%
-  base::round()
-
-# incubation period: adapt to {EpiNow2} distribution interface
-ebola_incubationtime_epinow <- EpiNow2::Gamma(
-  shape = ebola_incubationtime_params["shape"],
-  scale = ebola_incubationtime_params["scale"],
-  max = ebola_incubationtime_max
-)
-
-# collect required input
-ebola_generationtime
-ebola_reportdelay
-ebola_incubationtime_epinow
-
-
-# Set the number of parallel cores for {EpiNow2} --------------------------
-withr::local_options(list(mc.cores = parallel::detectCores() - 1))
-
-
-# Estimate transmission using EpiNow2::epinow() ---------------------------
-# with EpiNow2::*_opts() functions for generation time, delays, and stan.
-ebola_estimates <- EpiNow2::epinow(
-  data = dat_ebola,
-  generation_time = EpiNow2::generation_time_opts(ebola_generationtime),
-  delays = EpiNow2::delay_opts(ebola_incubationtime_epinow + ebola_reportdelay),
-  stan = EpiNow2::stan_opts(samples = 1000, chains = 3)
-)
-
+```{r, file = "fig/02-practical-instructor-1-G2.R", eval = FALSE}
 
-# Print plot and summary table outputs ------------------------------------
-summary(ebola_estimates)
-plot(ebola_estimates)
 ```
 
-##### COVID (sample)
-
-```{r}
-#| warning: false
-#| eval: false
-
-# Load packages -----------------------------------------------------------
-library(epiparameter)
-library(EpiNow2)
-library(tidyverse)
-
-# Read reported cases -----------------------------------------------------
-dat_covid <- read_rds(
-  "https://epiverse-trace.github.io/tutorials-middle/data/covid_30days.rds"  #<DIFFERENT PER GROUP>
-) %>%
-  dplyr::select(date, confirm)
-
-# Define a generation time from {epiparameter} to {EpiNow2} ---------------
-
-# access a serial interval
-covid_serialint <- epiparameter::epiparameter_db(
-  disease = "covid",
-  epi_name = "serial",
-  single_epiparameter = TRUE
-)
-
-# extract parameters from {epiparameter} object
-covid_serialint_params <- epiparameter::get_parameters(covid_serialint)
-
-# adapt {epiparameter} to {EpiNow2} distribution inferfase
-# preferred
-covid_generationtime <- EpiNow2::LogNormal(
-  meanlog = covid_serialint_params["meanlog"],
-  sdlog = covid_serialint_params["sdlog"]
-)
-# or
-covid_generationtime <- EpiNow2::LogNormal(
-  mean = covid_serialint$summary_stats$mean,
-  sd = covid_serialint$summary_stats$sd
-)
-
-
-# Define the delays from infection to case report for {EpiNow2} -----------
-
-# define delay from symptom onset to case report
-# or reporting delay
-covid_reportdelay <- EpiNow2::Gamma(
-  mean = EpiNow2::Normal(mean = 2, sd = 0.5),
-  sd = EpiNow2::Normal(mean = 1, sd = 0.5),
-  max = 5
-)
-
-# define a delay from infection to symptom onset
-# or incubation period
-covid_incubationtime <- epiparameter::epiparameter_db(
-  disease = "covid",
-  epi_name = "incubation",
-  single_epiparameter = TRUE
-)
-
-# incubation period: extract distribution parameters
-covid_incubationtime_params <- epiparameter::get_parameters(
-  covid_incubationtime
-)
-
-# incubation period: discretize and extract maximum value (p = 99%)
-# preferred
-covid_incubationtime_max <- covid_incubationtime %>%
-  epiparameter::discretise() %>%
-  quantile(p = 0.99)
-# or
-ebola_incubationtime_max <- covid_incubationtime %>%
-  quantile(p = 0.99) %>%
-  base::round()
-
-# incubation period: adapt to {EpiNow2} distribution interface
-covid_incubationtime_epinow <- EpiNow2::LogNormal(
-  meanlog = covid_incubationtime_params["meanlog"],
-  sdlog = covid_incubationtime_params["sdlog"],
-  max = covid_incubationtime_max
-)
-
-# collect required input
-covid_generationtime
-covid_reportdelay
-covid_incubationtime_epinow
 
+##### COVID (sample)
 
-# Set the number of parallel cores for {EpiNow2} --------------------------
-withr::local_options(list(mc.cores = parallel::detectCores() - 1))
-
-
-# Estimate transmission using EpiNow2::epinow() ---------------------------
-# with EpiNow2::*_opts() functions for generation time, delays, and stan.
-covid_estimates <- EpiNow2::epinow(
-  data = dat_covid,
-  generation_time = EpiNow2::generation_time_opts(covid_generationtime),
-  delays = EpiNow2::delay_opts(covid_reportdelay + covid_incubationtime_epinow),
-  stan = EpiNow2::stan_opts(samples = 1000, chains = 3)
-)
-
+```{r, file = "fig/02-practical-instructor-1-G1.R", eval = FALSE}
 
-# Print plot and summary table outputs ------------------------------------
-summary(covid_estimates)
-plot(covid_estimates)
 ```
 
