Tools for making epidemiological reporting easier with consistent 
    static and dynamic charts and maps. Builds on 'ggplot2' for static 
    visualizations as described in Wickham (2016) <doi:10.1007/978-3-319-24277-4> 
    and 'plotly' for interactive visualizations as described in 
    Sievert (2020) <doi:10.1201/9780429447273>.

A flexible framework for Agent-Based Models (ABM), the 'epiworldR' package provides methods for prototyping disease outbreaks and transmission models using a 'C++' backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents' features, providing great complexity for the model dynamics. Furthermore, 'epiworldR' is ideal for simulation studies featuring large populations.

Provides tools and pre-trained Machine Learning [ML] models for
  calibration of Agent-Based Models [ABMs] built with the R package
  'epiworldR'. Implements methods described in Najafzadehkhoei, Vega Yon,
  Modenesi, and Meyer (2025) <doi:10.48550/arXiv.2509.07013>. Users can
  automatically calibrate ABMs in seconds with pre-trained ML models,
  effectively focusing on simulation rather than calibration. Bridges a gap
  by allowing public health practitioners to run their own ABMs without the
  advanced technical expertise often required by calibration.

R 'shiny' web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR' (Meyer et al., 2023) <DOI:10.21105/joss.05781>. Some of the main features of the package include the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.