Package: SimInf
Title: A Framework for Data-Driven Stochastic Disease Spread
Simulations
Version: 9.2.0
Authors@R: c(person("Stefan", "Widgren", role = c("aut", "cre"),
email = "stefan.widgren@gmail.com",
comment = c(ORCID = "0000-0001-5745-2284")),
person("Robin", "Eriksson", role = "aut",
comment = c(ORCID = "0000-0002-4291-712X")),
person("Stefan", "Engblom", role = "aut",
comment = c(ORCID = "0000-0002-3614-1732")),
person("Pavol", "Bauer", role = "aut",
comment = c(ORCID = "0000-0003-4328-7171")),
person("Thomas", "Rosendal", role = "ctb",
comment = c(ORCID = "0000-0002-6576-9668")),
person("Ivana", "Rodriguez Ewerlöf", role = "ctb",
comment = c(ORCID = "0000-0002-9678-9813")),
person("Attractive Chaos", role = "cph",
comment = "Author of 'kvec.h'."))
Description: Provides an efficient and very flexible framework to
conduct data-driven epidemiological modeling in realistic large
scale disease spread simulations. The framework integrates
infection dynamics in subpopulations as continuous-time Markov
chains using the Gillespie stochastic simulation algorithm and
incorporates available data such as births, deaths and movements
as scheduled events at predefined time-points. 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 user-defined models. For more details see the paper by
Widgren, Bauer, Eriksson and Engblom (2019)
<doi:10.18637/jss.v091.i12>. The package also provides
functionality to fit models to time series data using the
Approximate Bayesian Computation Sequential Monte Carlo
('ABC-SMC') algorithm of Toni and others (2009)
<doi:10.1098/rsif.2008.0172>.
Acknowledgements: This software has been made possible by support from
the Swedish Research Council within the UPMARC Linnaeus center
of Excellence (Pavol Bauer, Robin Eriksson, and Stefan
Engblom), the Swedish Research Council Formas (Stefan Engblom
and Stefan Widgren), the Swedish Board of Agriculture (Stefan
Widgren), the Swedish strategic research program eSSENCE
(Stefan Widgren), and in the framework of the Full Force
project, supported by funding from the European Union’s Horizon
2020 Research and Innovation programme under grant agreement No
773830: One Health European Joint Programme (Stefan Widgren).
License: GPL-3
URL: https://github.com/stewid/SimInf
BugReports: https://github.com/stewid/SimInf/issues
Type: Package
LazyData: true
Biarch: true
NeedsCompilation: yes
SystemRequirements: GNU Scientific Library (GSL)
Depends: R(>= 4.0)
Imports: digest, graphics, grDevices, MASS, methods, stats, utils,
Matrix
Suggests: knitr, rmarkdown
Collate: 'C-generator.R' 'check_arguments.R' 'init.R' 'valid.R'
'classes.R' 'SimInf_model.R' 'SEIR.R' 'SIR.R' 'SIS.R' 'SISe.R'
'SISe3.R' 'SISe3_sp.R' 'SISe_sp.R' 'SimInf.R' 'SimInf_events.R'
'run.R' 'density_ratio.R' 'abc.R' 'abc_support.R' 'degree.R'
'distance.R' 'distributions.R' 'match_compartments.R'
'mparse.R' 'n.R' 'openmp.R' 'package_skeleton.R' 'pfilter.R'
'plot.R' 'prevalence.R' 'print.R' 'punchcard.R' 'trajectory.R'
'update.R'
Encoding: UTF-8
RoxygenNote: 7.2.0
VignetteBuilder: utils, knitr
Packaged: 2022-09-03 16:35:15 UTC; stefan
Author: Stefan Widgren [aut, cre] (<https://orcid.org/0000-0001-5745-2284>),
Robin Eriksson [aut] (<https://orcid.org/0000-0002-4291-712X>),
Stefan Engblom [aut] (<https://orcid.org/0000-0002-3614-1732>),
Pavol Bauer [aut] (<https://orcid.org/0000-0003-4328-7171>),
Thomas Rosendal [ctb] (<https://orcid.org/0000-0002-6576-9668>),
Ivana Rodriguez Ewerlöf [ctb] (<https://orcid.org/0000-0002-9678-9813>),
Attractive Chaos [cph] (Author of 'kvec.h'.)
Maintainer: Stefan Widgren <stefan.widgren@gmail.com>
Repository: CRAN
Date/Publication: 2022-09-03 17:40:01 UTC