Provides an efficient and very flexible framework to conduct datadriven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuoustime Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined timepoints. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with userdefined models. For more details see the paper by Widgren, Bauer, Eriksson and Engblom (2019) <doi:10.18637/jss.v091.i12>.
Package details 


Author  Stefan Widgren [aut, cre] (<https://orcid.org/0000000157452284>), Robin Eriksson [aut] (<https://orcid.org/000000024291712X>), Stefan Engblom [aut] (<https://orcid.org/0000000236141732>), Pavol Bauer [aut] (<https://orcid.org/0000000343287171>), Attractive Chaos [cph] (Author of 'kvec.h'.) 
Maintainer  Stefan Widgren <stefan.widgren@gmail.com> 
License  GPL3 
Version  6.5.1 
URL  https://github.com/stewid/SimInf 
Package repository  View on CRAN 
Installation 
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