nowcaster
is an R package for “nowcasting” epidemiological time-series
on individual level data.
Every single system of notification has an intrinsic delay between the
date of onset
of the event and the date of report
. nowcaster
can
estimate how many counts of any epidemiological data of interest
(i.e., daily cases and deaths counts) by fitting a negative binomial
model to the time steps of delay between onset date of the event,
(i.e., date of first symptoms for cases or date of occurrence of
death) and the date of report (i.e., date of notification of the case
or death).
After have a proper INLA
installation to install nowcaster
package
simply run the code below in R:
devtools::install_github("https://github.com/covid19br/nowcaster")
If you have any problem installing, please refer to next section on the dependencies of the package.
nowcaster
is based on the
R-INLA
and
INLA
packages for “Integrated Nested Laplace Approximation”
algorithm to Bayesian inference. INLA
is a fast alternative to others
methods for Bayesian inference like MCMC. An introduction to INLA
can be found
here.
nowcaster
it was built for epidemiological emergency use, it was
constructed for the Brazilian Severe Acute Respiratory Illness (SARI)
surveillance system (SIVEP-Gripe), at the time of Covid-19 pandemic.
Before installing the package certify you have an active installation of
INLA
, to do so you can run the following code:
install.packages("INLA",
repos=c(getOption("repos"),
INLA="https://inla.r-inla-download.org/R/stable"),
dep=TRUE)
If you want more detail on other possible installations of INLA
,
please refer to the official
page of the package.
There are other alternative packages, that can produce nowcasting estimation, here it is some options: