{ "_id": "6a3136943efcd9bda436161e", "Package": "SimInf", "Title": "A Framework for Data-Driven Stochastic Disease Spread\nSimulations", "Version": "10.1.0", "Authors@R": "c(person(\"Stefan\", \"Widgren\", role = c(\"aut\", \"cre\"),\nemail = \"stefan.widgren@gmail.com\",\ncomment = c(ORCID = \"0000-0001-5745-2284\")),\nperson(\"Robin\", \"Eriksson\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-4291-712X\")),\nperson(\"Stefan\", \"Engblom\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3614-1732\")),\nperson(\"Pavol\", \"Bauer\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-4328-7171\")),\nperson(\"Thomas\", \"Rosendal\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-6576-9668\")),\nperson(\"Ivana\", \"Rodriguez Ewerlöf\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-9678-9813\")),\nperson(\"Attractive Chaos\", role = \"cph\",\ncomment = \"Author of 'kvec.h'.\"))", "Description": "Provides an efficient and very flexible framework to\nconduct data-driven epidemiological modeling in realistic large\nscale disease spread simulations. The framework integrates\ninfection dynamics in subpopulations as continuous-time Markov\nchains using the Gillespie stochastic simulation algorithm and\nincorporates available data such as births, deaths and\nmovements as scheduled events at predefined time-points. Using\nC code for the numerical solvers and 'OpenMP' (if available) to\ndivide work over multiple processors ensures high performance\nwhen simulating a sample outcome. One of our design goals was\nto make the package extendable and enable usage of the\nnumerical solvers from other R extension packages in order to\nfacilitate complex epidemiological research. The package\ncontains template models and can be extended with user-defined\nmodels. For more details see the paper by Widgren, Bauer,\nEriksson and Engblom (2019) . The\npackage also provides functionality to fit models to time\nseries data using the Approximate Bayesian Computation\nSequential Monte Carlo ('ABC-SMC') algorithm of Toni and others\n(2009) or the Particle Markov\nChain Monte Carlo ('PMCMC') algorithm of 'Andrieu' and others\n(2010) .", "Acknowledgements": "This software has been made possible by support from\nthe Swedish Research Council within the UPMARC Linnaeus center\nof Excellence (Pavol Bauer, Robin Eriksson, and Stefan\nEngblom), the Swedish Research Council Formas (Stefan Engblom\nand Stefan Widgren), the Swedish Board of Agriculture (Stefan\nWidgren), the Swedish strategic research program eSSENCE\n(Stefan Widgren), and in the framework of the Full Force\nproject, supported by funding from the European Union’s Horizon\n2020 Research and Innovation programme under grant agreement No\n773830: One Health European Joint Programme (Stefan Widgren).", "License": "GPL-3", "URL": "https://github.com/stewid/SimInf, http://stewid.github.io/SimInf/", "BugReports": "https://github.com/stewid/SimInf/issues", "Type": "Package", "LazyData": "true", "Biarch": "true", "NeedsCompilation": "yes", "SystemRequirements": "GNU Scientific Library (GSL)", "Collate": "'C-generator.R' 'check_arguments.R' 'init.R' 'valid.R'\n'classes.R' 'SimInf_model.R' 'SEIR.R' 'SIR.R' 'SIS.R' 'SISe.R'\n'SISe3.R' 'SISe3_sp.R' 'SISe_sp.R' 'SimInf-package.R'\n'SimInf.R' 'SimInf_events.R' 'SimInf_individual_events.R'\n'run.R' 'density_ratio.R' 'abc.R' 'degree.R' 'distance.R'\n'distributions.R' 'edge_properties.R' 'lambert.R'\n'match_compartments.R' 'mparse.R' 'pmcmc.R' 'pfilter.R' 'n.R'\n'openmp.R' 'package_skeleton.R' 'plot.R' 'prevalence.R'\n'print.R' 'punchcard.R' 'trajectory.R' 'u0.R' 'v0.R'", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "VignetteBuilder": "utils, knitr", "Packaged": { "Date": "2026-06-16 11:37:40 UTC", "User": "root" }, "Author": "Stefan Widgren [aut, cre] (ORCID:\n), Robin Eriksson [aut]\n(ORCID: ), Stefan\nEngblom [aut] (ORCID: ),\nPavol Bauer [aut] (ORCID:\n), Thomas Rosendal [ctb]\n(ORCID: ), Ivana\nRodriguez Ewerlöf [ctb] (ORCID:\n), Attractive Chaos\n[cph] (Author of 'kvec.h'.)", "Maintainer": "Stefan Widgren ", "Config/pak/sysreqs": "libgsl0-dev", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2025-11-17 21:51:33 UTC", "RemoteUrl": "https://github.com/cran/SimInf", "RemoteRef": "HEAD", "RemoteSha": "2b3fb32c3891b69abbe33930df8c8de8c980bccd", "MD5sum": "7f40b2bb5ad4ff220192b1f84d8720c9", "_user": "cran", "_type": "src", "_file": "SimInf_10.1.0.tar.gz", "_fileid": "71ee7e4392c63ad6b00f694d6defca7bdb91dad38a40da9649a667397246ee2a", "_filesize": 