Andree Valle Campos avallecam

# Load libraries
library(tidyverse)

# Create data for the simple regression model (Panel A)
simple_data <- data.frame(
  Predictor = "Aware that humans can get TBD",
  Estimate = 0.3,
  SE = 0.1
)

# pak::pak("treedater")

library(treedater)
#> Loading required package: ape
#> Loading required package: limSolve

library(tidyverse)

We can estimate the relative risk for the causal interpretation of CFR estimates (Lipsitch et al.)

two-by-two table

	non-death	death
44-younger	311	768
45+older	51	299

CFR (stratified)

library(deSolve)   # Paquete deSolve para resolver las ecuaciones diferenciales
library(tidyverse) # Paquetes ggplot2 y dplyr de tidyverse
library(cowplot) # Paquete gridExtra para unir gráficos.
#> Warning: package 'cowplot' was built under R version 4.4.1
#> 
#> Attaching package: 'cowplot'
#> The following object is masked from 'package:lubridate':
#> 
#>     stamp

# from py to R ------------------------------------------------------------

# to convert the a python notebook to Rmd file
# with https://pkgs.rstudio.com/rmarkdown/reference/convert_ipynb.html

# for one sample ----------------------------------------------------------

set.seed(123)

	library(socialmixr)
	library(countrycode)
	library(tidyverse)

	# Get all countries names and... regex!!
	all_countries <- countrycode::codelist

	# Filter countries in the Africa continent
	africa_countries <- all_countries %>%
	select(continent, country.name.en,country.name.en.regex) %>%

	``` r
	if(!require("pak")) install.packages("pak")

	new_packages <- c(
	"incidence2",
	"outbreaks",
	"tidyverse"
	)

	pak::pkg_install(new_packages)

	``` r
	library(tidyverse)

	# epiparameter ------------------------------------------------------------

	library(epiparameter)

	# get set of epidist objects
	epidist_input <- epiparameter::epidist_db(
	disease = "covid",

	``` r
	# packages ----------------------------------------------------------------

	library(tidyverse)
	library(incidence2)

	# input -------------------------------------------------------------------

	onset <- tibble(
	date = seq(ymd(20200101),ymd(20200104),1),

	If I need to install python packages

	```{python}
	# install packages
	pip install pandas
	pip install matplotlib
	```

	I can install python (!!) and the packages in R using `{reticulate}`