EpiNova: Flexible Extended State-Space Epidemiological Models with Modern Inference

An extended epidemiological modelling framework that goes beyond the classical SIR (Susceptible-Infectious-Recovered) model. Supports SEIR (Susceptible-Exposed-Infectious-Recovered), SEIRD (Susceptible-Exposed-Infectious-Recovered-Deceased), SVEIRD (Susceptible-Vaccinated-Exposed-Infectious-Recovered-Deceased), and age-stratified compartmental models with flexible intervention functions (spline-based, Gaussian process, or user-defined). Inference is available via maximum likelihood or sequential Monte Carlo (SMC, also known as particle filtering) with no external binary dependencies. Includes a dependency-free real-time effective reproduction number (Rt) estimator, spatial multi-patch models with gravity-model mobility, ensemble forecasting via Bayesian model averaging (BMA), and proper scoring rules including CRPS (Continuous Ranked Probability Score), coverage, and MAE (Mean Absolute Error) for forecast evaluation. Methods follow Anderson and May (1991, ISBN:9780198545996), Doucet, de Freitas, and Gordon (2001) <doi:10.1007/978-1-4757-3437-9>, Cori et al. (2013) <doi:10.1093/aje/kwt133>, and Gneiting and Raftery (2007) <doi:10.1198/016214506000001437>.

Version:	0.1.0
Depends:	R (≥ 4.0.0)
Imports:	deSolve, ggplot2, dplyr, tidyr, splines, scales
Suggests:	DEoptim, MASS, numDeriv, rstan, TMB, EpiEstim, knitr, rmarkdown, testthat (≥ 3.0.0), ggpubr, patchwork
Published:	2026-04-22
DOI:	10.32614/CRAN.package.EpiNova
Author:	Subir Hait [aut, cre]
Maintainer:	Subir Hait <haitsubi at msu.edu>
BugReports:	https://github.com/causalfragility-lab/EpiNova/issues
License:	MIT + file LICENSE
URL:	https://github.com/causalfragility-lab/EpiNova
NeedsCompilation:	no
Citation:	EpiNova citation info
Materials:	README, NEWS
CRAN checks:	EpiNova results

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