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).
- GitHub
- https://epiverse-trace.github.io/superspreading/
- File a bug report
- superspreading results
- superspreading.pdf
- Version0.3.0
- R versionunknown
- LicenseMIT
- Needs compilation?No
- Languageen-GB
- Last release01/27/2025
Documentation
Team
Joshua W. Lambert
MaintainerShow author detailsDillon C. Adam
Chris Hartgerink
Pratik Gupte
Hugo Gruson
Sebastian Funk
Adam Kucharski
James M. Azam
Insights
Last 30 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Suggests10 packages