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superspreading: Understand Individual-Level Variation in Infectious DiseaseTransmission

Estimate and understand individual-level variation in transmission. Implements density and cumulative compound Poisson discrete distribution functions (Kremer et al. (2021) <doi:10.1038/s41598-021-93578-x>), as well as functions to calculate infectious disease outbreak statistics given epidemiological parameters on individual-level transmission; including the probability of an outbreak becoming an epidemic/extinct (Kucharski et al. (2020) <doi:10.1016/S1473-3099(20)30144-4>), or the cluster size statistics, e.g. what proportion of cases cause X\% of transmission (Lloyd-Smith et al. (2005) <doi:10.1038/nature04153>).

Version:	0.4.0
Imports:	checkmate,rlang, stats
Suggests:	dplyr,epiparameter (≥ 0.4.0),fitdistrplus,ggplot2,ggtext,knitr,purrr,rmarkdown,scales,spelling,testthat (≥3.0.0)
Published:	2025-07-15
DOI:	10.32614/CRAN.package.superspreading
Author:	Joshua W. Lambert [aut, cre, cph], Adam Kucharski [aut, cph], Dillon C. Adam [aut], Sebastian Funk [ctb, cph] (.chain_sim uses code from bpmodels::chain_sim), Pratik Gupte [rev], Hugo Gruson [rev], James M. Azam [rev, ctb], Chris Hartgerink [rev]
Maintainer:	Joshua W. Lambert <joshua.lambert at lshtm.ac.uk>
BugReports:	https://github.com/epiverse-trace/superspreading/issues
License:	MIT + fileLICENSE
URL:	https://github.com/epiverse-trace/superspreading,https://epiverse-trace.github.io/superspreading/
NeedsCompilation:	no
Language:	en-GB
Materials:	README,NEWS
In views:	Epidemiology
CRAN checks:	superspreading results

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