{
  "_id": "6a5f69ec14e95619b75d66c3",
  "Package": "vimcheck",
  "Title": "Diagnostics for Vaccine Impact Modelling Consortium Burden and\nImpact Estimates",
  "Version": "0.0.5",
  "Authors@R": "c(\nperson(\"Pratik\", \"Gupte\", , \"p.gupte24@imperial.ac.uk\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-5294-7819\")),\nperson(\"Katy\", \"Gaythorpe\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-3734-9081\")),\nperson(\"Xiang\", \"Li\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-5945-159X\")),\nperson(\"Zoë\", \"Gibney\", role = \"aut\",\ncomment = c(ORCID = \"0009-0002-8114-9984\")),\nperson(\"Imperial College of Science, Technology and Medicine\", role = c(\"cph\", \"fnd\"))\n)",
  "Description": "Run diagnostics on burden estimates submitted by modellers\nin the Vaccine Impact Modelling Consortium (VIMC) and impact\nestimates calculated by the VIMC Science & Policy team.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/vimc/vimcheck, https://vimc.github.io/vimcheck/",
  "BugReports": "https://github.com/vimc/vimcheck/issues",
  "VignetteBuilder": "knitr",
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  "Repository": "https://vimc.r-universe.dev",
  "Date/Publication": "2026-07-21 11:05:07 UTC",
  "RemoteUrl": "https://github.com/vimc/vimcheck",
  "RemoteRef": "main",
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  "Packaged": {
    "Date": "2026-07-21 12:41:39 UTC",
    "User": "root"
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  "Author": "Pratik Gupte [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-5294-7819>),\nKaty Gaythorpe [aut] (ORCID: <https://orcid.org/0000-0003-3734-9081>),\nXiang Li [aut] (ORCID: <https://orcid.org/0000-0002-5945-159X>),\nZoë Gibney [aut] (ORCID: <https://orcid.org/0009-0002-8114-9984>),\nImperial College of Science, Technology and Medicine [cph, fnd]",
  "Maintainer": "Pratik Gupte <p.gupte24@imperial.ac.uk>",
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  "_expires": "2026-10-29T12:45:29.000Z",
  "_created": "2026-07-21T12:41:39.000Z",
  "_published": "2026-07-21T12:45:31.892Z",
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    "author": "Pratik Gupte <pratikgupte16@gmail.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Add impact diagnostics functions (#17)\n\n* Add initial fns from pressure testing report\n\n* Move pressure testing plotting\n\n* Clean up funs and add constants\n\n* Clean up fns and add constants\n\n* Rename files\n\n* Add checks and docs for pressure testing fns\n\n* Add pkg constants\n\n* Add pkg helpers\n\n* WIP separate plot prep from plot code\n\n* WIP add docs and pkg infra\n\n* Reorganise docs\n\n* WIP plotting and prep fns impact diagnostics\n\n* Add constants\n\n* Update plot prep and plot fns\n\n* Fixes from initial test run\n\n* Update infra, bump to v0.0.4\n\n* Rename fn file, fix arg name\n\n* Adding pine countries to constants for impact plotting key countries\n\n* Adding plotting functions from rapid-model-run-impact report which plots central impact estimates, coverage and fvps. Associated documentation also added from attempts at roxygen!\n\n* Fix for enabling package checks\n\n* Adding more meaningful checks and assertions\n\n* Defining example data and fvps dataframes\n\n* Adding impact plots to pkgdown documentation\n\n* Sync _pkgdown.yml with develop\n\n* Added new functions\n\n* Allow R CMD check on PRs\n\n* Fix linting YAML\n\n* Fix formatting\n\n* Rework plotting fns\n\n* Add tests and tweaks, bump to v0.0.5\n\n* Fix docs and spellings\n\n* Fixes from review\n\n* Fix country facetting\n\n---------\n\nCo-authored-by: Zoe Gibney <z.gibney@imperial.ac.uk>",
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    "burden_outcome_names",
    "check_demography_alignment",
    "colnames_df_missing_cols",
    "COLNAMES_INTEREST_PRESSURE_TEST",
    "COLNAMES_KEY_PRESSURE_TEST",
    "colnames_plot_demog_compare",
    "COLOUR_VIMC",
    "compare_natl_subreg",
    "DEF_TOUCHSTONE_NEW",
    "DEF_TOUCHSTONE_OLD",
    "DEF_TOUCHSTONE_OLD_OLD",
    "EXCLUDED_DISEASES",
    "file_dict_colnames",
    "filter_excluded_diseases_ts",
    "filter_invalid_trajectories",
    "filter_recent_ts",
    "flag_duplicates",
    "flag_large_diffs",
    "gen_combined_df",
    "gen_national_iqr",
    "generate_diffs",
    "IMPACT_OUTCOMES",
    "MAX_TS_MONTH",
    "MAX_TS_YEAR",
    "MIN_TS_MONTH",
    "MIN_TS_YEAR",
    "N_TS_MIN_CHARS",
    "N_TS_YEAR_CHARS",
    "PINE",
    "plot_age_patterns",
    "plot_compare_demography",
    "plot_coverage_fvps",
    "plot_coverage_set",
    "plot_cumul",
    "plot_diff",
    "plot_fvp",
    "plot_global_burden",
    "plot_global_burden_decades",
    "plot_impact",
    "plot_modelling_group_variation",
    "plot_sig_diff",
    "plot_vaccine_gavi",
    "prep_plot_age",
    "prep_plot_burden_decades",
    "prep_plot_coverage_set",
