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.
Package details 


Maintainer  
License  GPL3 
Version  6.1.0.9000 
URL  https://github.com/stewid/SimInf 
Package repository  View on GitHub 
Installation 
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