| covid19BH | R Documentation |
The purpose of this page is to show the user how to format the Y input argument
in the pandemic_model function, when epidemiological data was obtained
outside of the load_covid function.
The Covid-19 data for the city of Belo Horizonte, MG - Brazil will be used to illustrate
how to correctly format the epidemiological data required in the pandemic_model function,
using the function format_data.
See the Examples section.
For complete information on the required data format,
check the Y input argument description in ?pandemic_model.
covid19BH
This data frame has 103 observations and 6 variables. It contains the number of Covid-19 confirmed cases and deaths for the city of Belo Horizonte, from the date of the first notified case in 2020-03-16 to 2020-06-26.
date - dates in the YYYY-MM-DD format
new_confirmed - number of new cases
new_deaths - number of new deaths
last_available_confirmed - cumulative number of cases
last_available_deaths - cumulative number of deaths
estimated_population_2019 - size of Belo Horizonte's population
https://brasil.io/dataset/covid19
CovidLP Team, 2020. CovidLP: Short and Long-term Prediction for COVID-19. Departamento de Estatistica. UFMG, Brazil. URL: http://est.ufmg.br/covidlp/home/en/
load_covid, format_data, pandemic_model, posterior_predict.pandemicEstimated,
pandemic_stats and plot.pandemicPredicted.
## formating the data frame for pandemic_model function
#loading data
data <- covid19BH
data
names(data)
#re-order data in ascending order
class(data$date)
data$date = as.Date(data$date)
class(data$date)
data <- data[order(data$date), ]
head(data)
# building the Y list required
start <- data$date[1]
end <- data$date[nrow(data)]
cases <- data$last_available_confirmed
new_cases <- data$new_confirmed
deaths <- data$last_available_deaths
new_deaths <- data$new_deaths
pop <- data$estimated_population_2019[1]
Y <- format_data(s_date = start, e_date = end,
cases = cases, n_cases = new_cases,
deaths = deaths, n_deaths = new_deaths,
name = "Belo Horizonte/MG", pop = pop)
Y
plot(Y)
## fitted model:
##pandemic_model function may take a few minutes...
## Not run:
outputBH = pandemic_model(Y, control = list(max_treedepth = 50, adapt_delta = 0.999))
outputBH
summary(outputBH)
##convergence diagnostics
traceplot(outputBH)
density(outputBH)
stan_ac(outputBH$fit, pars = c("a","b","c","f"))
## making predictions
predictions = posterior_predict(outputBH)
## calculating prediction intervals and statistics
stats = pandemic_stats(predictions)
## plotting results
plot(predictions)
## End(Not run)
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