    "prep_plot_cumul",
    "prep_plot_demography",
    "prep_plot_fvp",
    "prep_plot_global_burden",
    "prep_plot_mod_grp_varn",
    "prep_plot_vax_gavi",
    "save_outputs",
    "scenario_data_colnames",
    "theme_vimc",
    "theme_vimc_noxaxis",
    "validate_complete_incoming_files",
    "validate_file_dict_template",
    "validate_template_alignment"
  ],
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    {
      "name": "eg_burden_template",
      "title": "Example of VIMC burden template provided to modellers",
      "object": "eg_burden_template",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "disease",
        "year",
        "age",
        "country",
        "country_name",
        "cases",
        "dalys",
        "deaths",
        "yll",
        "cohort_size",
        "scenario"
      ],
      "rows": 20402,
      "table": true,
      "tojson": true
    },
    {
      "name": "eg_coverage",
      "title": "Example of scenario coverage data",
      "object": "eg_coverage",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "scenario_type",
        "scenario_type_description",
        "scenario",
        "scenario_description",
        "coverage_set",
        "gavi_support_level",
        "source_from",
        "disease",
        "vaccine",
        "activity_type",
        "year",
        "country",
        "age_from",
        "age_to",
        "age_range_verbatim",
        "target",
        "coverage",
        "gender",
        "proportion_risk"
      ],
      "rows": 11,
      "table": true,
      "tojson": true
    },
    {
      "name": "eg_fvps",
      "title": "Example of FVP estimate data",
      "object": "eg_fvps",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "scenario_type",
        "scenario_type_description",
        "scenario",
        "scenario_description",
        "coverage_set",
        "gavi_support_level",
        "source_from",
        "disease",
        "vaccine",
        "activity_type",
        "year",
        "country",
        "age_from",
        "age_to",
        "age_range_verbatim",
        "target",
        "coverage",
        "gender",
        "proportion_risk",
        "job",
        "fvps",
        "fvps_adjusted",
        "target_adjusted",
        "coverage_adjusted"
      ],
      "rows": 11,
      "table": true,
      "tojson": true
    },
    {
      "name": "eg_fvps_2",
      "title": "A second FVP data example",
      "object": "eg_fvps_2",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "country",
        "year",
        "activity_type",
        "scenario_type",
        "vaccine",
        "coverage_adjusted",
        "fvps"
      ],
      "rows": 4,
      "table": true,
      "tojson": true
    },
    {
      "name": "eg_impact",
      "title": "Example of impact data",
      "object": "eg_impact",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "modelling_group",
        "country",
        "year",
        "vaccine",
        "activity_type",
        "burden_outcome",
        "impact",
        "disease",
        "country_name"
      ],
      "rows": 5396,
      "table": true,
      "tojson": true
    },
    {
      "name": "eg_impact_2",
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      "object": "eg_impact_2",
      "class": [
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        "tbl",
        "data.frame"
      ],
      "fields": [
        "country",
        "year",
        "birth_cohort",
        "burden_outcome",
        "impact",
        "short_name"
      ],
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      "table": true,
      "tojson": true
    },
    {
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      "class": [
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        "tbl",
        "data.frame"
      ],
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        "year",
        "age",
        "gender",
        "value"
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      "table": true,
      "tojson": true
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      "object": "who_subregions",
      "class": [
        "spec_tbl_df",
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        "tbl",
        "data.frame"
      ],
      "fields": [
        "choice_subregion",
        "country_name",
        "country",
        "Global.Name",
        "Region.Name",
        "Sub.region",
        "Intermediate.Region.Name",
        "subregion",
        "vimc117"
      ],
      "rows": 249,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "vimcheck-package",
      "title": "vimcheck: Diagnostics for Vaccine Impact Modelling Consortium Burden and Impact Estimates",
      "topics": [
        "vimcheck-package",
        "vimcheck"
      ]
    },
    {
      "page": "basic_burden_sanity",
      "title": "Sanity checks on burden estimates",
      "topics": [