 #### Outputs
@@ -647,156 +446,14 @@ Write your answers to the questions above:
 
 ##### COVID (sample)
 
-```{r}
-#| warning: false
-#| eval: false
-
-# Load packages -----------------------------------------------------------
-library(cfr)
-library(epiparameter)
-library(tidyverse)
-
-
-# Read reported cases -----------------------------------------------------
-covid_dat <- read_rds(
-  "https://epiverse-trace.github.io/tutorials-middle/data/diamond_70days.rds" 
-)
-
-covid_dat
-
-
-# Create incidence object ------------------------------------------------
-covid_incidence <- covid_dat %>%
-  incidence2::incidence(
-    date_index = "date",
-    counts = c("cases", "deaths"),
-    complete_dates = TRUE
-  )
-
-plot(covid_incidence)
-
-
-# Confirm {cfr} data input format ----------------------------------------
-
-# does input data already adapted to {cfr} input? Yes.
-covid_adapted <- covid_dat
-# does input data require to be adapted to {cfr}? No.
-# covid_adapted <- covid_incidence %>%
-#   cfr::prepare_data(
-#     cases = "cases",
-#     deaths = "deaths"
-#   )
-
-covid_adapted
-
-# Access delay distribution -----------------------------------------------
-covid_delay <- epiparameter::epiparameter_db(
-  disease = "covid",
-  epi_name = "onset-to-death",
-  single_epiparameter = TRUE
-)
-
-
-# Estimate naive and adjusted CFR ----------------------------------------
-
-# Estimate Static Delay-Adjusted CFR
-covid_dat %>%
-  filter(
-    date < ymd(20200301)
-  ) %>% 
-  cfr::cfr_static()
+```{r, file = "fig/02-practical-instructor-2-G1.R", eval = FALSE}
 
-# Estimate Static Delay-Adjusted CFR
-covid_dat %>%
-  filter(
-    date < ymd(20200301)
-  ) %>% 
-  cfr::cfr_static(
-    delay_density = function(x) density(covid_delay, x)
-  )
-
-
-# CFR estimates in whole data --------------------------------------------
-
-# Estimate Static Delay-Adjusted CFR
-covid_dat %>% 
-  cfr::cfr_static()
-
-# Estimate Static Delay-Adjusted CFR
-covid_dat %>%
-  cfr::cfr_static(
-    delay_density = function(x) density(covid_delay, x)
-  )
 ```
 
 ##### MERS (sample)
 
-```{r}
-#| warning: false
-#| eval: false
-
-# Load packages -----------------------------------------------------------
-library(cfr)
-library(epiparameter)
-library(tidyverse)
-
-
-# Read reported cases -----------------------------------------------------
-mers_dat <- readr::read_rds(
-  "https://epiverse-trace.github.io/tutorials-middle/data/mers_linelist.rds"
-)
-
-mers_dat
-
-
-# Create incidence object ------------------------------------------------
-mers_incidence <- mers_dat %>%
-  incidence2::incidence(
-    date_index = c("dt_onset", "dt_death"),
-    complete_dates = TRUE
-  )
-
-plot(mers_incidence)
-
-
-# Confirm {cfr} data input format ----------------------------------------
-
-# does input data already adapted to {cfr} input? No.
-# mers_adapted <- mers_dat
-# does input data require to be adapted to {cfr}? Yes.
-mers_adapted <- mers_incidence %>%
-  cfr::prepare_data(
-    cases = "dt_onset",
-    deaths = "dt_death"
-  )
-
-mers_adapted
-
-# Access delay distribution -----------------------------------------------
-mers_delay <- epiparameter::epiparameter_db(
-  disease = "mers",
-  epi_name = "onset-to-death",
-  single_epiparameter = TRUE
-)
-
-
-# Estimate naive and adjusted CFR ----------------------------------------
-
-# Estimate Static CFR
-mers_adapted %>%
-  # filter(
-  #   #<COMPLETE>
-  # ) %>%
-  cfr::cfr_static()
+```{r, file = "fig/02-practical-instructor-2-G2.R", eval = FALSE}
 
-# Estimate Static Delay-Adjusted CFR
-mers_adapted %>%
-  # filter(
-  #   #<COMPLETE>
-  # ) %>%
-  cfr::cfr_static(
-    delay_density = function(x) density(mers_delay, x)
-  )
 ```
 
 #### Outputs