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modelSSE (version 0.1-3)

Modelling Infectious Disease Superspreading from Contact Tracing Data

Description

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) ), case cluster size distribution (Nishiura et al. (2012) , Blumberg et al. (2014) , and Kucharski and Althaus (2015) ), and decomposition of reproduction number (Zhao et al. (2022) ).

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Version

Install

install.packages('modelSSE')

Monthly Downloads

215

Version

0.1-3

License

GPL-3

Maintainer

Shi Zhao

Last Published

September 7th, 2023

Functions in modelSSE (0.1-3)

COVID19_JanApr2020_HongKong

A dataset of COVID-19 outbreak in Hong Kong
d_reproductiondistn

The distribution of individual reproduction number
d_offspringdistn

The offspring distribution
MERS_2013_MEregion

A dataset of MERS outbreaks in the Middle East region
d_nextgenclusterdistn

The next-generation cluster size distribution
convert.epipara.to.delappara

To convert model parameters
mpox_19801984_DRC

A dataset of mpox outbreaks in DRC
paraest.ML

To estimate model parameters using maximum likelihood approach
tailoffspringQ

The "20/80" rule
overalllikelihood

The likelihood function
smallpox_19581973_Europe

A dataset of smallpox outbreaks in Europe
d_outbreakdistn

The final outbreak size distribution
paraest.MCMC

To estimate model parameters using Markov chain Monte Carlo approach