{
  "_id": "6ac91f3fde46216d5edd9dab",
  "Package": "csalert",
  "Title": "Alerts from Public Health Surveillance Data",
  "Version": "2026.10.13",
  "Authors@R": "c(\nperson(\ngiven = c(\"Beatriz\", \"Valcarcel\"),\nfamily = \"Salamanca\",\nemail = \"beva@fhi.no\",\nrole = \"aut\"\n),\nperson(\ngiven = \"Chi\",\nfamily = \"Zhang\",\nemail = \"andreachizhang@yahoo.com\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0003-0501-5909\")\n),\nperson(\ngiven = c(\"Richard\", \"Aubrey\"),\nfamily = \"White\",\nemail = \"hello@rwhite.no\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-6747-1726\")\n),\nperson(\ngiven = \"Folkehelseinstituttet\",\nrole = \"cph\"\n)\n)",
  "Description": "Helps create alerts and determine trends by using various\nmethods to analyze public health surveillance data. The primary\nanalysis method is based upon a published analytics strategy by\nBenedetti (2019) <doi:10.5588/pha.19.0002>.",
  "License": "MIT + file LICENSE",
  "URL": "https://niphr.github.io/csalert/, https://github.com/niphr/csalert",
  "BugReports": "https://github.com/niphr/csalert/issues",
  "Encoding": "UTF-8",
  "VignetteBuilder": "knitr",
  "Remotes": [
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  "Config/Needs/website": "niphr/cstemplate",
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  "Roxygen": "list(markdown = TRUE)",
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://niphr.r-universe.dev",
  "Date/Publication": "2026-10-09 14:39:14 UTC",
  "RemoteUrl": "https://github.com/niphr/csalert",
  "RemoteRef": "HEAD",
  "RemoteSha": "8f88045272b717a4785607568bb39f081c4c094f",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-10-09 16:39:12 UTC",
    "User": "root"
  },
  "Author": "Beatriz Valcarcel Salamanca [aut],\nChi Zhang [aut] (ORCID: <https://orcid.org/0000-0003-0501-5909>),\nRichard Aubrey White [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-6747-1726>),\nFolkehelseinstituttet [cph]",
  "Maintainer": "Richard Aubrey White <hello@rwhite.no>",
  "_user": "niphr",
  "_type": "src",
  "_file": "csalert_2026.10.13.tar.gz",
  "_fileid": "https://r2.ropensci.org/8ce2cea1ab56d4dd63bddb4ef73d34c87eeb47c015a62a589e65c42a8cce15a7",
  "_filesize": 627504,
  "_sha256": "8ce2cea1ab56d4dd63bddb4ef73d34c87eeb47c015a62a589e65c42a8cce15a7",
  "_expires": "2027-01-17T17:07:09.000Z",
  "_created": "2026-10-09T16:39:12.000Z",
  "_published": "2026-10-09T17:07:11.292Z",
  "_buildurl": "https://github.com/r-universe/niphr/actions/runs/37959799040",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_jobs": [
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  "_upstream": "https://github.com/niphr/csalert",
  "_commit": {
    "id": "8f88045272b717a4785607568bb39f081c4c094f",
    "author": "Richard Aubrey White <hello@rwhite.no>",
    "committer": "Richard Aubrey White <hello@rwhite.no>",
    "message": "Remove the interval and outage_gap_days options of the ECDF nowcast (2026.10.13)\n\nOn 52 replayed weeks of Norwegian surveillance data, neither\ninterval = \"log_robust\" nor outage_gap_days beat the default empirical\ninterval by enough to matter. The arguments go, with the internals used\nonly by them: .ecdf_complete_options, .option_week, .option_draws,\n.outage_pool, .gap_len, .check_outage_gap_days and .ecdf_series_draws.\nTheir tests and the reference-implementation branches go too.\n\nThe default path is unchanged: identical() output and identical RNG\nstate afterwards on 3 triangles in 6 configurations, against 5b6f206.\nThat check goes red under a mutation of the default path.\n\nThe method rejects anything in `...`, so a call that still passes a\nremoved argument errors instead of silently getting the default (found\nby codex review). Proven red with the check disabled.\n\ntestthat: 520 expectations, 0 failed. R CMD check --as-cran: 0 errors,\n0 warnings, 1 NOTE (time server unreachable).\n",
    "time": 1791556754
  },
  "_maintainer": {
    "name": "Richard Aubrey White",
    "email": "hello@rwhite.no",
