Package: modelSSE 0.1-3
Shi Zhao
modelSSE: Modelling Infectious Disease Superspreading from Contact Tracing Data
Comprehensive analytical tools are provided to characterize infectious disease superspreading from contact tracing surveillance data. The underlying theoretical frameworks of this toolkit include branching process with transmission heterogeneity (Lloyd-Smith et al. (2005) <doi:10.1038/nature04153>), case cluster size distribution (Nishiura et al. (2012) <doi:10.1016/j.jtbi.2011.10.039>, Blumberg et al. (2014) <doi:10.1371/journal.ppat.1004452>, and Kucharski and Althaus (2015) <doi:10.2807/1560-7917.ES2015.20.25.21167>), and decomposition of reproduction number (Zhao et al. (2022) <doi:10.1371/journal.pcbi.1010281>).
Authors:
modelSSE_0.1-3.tar.gz
modelSSE_0.1-3.zip(r-4.5)modelSSE_0.1-3.zip(r-4.4)modelSSE_0.1-3.zip(r-4.3)
modelSSE_0.1-3.tgz(r-4.4-any)modelSSE_0.1-3.tgz(r-4.3-any)
modelSSE_0.1-3.tar.gz(r-4.5-noble)modelSSE_0.1-3.tar.gz(r-4.4-noble)
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modelSSE.pdf |modelSSE.html✨
modelSSE/json (API)
| # Install 'modelSSE' in R: |
| install.packages('modelSSE', repos = c('https://epiverse-connect.r-universe.dev', 'https://cloud.r-project.org')) |
- COVID19_JanApr2020_HongKong - A dataset of COVID-19 outbreak in Hong Kong
- MERS_2013_MEregion - A dataset of MERS outbreaks in the Middle East region
- mpox_19801984_DRC - A dataset of mpox outbreaks in DRC
- smallpox_19581973_Europe - A dataset of smallpox outbreaks in Europe
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:06c8e3521f. Checks:OK: 3 NOTE: 4. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 10 2024 |
| R-4.5-win | NOTE | Oct 10 2024 |
| R-4.5-linux | NOTE | Oct 10 2024 |
| R-4.4-win | NOTE | Oct 10 2024 |
| R-4.4-mac | NOTE | Oct 10 2024 |
| R-4.3-win | OK | Oct 10 2024 |
| R-4.3-mac | OK | Oct 10 2024 |
Exports:convert.epipara.to.delapparad_nextgenclusterdistnd_offspringdistnd_outbreakdistnd_reproductiondistnmostinfectiousPoveralllikelihoodp_nextgenclusterdistnp_offspringdistnp_outbreakdistnparaest.MCMCparaest.MLq_nextgenclusterdistnq_offspringdistnq_outbreakdistnr_nextgenclusterdistnr_offspringdistnr_outbreakdistntailoffspringQ
Dependencies:Delaporte
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A dataset of COVID-19 outbreak in Hong Kong | COVID19_JanApr2020_HongKong |
| The next-generation cluster size distribution | d_nextgenclusterdistn p_nextgenclusterdistn q_nextgenclusterdistn r_nextgenclusterdistn |
| The offspring distribution | d_offspringdistn p_offspringdistn q_offspringdistn r_offspringdistn |
| The final outbreak size distribution | d_outbreakdistn p_outbreakdistn q_outbreakdistn r_outbreakdistn |
| The distribution of individual reproduction number | d_reproductiondistn |
| A dataset of MERS outbreaks in the Middle East region | MERS_2013_MEregion |
| A dataset of mpox outbreaks in DRC | mpox_19801984_DRC |
| The likelihood function | overalllikelihood |
| To estimate model parameters using Markov chain Monte Carlo approach | paraest.MCMC |
| To estimate model parameters using maximum likelihood approach | paraest.ML |
| A dataset of smallpox outbreaks in Europe | smallpox_19581973_Europe |
| The "20/80" rule | mostinfectiousP tailoffspringQ |