nowcaster: Statistical Models for Notification Delay Correction of Epidemiological Data.
The package wraps statistical models to estimate not yet reported data using empirical delay distribution either from individual-level data or from the differences of aggregated time series of cases. nowcaster it was built for and during 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.
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).
Installing
You can install direct from CRAN:
install.packages("nowcaster")Or you can install the developing version directly from GitHub:
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.
Dependencies
nowcaster is based on the R-INLA and mgcv. Please make sure you have stable version of those packages to be able to fully work with nowcaster
Installing INLA:
install.packages("INLA", repos=c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/stable"), dep=TRUE)Installing mgcv:
install.packages("mgcv")