Package: superspreading 0.3.0.9000

Joshua W. Lambert

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:Joshua W. Lambert [aut, cre, cph], Adam Kucharski [aut, cph], Dillon C. Adam [aut], Sebastian Funk [ctb, cph], Pratik Gupte [rev], Hugo Gruson [rev], James M. Azam [rev, ctb], Chris Hartgerink [rev]

superspreading_0.3.0.9000.tar.gz
superspreading_0.3.0.9000.zip(r-4.7-any)superspreading_0.3.0.9000.zip(r-4.6-any)superspreading_0.3.0.9000.zip(r-4.5-any)
superspreading_0.3.0.9000.tgz(r-4.6-any)superspreading_0.3.0.9000.tgz(r-4.5-any)
superspreading_0.3.0.9000.tar.gz(r-4.7-any)superspreading_0.3.0.9000.tar.gz(r-4.6-any)
superspreading_0.3.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
superspreading/json (API)

# Install 'superspreading' in R:
install.packages('superspreading', repos = c('https://epiverse-connect.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/epiverse-trace/superspreading/issues

Pkgdown/docs site:https://epiverse-trace.github.io

On CRAN:

Conda:

disease-transmissionepidemiologyepiverse

6.30 score 5 stars 33 scripts 290 downloads 11 exports 3 dependencies

Last updated from:7f2b20ec20. Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK183
source / vignettesOK201
linux-releaseOK226
macos-releaseOK122
macos-oldrelOK148
windows-develOK123
windows-releaseOK107
windows-oldrelOK122
wasm-releaseOK131

Exports:calc_network_Rdpoislnormdpoisweibullic_tblppoislnormppoisweibullprobability_containprobability_epidemicprobability_extinctproportion_cluster_sizeproportion_transmission

Dependencies:backportscheckmaterlang

Design Principles for {superspreading}
Scope | Output | Design decisions | Dependencies | Contribute
Rendered fromdesign-principles.Rmdusingknitr::rmarkdown

Last update: 2024-10-31
Started: 2023-12-14

Getting started with {superspreading}
Definition | Probability of epidemic | Empirical superspreading | References
Rendered fromsuperspreading.Rmdusingknitr::rmarkdown

Last update: 2024-10-10
Started: 2023-05-18

Methods for calculating the proportion of transmission
Definitions | Exploring each method
Rendered fromproportion_transmission.Rmdusingknitr::rmarkdown

Last update: 2024-10-10
Started: 2024-09-27

Epidemic Risk
plot probability of epidemic across dispersion | plot probability of epidemic across introductions | plot probability of extinction across R for multiple k | Controls on transmission | plot probability of epidemic across introductions for multiple k
Rendered fromepidemic_risk.Rmdusingknitr::rmarkdown

Last update: 2024-10-07
Started: 2023-06-13

Estimate individual-level transmission
Transmission data | Superspreading using alternative distributions | References
Rendered fromestimate_individual_level_transmission.Rmdusingknitr::rmarkdown

Last update: 2024-10-07
Started: 2023-05-26

Outbreaks in heterogeneous networks
Rendered fromheterogeneous_network_outbreaks.Rmdusingknitr::rmarkdown

Last update: 2024-10-07
Started: 2024-01-09