        "basic_burden_sanity"
      ]
    },
    {
      "page": "check_demography_alignment",
      "title": "Check incoming burden cohort size against interpolated population",
      "topics": [
        "check_demography_alignment"
      ]
    },
    {
      "page": "compare_natl_subreg",
      "title": "Compare sub-regional and national estimates",
      "topics": [
        "compare_natl_subreg"
      ]
    },
    {
      "page": "constants",
      "title": "Package constants",
      "topics": [
        "burden_outcome_names",
        "colnames_df_missing_cols",
        "COLNAMES_INTEREST_PRESSURE_TEST",
        "COLNAMES_KEY_PRESSURE_TEST",
        "colnames_plot_demog_compare",
        "COLOUR_VIMC",
        "constants",
        "DEF_TOUCHSTONE_NEW",
        "DEF_TOUCHSTONE_OLD",
        "DEF_TOUCHSTONE_OLD_OLD",
        "EXCLUDED_DISEASES",
        "file_dict_colnames",
        "IMPACT_OUTCOMES",
        "MAX_TS_MONTH",
        "MAX_TS_YEAR",
        "MIN_TS_MONTH",
        "MIN_TS_YEAR",
        "N_TS_MIN_CHARS",
        "N_TS_YEAR_CHARS",
        "PINE",
        "scenario_data_colnames"
      ]
    },
    {
      "page": "eg_burden_template",
      "title": "Example of VIMC burden template provided to modellers",
      "topics": [
        "eg_burden_template"
      ]
    },
    {
      "page": "eg_coverage",
      "title": "Example of scenario coverage data",
      "topics": [
        "eg_coverage"
      ]
    },
    {
      "page": "eg_fvps",
      "title": "Example of FVP estimate data",
      "topics": [
        "eg_fvps"
      ]
    },
    {
      "page": "eg_fvps_2",
      "title": "A second FVP data example",
      "topics": [
        "eg_fvps_2"
      ]
    },
    {
      "page": "eg_impact",
      "title": "Example of impact data",
      "topics": [
        "eg_impact"
      ]
    },
    {
      "page": "eg_impact_2",
      "title": "Second example of impact data",
      "topics": [
        "eg_impact_2"
      ]
    },
    {
      "page": "eg_wpp",
      "title": "Example of UN-WPP time-series data",
      "topics": [
        "eg_wpp"
      ]
    },
    {
      "page": "filter_impact_data",
      "title": "Filter data for touchstones or diseases",
      "topics": [
        "filter_excluded_diseases_ts",
        "filter_impact_data",
        "filter_invalid_trajectories",
        "filter_recent_ts",
        "flag_duplicates"
      ]
    },
    {
      "page": "flag_large_diffs",
      "title": "Flag significant changes in impact estimates",
      "topics": [
        "flag_large_diffs"
      ]
    },
    {
      "page": "gen_combined_df",
      "title": "Combine and align data from two touchstones",
      "topics": [
        "gen_combined_df"
      ]
    },
    {
      "page": "gen_national_iqr",
      "title": "Generate IQR for key outcomes",
      "topics": [
        "gen_national_iqr"
      ]
    },
    {
      "page": "generate_diffs",
      "title": "Explore significant changes in deaths and DALYs",
      "topics": [
        "generate_diffs"
      ]
    },
    {
      "page": "plot_burden_diagnostics",
      "title": "Plot burden and impact diagnostics",
      "topics": [
        "plot_age_patterns",
        "plot_burden_diagnostics",
        "plot_compare_demography",
        "plot_coverage_set",
        "plot_fvp",
        "plot_global_burden",
        "plot_global_burden_decades"
      ]
    },
    {
      "page": "plot_coverage_fvps",
      "title": "Plot coverage and fully vaccinated persons (FVPs)",
      "topics": [
        "plot_coverage_fvps"
      ]
    },
    {
      "page": "plot_impact",
      "title": "Plot central impact estimates by cohort and year",
      "topics": [
        "plot_impact"
      ]
    },
    {
      "page": "plot_impact_diagnostics",
      "title": "Create impact diagnostics plots",
      "topics": [
        "plot_cumul",
        "plot_diff",
        "plot_impact_diagnostics",
        "plot_modelling_group_variation",
        "plot_sig_diff",
        "plot_vaccine_gavi"
      ]
    },
    {
      "page": "plot_prep_burden_diagnostics",
      "title": "Prepare data for plotting",
      "topics": [
        "plot_prep_burden_diagnostics",
        "prep_plot_age",
        "prep_plot_burden_decades",
        "prep_plot_coverage_set",
        "prep_plot_demography",
        "prep_plot_fvp",
        "prep_plot_global_burden"
      ]
    },
    {
      "page": "plot_prep_impact_diagnostics",
      "title": "Prepare impact diagnostics for plotting",
      "topics": [
        "plot_prep_impact_diagnostics",
        "prep_plot_cumul",
        "prep_plot_mod_grp_varn",
        "prep_plot_vax_gavi"
      ]
    },
    {
      "page": "plotting_theme",
      "title": "Plotting theme for vimcheck",
      "topics": [
        "plotting_theme",
        "theme_vimc",
        "theme_vimc_noxaxis"
      ]
    },
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