{ "_id": "6a102b19acfb0bcc41c9239e", "Package": "MGDrivE2", "Type": "Package", "Title": "Mosquito Gene Drive Explorer 2", "Version": "2.1.1", "Authors@R": "c(\nperson(\"Sean L.\", \"Wu\", email = \"slwood89@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Jared B.\", \"Bennett\", email = \"jared_bennett@berkeley.edu \", role = \"aut\"),\nperson(\"Héctor Manuel\", \"Sánchez Castellanos\", email = \"sanchez.hmsc@berkeley.edu\", role = \"ctb\"),\nperson(\"Tomás M.\", \"León\", email = \"tomas.leon@berkeley.edu\", role = \"ctb\"),\nperson(\"Andrew J.\", \"Dolgert\", email = \"adolgert@uw.edu\", role = \"ctb\"),\nperson(\"John M.\", \"Marshall\", email = \"john.marshall@berkeley.edu\", role = \"aut\"),\nperson(\"Agastya\", \"Mondal\", email= \"amondal13@gmail.com\", role = \"aut\")\n)", "Maintainer": "Sean L. Wu ", "URL": "https://marshalllab.github.io/MGDrivE/docs_v2/index.html,\nhttps://www.marshalllab.com/", "BugReports": "https://github.com/MarshallLab/MGDrivE/issues", "Description": "A simulation modeling framework which significantly\nextends capabilities from the 'MGDrivE' simulation package via\na new mathematical and computational framework based on\nstochastic Petri nets. For more information about 'MGDrivE',\nsee our publication: Sánchez et al. (2019)\n Some of the notable capabilities\nof 'MGDrivE2' include: incorporation of human populations,\nepidemiological dynamics, time-varying parameters, and a\ncontinuous-time simulation framework with various sampling\nalgorithms for both deterministic and stochastic\ninterpretations. 'MGDrivE2' relies on the genetic inheritance\nstructures provided in package 'MGDrivE', so we suggest\ninstalling that package initially.", "License": "GPL-3", "Encoding": "UTF-8", "ByteCompile": "true", "LazyData": "true", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.2", "Roxygen": "list(markdown = TRUE)", "Repository": "https://marshalllab.r-universe.dev", "Date/Publication": "2025-09-14 02:14:25 UTC", "RemoteUrl": "https://github.com/marshalllab/mgdrive", "RemoteRef": "HEAD", "RemoteSha": "f7ec820e8a6b0f4fa5697b190f6cb0b1d2d02311", "RemoteSubdir": "MGDrivE2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-13 06:42:54 UTC", "User": "root" }, "Author": "Sean L. Wu [aut, cre],\nJared B. Bennett [aut],\nHéctor Manuel Sánchez Castellanos [ctb],\nTomás M. León [ctb],\nAndrew J. Dolgert [ctb],\nJohn M. Marshall [aut],\nAgastya Mondal [aut]", "MD5sum": "c2de8f78acb80353e652aba8e53e2b29", "_user": "marshalllab", "_type": "src", "_file": "MGDrivE2_2.1.1.tar.gz", "_fileid": "50cdb7016841ccfeabb34036ffaadf187e689d4a48154b746580aa6963a947f4", "_filesize": 3642645, "_sha256": "50cdb7016841ccfeabb34036ffaadf187e689d4a48154b746580aa6963a947f4", "_created": "2026-05-13T06:42:54.000Z", "_published": "2026-05-22T10:08:25.455Z", "_distro": "noble", "_jobs": [ { "job": 77358730525, "time": 152, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6963351907" }, { "job": 77358730506, "time": 128, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "6963344279" }, { "job": 77358730730, "time": 113, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "6963492302" }, { "job": 77358730371, "time": 106, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "6963561414" }, { "job": 77358729498, "time": 278, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "6963312048" }, { "job": 77358729765, "time": 138, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7157989069" }, { "job": 77358730584, "time": 110, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "6963339640" }, { "job": 77358730312, "time": 105, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "6963338650" }, { "job": 77358730532, "time": 89, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "6963334757" } ], "_buildurl": "https://github.com/r-universe/marshalllab/actions/runs/25782826825", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/marshalllab/mgdrive", "_commit": { "id": "f7ec820e8a6b0f4fa5697b190f6cb0b1d2d02311", "author": "slwu89 <10673535+slwu89@users.noreply.github.com>", "committer": "slwu89 <10673535+slwu89@users.noreply.github.com>", "message": "minor fix to 2.1.1\n", "time": 1757816065 }, "_maintainer": { "name": "Sean L. Wu", "email": "slwood89@gmail.com", "login": "slwu89", "uuid": 10673535 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.1.0", "role": "Depends" }, { "package": "Matrix", "role": "Imports" }, { "package": "deSolve", "role": "Imports" }, { "package": "statmod", "role": "Imports" }, { "package": "MGDrivE", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "markdown", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" } ], "_owner": "marshalllab", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-35", "n": 1 }, { "week": "2025-36", "n": 1 }, { "week": "2025-37", "n": 2 } ], "_tags": [], "_stars": 8, "_contributors": [ { "user": "gilchrist19", "count": 49, "uuid": 23705161 }, { "user": "chipdelmal", "count": 43, "uuid": 684756 }, { "user": "slwu89", "count": 18, "uuid": 10673535 }, { "user": "marshalllab", "count": 1, "uuid": 16087894 } ], "_userbio": { "uuid": 16087894, "type": "user", "name": "Marshall Lab", "description": "Our research is focused on: 1) genetics-based strategies to control mosquito-borne diseases, and 2) mathematical models to support vector-borne disease control." }, "_downloads": { "count": 531, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/MGDrivE2" }, "_mentions": 1, "_devurl": "https://github.com/marshalllab/mgdrive", "_searchresults": 30, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/MGDrivE2.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/marshalllab/mgdrive", "_realowner": "marshalllab", "_cranurl": true, "_releases": [ { "version": "1.0.1", "date": "2020-10-24" }, { "version": "1.1.0", "date": "2021-01-13" }, { "version": "2.0.0", "date": "2022-08-20" }, { "version": "2.1.0", "date": "2023-03-04" }, { "version": "2.1.1", "date": "2025-09-14" } ], "_exports": [ "add_interventions", "batch_migration", "calc_move_rate", "convert_prevalence_to_eir", "equilibrium_Imperial_decoupled", "equilibrium_lifeycle", "equilibrium_SEI_decoupled_human", "equilibrium_SEI_decoupled_mosy", "equilibrium_SEI_Imperial", "equilibrium_SEI_SEIR", "equilibrium_SEI_SIS", "get_shape", "human_Imperial_ODE", "imperial_model_param_list_create", "make_Q_Imperial", "make_Q_SEI", "movement_prob2rate", "sim_trajectory_CSV", "sim_trajectory_CSV_decoupled", "sim_trajectory_R", "sim_trajectory_R_decoupled", "solve_muAqua", "split_aggregate_CSV", "split_aggregate_CSV_decoupled", "spn_hazards", "spn_hazards_decoupled", "spn_P_epi_decoupled_node", "spn_P_epiSEIR_network", "spn_P_epiSEIR_node", "spn_P_epiSIS_network", "spn_P_epiSIS_node", "spn_P_lifecycle_network", "spn_P_lifecycle_node", "spn_S", "spn_T_epi_decoupled_node", "spn_T_epiSEIR_network", "spn_T_epiSEIR_node", "spn_T_epiSIS_network", "spn_T_epiSIS_node", "spn_T_lifecycle_network", "spn_T_lifecycle_node", "step_CLE", "step_DM", "step_ODE", "step_ODE_decoupled", "step_PTS", "step_PTS_decoupled", "summarize_eggs_geno", "summarize_eggs_stage", "summarize_females", "summarize_females_epi", "summarize_humans_epiImperial", "summarize_humans_epiSEIR", "summarize_humans_epiSIS", "summarize_larvae_geno", "summarize_larvae_stage", "summarize_males", "summarize_pupae_geno", "summarize_pupae_stage", "summarize_stats_CSV", "summarize_stats_CSV_decoupled", "track_hinf" ], "_datasets": [ { "name": "mu_ts", "title": "Mosquito Death Rates, Comoros Islands", "object": "mu_ts", "class": [ "matrix", "array" ], "fields": [ "Grande_Comore", "Moheli", "Anjouan" ], "rows": 8760, "table": true, "tojson": true } ], "_help": [ { "page": "add_interventions", "title": "This set of functions modifies mosquito life history parameters in the presence of adult interventions - indoor