% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/shiny.R
\name{epiweb}
\alias{epiweb}
\title{EpiModel Web}
\usage{
epiweb(class, ...)
}
\arguments{
\item{class}{Model class, with options of \code{"dcm"} and \code{"icm"}.}

\item{...}{Additional arguments passed to \link[shiny:runApp]{shiny::runApp}, such as
\code{port}, \code{host}, or \code{launch.browser}.}
}
\description{
Launches interactive Shiny applications for exploring
deterministic compartmental models (DCMs) and stochastic
individual contact models (ICMs) of infectious disease
transmission.
}
\details{
\code{epiweb} launches a web-based graphical interface for configuring, running,
and analyzing epidemic models built on EpiModel. Each application provides
interactive controls for model parameters, real-time (or on-demand)
visualization with plotly, narrative model summaries, and downloadable
data tables. Both applications include a \strong{Guide} tab with a comprehensive
user manual covering the underlying theory, parameter definitions, and
instructions for interpreting output.
}
\section{DCM Application (\code{class = "dcm"})}{

The DCM app solves systems of ordinary differential equations for one-group
SI, SIR, and SIS models. Models run instantly and the interface is fully
reactive (no run button). Features include:
\itemize{
\item \strong{Scenario presets:} Flu-like (SIR), STI-like (SIS), and
Measles-like (SIR) configurations that set all parameters to
epidemiologically plausible values.
\item \strong{Interventions:} An optional mid-epidemic intervention that
reduces the transmission probability by a user-specified efficacy,
shown as a vertical dashed line on the plot.
\item \strong{Sensitivity analysis:} Vary any epidemic parameter across a
range of values to compare trajectories side by side with a
blue-to-red color ramp.
\item \strong{Vital dynamics:} Optional births and deaths to model endemic
equilibria over longer time horizons.
\item \strong{Summary tab:} Displays the basic reproduction number
(R\ifelse{html}{\out{<sub>0</sub>}}{0}), peak timing, cumulative
infections, attack rate, and contextual interpretation.
\item \strong{Data tab:} Searchable table of model output with CSV download.
}
}

\section{ICM Application (\code{class = "icm"})}{

The ICM app runs agent-based stochastic microsimulations for one-group
SI, SIR, and SIS models. Because ICMs are computationally more expensive,
a \strong{Run Model} button controls when simulations execute. Features include:
\itemize{
\item \strong{Stochastic visualization:} Multiple simulations are summarized
with mean trajectory lines and interquartile range (IQR) ribbons
showing the middle 50\\% of outcomes. Single simulations display
individual trajectories.
\item \strong{Scenario presets:} The same Flu-like, STI-like, and Measles-like
configurations as the DCM app, adapted for smaller populations suitable
for agent-based simulation.
\item \strong{Interventions:} Same intervention system as DCM, natively
supported by \link{param.icm}.
\item \strong{Vital dynamics:} Optional births and deaths, as in DCM.
\item \strong{Summary tab:} Displays R\ifelse{html}{\out{<sub>0</sub>}}{0},
epidemic timeline from the mean trajectory, and a stochastic variation
section showing the range and standard deviation of peak infections and
final prevalence across simulations.
\item \strong{Data tab:} View simulation output as means, standard deviations,
or individual simulation values, with CSV download.
}
}

\section{Required Packages}{

Both applications require the \code{shiny}, \code{bslib}, \code{DT}, and \code{plotly} packages.
Install any missing packages with
\code{install.packages(c("shiny", "bslib", "DT", "plotly"))}.
}

\examples{
\dontrun{
## Deterministic compartmental models
epiweb(class = "dcm")

## Stochastic individual contact models
epiweb(class = "icm")
}

}
\seealso{
\link{dcm} and \link{param.dcm} for the DCM modeling API;
\link{icm} and \link{param.icm} for the ICM modeling API.
}
