Package: superspreading 0.3.0
superspreading: Understand Individual-Level Variation in Infectious Disease Transmission
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>).
Authors:
superspreading_0.3.0.tar.gz
superspreading_0.3.0.tar.gz(r-4.5-noble)superspreading_0.3.0.tar.gz(r-4.4-noble)
superspreading_0.3.0.tgz(r-4.4-emscripten)superspreading_0.3.0.tgz(r-4.3-emscripten)
superspreading.pdf |superspreading.html✨
superspreading/json (API)
NEWS
# Install 'superspreading' in R: |
install.packages('superspreading', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/epiverse-trace/superspreading/issues
Pkgdown site:https://epiverse-trace.github.io
Last updated 26 days agofrom:6bde742025. Checks:2 OK. Indexed: no.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Jan 27 2025 |
R-4.5-linux | OK | Jan 27 2025 |
Exports:calc_network_Rdpoislnormdpoisweibullic_tblppoislnormppoisweibullprobability_containprobability_epidemicprobability_extinctproportion_cluster_sizeproportion_transmission
Design Principles for {superspreading}
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Epidemic Risk
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Estimate individual-level transmission
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Getting started with {superspreading}
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Methods for calculating the proportion of transmission
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Outbreaks in heterogeneous networks
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on Jan 27 2025.Last update: 2025-01-27
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