residual spraying (IRS) and insecticide treated nets (ITN) This is based on the work of Le Menach et al (2007) and Griffin et al (2010). We vary three parameters in the presence of interventions: Egg laying rate (beta) Adult mortality (muF) Mosquito biting rate (av0)", "topics": [ "add_interventions" ] }, { "page": "batch_migration", "title": "Sample Batch Migration Events", "topics": [ "batch_migration" ] }, { "page": "calc_move_rate", "title": "Calculate Outbound Movement Rate", "topics": [ "calc_move_rate" ] }, { "page": "convert_prevalence_to_eir", "title": "Generally, pathogen prevalence is a more accesible metric for users, but the Imperial equilibrium function requires an annual EIR. This function converts a given pathogen prevalence to an EIR", "topics": [ "convert_prevalence_to_eir" ] }, { "page": "equilibrium_Imperial_decoupled", "title": "This function calculates the human and mosquito equilibrium values for the decoupled Imperial model. Currently this only works in one node.", "topics": [ "equilibrium_Imperial_decoupled" ] }, { "page": "equilibrium_Imperial_decoupled_human", "title": "This function calculates the human equilibrium values for the decoupled Imperial model. Requires the age structure of the population Currently this only works in one node.", "topics": [ "equilibrium_Imperial_decoupled_human" ] }, { "page": "equilibrium_lifeycle", "title": "Calculate Equilibrium for Lifecycle Model (Logistic or Lotka-Volterra)", "topics": [ "equilibrium_lifeycle" ] }, { "page": "equilibrium_SEI_decoupled_human", "title": "This function calculates the equilibrium values for the decoupled SIS human states. Currently this only works in one node.", "topics": [ "equilibrium_SEI_decoupled_human" ] }, { "page": "equilibrium_SEI_decoupled_mosy", "title": "Calculate Equilibrium for Decoupled Mosquito SEI model. Human states will be handled separately.", "topics": [ "equilibrium_SEI_decoupled_mosy" ] }, { "page": "equilibrium_SEI_Imperial", "title": "Calculate Equilibrium for Mosquito SEI - Human Imperial Model", "topics": [ "equilibrium_SEI_Imperial" ] }, { "page": "equilibrium_SEI_SEIR", "title": "Calculate Equilibrium for Mosquito SEI - Human SEIR Model", "topics": [ "equilibrium_SEI_SEIR" ] }, { "page": "equilibrium_SEI_SIS", "title": "Calculate Equilibrium for Mosquito SEI - Human SIS Model", "topics": [ "equilibrium_SEI_SIS" ] }, { "page": "get_shape", "title": "Calculate Erlang shape parameter", "topics": [ "get_shape" ] }, { "page": "human_Imperial_ODE", "title": "ODE describing the age-structured Imperial model used in decoupled sampling, which will pass in values of I_V and return the human states for usein the mosquito portion of the model", "topics": [ "human_Imperial_ODE" ] }, { "page": "imperial_model_param_list_create", "title": "Model Parameter List Creation", "topics": [ "imperial_model_param_list_create" ] }, { "page": "make_Q_Imperial", "title": "Rate Matrix (Q) for Adult Mosquito SEI Dynamics", "topics": [ "make_Q_Imperial" ] }, { "page": "make_Q_SEI", "title": "Rate Matrix (Q) for Adult Mosquito SEI Dynamics", "topics": [ "make_Q_SEI" ] }, { "page": "movement_prob2rate", "title": "Convert Stochastic Matrix to Rate Matrix", "topics": [ "movement_prob2rate" ] }, { "page": "mu_ts", "title": "Mosquito Death Rates, Comoros Islands", "topics": [ "mu_ts" ] }, { "page": "sim_trajectory_base_CSV", "title": "Simulate Trajectory From one SPN Model", "topics": [ "sim_trajectory_base_CSV" ] }, { "page": "sim_trajectory_base_CSV_decoupled", "title": "Simulate Trajectory From one SPN Model", "topics": [ "sim_trajectory_base_CSV_decoupled" ] }, { "page": "sim_trajectory_base_R", "title": "Simulate Trajectory From one SPN Model", "topics": [ "sim_trajectory_base_R" ] }, { "page": "sim_trajectory_base_R_decoupled_Imperial", "title": "Simulate Trajectory From one SPN Model using Imperial Malaria model", "topics": [ "sim_trajectory_base_R_decoupled_Imperial" ] }, { "page": "sim_trajectory_base_R_decoupled_SIS", "title": "Simulate Trajectory From one SPN Model using Human SIS model", "topics": [ "sim_trajectory_base_R_decoupled_SIS" ] }, { "page": "sim_trajectory_CSV", "title": "Simulate Trajectory From a SPN Model", "topics": [ "sim_trajectory_CSV" ] }, { "page": "sim_trajectory_CSV_decoupled", "title": "Simulate Trajectory From a SPN Model", "topics": [ "sim_trajectory_CSV_decoupled" ] }, { "page": "sim_trajectory_R", "title": "Simulate Trajectory From a SPN Model", "topics": [ "sim_trajectory_R" ] }, { "page": "sim_trajectory_R_decoupled", "title": "Simulate Trajectory From a SPN Model", "topics": [ "sim_trajectory_R_decoupled" ] }, { "page": "solve_muAqua", "title": "Solve for Constant Aquatic Mortality", "topics": [ "solve_muAqua" ] }, { "page": "split_aggregate_CSV", "title": "Split CSV output by Patch and Aggregate by Mate or Dwell-Stage", "topics": [ "split_aggregate_CSV" ] }, { "page": "split_aggregate_CSV_decoupled", "title": "Split CSV output for decoupled sampling with Imperial malaria model", "topics": [ "split_aggregate_CSV_decoupled" ] }, { "page": "spn_hazards", "title": "Make Hazards (Lambda) For a MGDrivE2: Node and Network Simulations", "topics": [ "spn_hazards" ] }, { "page": "spn_hazards_decoupled", "title": "Make Hazards (Lambda) For a MGDrivE2: Node and Network Simulations", "topics": [ "spn_hazards_decoupled" ] }, { "page": "spn_P_epi_decoupled_node", "title": "Make Places (P) For a Node (SEI Mosquitoes). Note in the v2 epi module, we only use the SPN framework for the mosquito component of the model. The human compoenent will be handled separately in the sampler, and will be formulated as an ODE. This function makes the set of places (P) for a SPN. It is used alone if our model is a single-node metapopulation for mosquito SEI and dynamics; This is used by both SIS and Imperial transmission models.", "topics": [ "spn_P_epi_decoupled_node" ] }, { "page": "spn_P_epiSEIR_network", "title": "Make Places (P) For a Network (SEI Mosquitoes - SEIR Humans)", "topics": [ "spn_P_epiSEIR_network" ] }, { "page": "spn_P_epiSEIR_node", "title": "Make Places (P) For a Node (SEI Mosquitoes - SEIR Humans)", "topics": [ "spn_P_epiSEIR_node" ] }, { "page": "spn_P_epiSIS_network", "title": "Make Places (P) For a Network (SEI Mosquitoes - SIS Humans)", "topics": [ "spn_P_epiSIS_network" ] }, { "page": "spn_P_epiSIS_node", "title": "Make Places (P) For a Node (SEI Mosquitoes - SIS Humans)", "topics": [ "spn_P_epiSIS_node" ] }, { "page": "spn_P_lifecycle_network", "title": "Make Places (P) For a Network (Mosquitoes only)", "topics": [ "spn_P_lifecycle_network" ] }, { "page": "spn_P_lifecycle_node", "title": "Make Places (P) For a Node (Mosquitoes only)", "topics": [ "spn_P_lifecycle_node" ] }, { "page": "spn_Post", "title": "Make Post Matrix For a Petri Net", "topics": [ "spn_Post" ] }, { "page": "spn_Pre", "title": "Make Pre Matrix For a Petri Net", "topics": [ "spn_Pre" ] }, { "page": "spn_S", "title": "Make stoichiometry Matrix For a Petri Net", "topics": [ "spn_S" ] }, { "page": "spn_T_epi_decoupled_node", "title": "Make Transitions (T) For a Node (SEI Mosquitoes)", "topics": [ "spn_T_epi_decoupled_node" ] }, { "page": "spn_T_epiSEIR_network", "title": "Make Transitions (T) For a Network (SEI Mosquitoes - SEIR Humans)", "topics": [ "spn_T_epiSEIR_network" ] }, { "page": "spn_T_epiSEIR_node", "title": "Make Transitions (T) For a Node (SEI Mosquitoes - SEIR Humans)", "topics": [ "spn_T_epiSEIR_node" ] }, { "page": "spn_T_epiSIS_network", "title": "Make Transitions (T) For a Network (SEI Mosquitoes - SIS Humans)", "topics": [ "spn_T_epiSIS_network" ] }, { "page": "spn_T_epiSIS_node", "title": "Make Transitions (T) For a Node (SEI Mosquitoes - SIS Humans)", "topics": [ "spn_T_epiSIS_node" ] }, { "page": "spn_T_lifecycle_network", "title": "Make Transitions (T) For a Network (Mosquitoes only)", "topics": [ "spn_T_lifecycle_network" ] }, { "page": "spn_T_lifecycle_node", "title": "Make Transitions (T) For a Node (Mosquitoes only)", "topics": [ "spn_T_lifecycle_node" ] }, { "page": "step_CLE", "title": "Make Chemical Langevin (CLE) Sampler for a SPN model", "topics": [ "step_CLE" ] }, { "page": "step_DM", "title": "Make Gillespie's Direct Method (DM) Sampler for a SPN model", "topics": [ "step_DM" ] }, { "page": "step_ODE", "title": "Make Mean-field Approximation (ODE) Numerical Integrator for a SPN Model", "topics": [ "step_ODE" ] }, { "page": "step_ODE_decoupled", "title": "Make Mean-field Approximation (ODE) Numerical Integrator for a SPN Model for Decoupled Epi Dynamics", "topics": [ "step_ODE_decoupled" ] }, { "page": "step_PTS", "title": "Make Poisson Time-Step (PTS) Sampler for a SPN Model", "topics": [ "step_PTS" ] }, { "page": "step_PTS_decoupled", "title": "Make Poisson Time-Step (PTS) Sampler for a SPN Model", "topics": [ "step_PTS_decoupled" ] }, { "page": "summarize_eggs_geno", "title": "Summarize Eggs by Genotype", "topics": [ "summarize_eggs_geno" ] }, { "page": "summarize_eggs_stage", "title": "Summarize Eggs by Erlang-Stage", "topics": [ "summarize_eggs_stage" ] }, { "page": "summarize_females", "title": "Summarize Adult Females (One Node or Metapopulation Network, Lifecycle Model)", "topics": [ "summarize_females" ] }, { "page": "summarize_females_epi", "title": "Summarize Adult Females (One Node or Metapopulation Network, SEI Mosquitoes)", "topics": [ "summarize_females_epi" ] }, { "page": "summarize_humans_epiImperial", "title": "Summarize Humans for Imperial Model", "topics": [ "summarize_humans_epiImperial" ] }, { "page": "summarize_humans_epiSEIR", "title": "Summarize Humans (One Node or Metapopulation Network, SEI Mosquitoes - SEIR Humans)", "topics": [ "summarize_humans_epiSEIR" ] }, { "page": "summarize_humans_epiSIS", "title": "Summarize Humans (One Node or Metapopulation Network, SEI Mosquitoes - SIS Humans)", "topics": [ "summarize_humans_epiSIS" ] }, { "page": "summarize_larvae_geno", "title": "Summarize Larvae by Genotype", "topics": [ "summarize_larvae_geno" ] }, { "page": "summarize_larvae_stage", "title": "Summarize Larval by Erlang-Stage", "topics": [ "summarize_larvae_stage" ] }, { "page": "summarize_males", "title": "Summarize Adult Males (One Node or Metapopulation Network)", "topics": [ "summarize_males" ] }, { "page": "summarize_pupae_geno", "title": "Summarize Pupal by Genotype", "topics": [ "summarize_pupae_geno" ] }, { "page": "summarize_pupae_stage", "title": "Summarize Pupal by Erlang-Stage", "topics": [ "summarize_pupae_stage" ] }, { "page": "summarize_stats_CSV", "title": "Summary Statistics for MGDrivE2", "topics": [ "summarize_stats_CSV" ] }, { "page": "summarize_stats_CSV_decoupled", "title": "Summary Statistics for MGDrivE2 - Decoupled samples", "topics": [ "summarize_stats_CSV_decoupled" ] }, { "page": "track_hinf", "title": "Make tracking matrix for human infection events", "topics": [ "track_hinf" ] } ], "_readme": "https://github.com/marshalllab/mgdrive/raw/HEAD/MGDrivE2/README.md", "_rundeps": [ "deSolve", "lattice", "Matrix", "statmod" ], "_vignettes": [ { "source": "advanced_topics.Rmd", "filename": "advanced_topics.html", "title": "MGDrivE2: Advanced Topics", "engine": "knitr::rmarkdown", "headings": [ "Table of Contents", "Preface", "Custom Numerical Routines", "Step Function", "Test Simulation", "Parameterization", "Initialization of the Petri Net", "Equilibrium Conditions and Hazard Functions", "Simulation of Fully Specified SPN Model", "Euler Method Solutions", "Default ODE Solutions", "Analysis", "Tips and Tricks" ], "created": "2020-10-06 14:41:51", "modified": "2025-09-14 01:43:43", "commits": 3 }, { "source": "epi-network.Rmd", "filename": "epi-network.html", 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