4254106, "_sha256": "71ee7e4392c63ad6b00f694d6defca7bdb91dad38a40da9649a667397246ee2a", "_created": "2026-06-16T11:37:40.000Z", "_published": "2026-06-16T11:42:12.926Z", "_distro": "noble", "_jobs": [ { "job": 81647864929, "time": 187, "config": "linux-devel-arm64", "r": "4.7.0", "check": "NOTE", "artifact": 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"page": "SimInf_events", "title": "Create a 'SimInf_events' object", "topics": [ "SimInf_events" ] }, { "page": "SimInf_events-class", "title": "Class '\"SimInf_events\"'", "topics": [ "SimInf_events-class" ] }, { "page": "SimInf_individual_events-class", "title": "Class '\"SimInf_individual_events\"'", "topics": [ "SimInf_individual_events-class" ] }, { "page": "SimInf_model", "title": "Create a 'SimInf_model'", "topics": [ "SimInf_model" ] }, { "page": "SimInf_model-class", "title": "Class '\"SimInf_model\"'", "topics": [ "SimInf_model-class" ] }, { "page": "SimInf_pfilter-class", "title": "Class '\"SimInf_pfilter\"'", "topics": [ "SimInf_pfilter-class" ] }, { "page": "SimInf_pmcmc-class", "title": "Class '\"SimInf_pmcmc\"'", "topics": [ "SimInf_pmcmc-class" ] }, { "page": "SIR", "title": "Create an SIR model", "topics": [ "SIR" ] }, { "page": "SIR-class", "title": "Definition of the SIR model", "topics": [ "SIR-class" ] }, { "page": "SIS", "title": "Create an SIS model", "topics": [ "SIS" ] }, { "page": "SIS-class", "title": "Definition of the SIS model", "topics": [ "SIS-class" ] }, { "page": "SISe", "title": "Create a SISe model", "topics": [ "SISe" ] }, { "page": "SISe_sp", "title": "Create a 'SISe_sp' model", "topics": [ "SISe_sp" ] }, { "page": "SISe_sp-class", "title": "Definition of the 'SISe_sp' model", "topics": [ "SISe_sp-class" ] }, { "page": "SISe-class", "title": "Definition of the 'SISe' model", "topics": [ "SISe-class" ] }, { "page": "SISe3", "title": "Create a 'SISe3' model", "topics": [ "SISe3" ] }, { "page": "SISe3_sp", "title": "Create an 'SISe3_sp' model", "topics": [ "SISe3_sp" ] }, { "page": "SISe3_sp-class", "title": "Definition of the 'SISe3_sp' model", "topics": [ "SISe3_sp-class" ] }, { "page": "SISe3-class", "title": "Definition of the 'SISe3' model", "topics": [ "SISe3-class" ] }, { "page": "summary-SimInf_abc-method", "title": "Detailed summary of a 'SimInf_abc' object", "topics": [ "summary,SimInf_abc-method" ] }, { "page": "summary-SimInf_events-method", "title": "Detailed summary of a 'SimInf_events' object", "topics": [ "summary,SimInf_events-method" ] }, { "page": "summary-SimInf_individual_events-method", "title": "Detailed summary of a 'SimInf_individual_events' object", "topics": [ "summary,SimInf_individual_events-method" ] }, { "page": "summary-SimInf_model-method", "title": "Detailed summary of a 'SimInf_model' object", "topics": [ "summary,SimInf_model-method" ] }, { "page": "summary-SimInf_pfilter-method", "title": "Detailed summary of a 'SimInf_pfilter' object", "topics": [ "summary,SimInf_pfilter-method" ] }, { "page": "summary-SimInf_pmcmc-method", "title": "Detailed summary of a 'SimInf_pmcmc' object", "topics": [ "summary,SimInf_pmcmc-method" ] }, { "page": "trajectory", "title": "Generic function to extract data from a simulated trajectory", "topics": [ "trajectory" ] }, { "page": "trajectory-SimInf_model-method", "title": "Extract data from a simulated trajectory", "topics": [ "trajectory,SimInf_model-method" ] }, { "page": "trajectory-SimInf_pfilter-method", "title": "Extract filtered trajectory from running a particle filter", "topics": [ "trajectory,SimInf_pfilter-method" ] }, { "page": "trajectory-SimInf_pmcmc-method", "title": "Extract filtered trajectories from fitting a PMCMC algorithm", "topics": [ "trajectory,SimInf_pmcmc-method" ] }, { "page": "u0", "title": "Get the initial compartment state", "topics": [ "u0", "u0,SimInf_individual_events-method", "u0,SimInf_model-method" ] }, { "page": "u0_SEIR", "title": "Example data to initialize the 'SEIR' model", "topics": [ "u0_SEIR" ] }, { "page": "u0_SIR", "title": "Example data to initialize the 'SIR' model", "topics": [ "u0_SIR" ] }, { "page": "u0_SIS", "title": "Example data to initialize the 'SIS' model", "topics": [ "u0_SIS" ] }, { "page": "u0_SISe", "title": "Example data to initialize the 'SISe' model", "topics": [ "u0_SISe" ] }, { "page": "u0_SISe3", "title": "Example data to initialize the 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