    "login": "raubreywhite",
    "orcid": "0000-0002-6747-1726",
    "twitter": "@raubreywhite",
    "description": "Statistician. Head of @norsyss within @folkehelseinstituttet \n",
    "uuid": 1532091
  },
  "_distro": "resolute",
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.1.0",
      "role": "Depends"
    },
    {
      "package": "data.table",
      "role": "Imports"
    },
    {
      "package": "ggplot2",
      "role": "Imports"
    },
    {
      "package": "glm2",
      "role": "Imports"
    },
    {
      "package": "cstidy",
      "version": ">= 2026.7.1",
      "role": "Imports"
    },
    {
      "package": "cstime",
      "role": "Imports"
    },
    {
      "package": "digest",
      "role": "Imports"
    },
    {
      "package": "lubridate",
      "role": "Imports"
    },
    {
      "package": "matrixStats",
      "role": "Imports"
    },
    {
      "package": "stringr",
      "role": "Imports"
    },
    {
      "package": "surveillance",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "testthat",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "glue",
      "role": "Suggests"
    },
    {
      "package": "csmaps",
      "role": "Suggests"
    },
    {
      "package": "mem",
      "role": "Suggests"
    },
    {
      "package": "scoringutils",
      "role": "Suggests"
    }
  ],
  "_owner": "niphr",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2025-52",
      "n": 3
    },
    {
      "week": "2026-27",
      "n": 13
    },
    {
      "week": "2026-30",
      "n": 5
    },
    {
      "week": "2026-32",
      "n": 8
    },
    {
      "week": "2026-34",
      "n": 10
    },
    {
      "week": "2026-35",
      "n": 13
    },
    {
      "week": "2026-39",
      "n": 14
    },
    {
      "week": "2026-41",
      "n": 10
    }
  ],
  "_tags": [],
  "_topics": [
    "csverse"
  ],
  "_stars": 1,
  "_contributors": [
    {
      "user": "raubreywhite",
      "count": 187,
      "uuid": 1532091
    },
    {
      "user": "bedavs",
      "count": 22,
      "uuid": 15072977
    },
    {
      "user": "chizapoth",
      "count": 3,
      "uuid": 32897643
    }
  ],
  "_userbio": {
    "uuid": 244534951,
    "type": "organization",
    "name": "Norwegian Institute of Public Health - R codebases",
    "followers": 3,
    "description": "The Norwegian Institute of Public Health is a government agency under the Ministry of Health and Care Services."
  },
  "_downloads": {
    "count": 580,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/csalert"
  },
  "_devurl": "https://github.com/niphr/csalert",
  "_pkgdown": "https://niphr.github.io/csalert/",
  "_searchresults": 4,
  "_rbuild": "4.6.1",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/csalert.html",
    "extra/manual.pdf",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "LICENSE"
  ],
  "_realowner": "raubreywhite",
  "_cranurl": false,
  "_releases": [
    {
      "version": "2023.6.17",
      "date": "2023-06-15"
    },
    {
      "version": "2024.6.24",
      "date": "2024-06-24"
    }
  ],
  "_exports": [
    "add_holiday_effect",
    "compare_results",
    "csfmt_ensemble_v3",
    "csfmt_interpret",
    "csfmt_parse",
    "csfmt_reporting_triangle_v3",
    "csfmt_var",
    "ens_add_rate",
    "ens_collapse",
    "isoyearweek_week_start",
    "mem_thresholds_v1",
    "nowcast_backtest",
    "nowcast_censor",
    "nowcast_delay_ecdf_v1",
    "nowcast_passthrough_to_ensemble_v1",
    "nowcast_score_v1",
    "nowcast_truth",
    "q_label",
    "q_value",
    "qc_surveillance_data_v1",
    "qc_week_over_week_v1",
    "reporting_completion_trend_v1",
    "reporting_completion_v1",
    "reporting_triangle_matrix",
    "rolling_slope_matrix",
    "set_time_series_id",
    "short_term_trend",
    "short_term_trend_sts_v1",
    "signal_detection_hlm",
    "simulate_baseline_data",
    "simulate_seasonal_outbreak_data",
    "simulate_spike_outbreak_data",
    "validate_ensemble"
  ],
  "_help": [
    {
      "page": "add_holiday_effect",
      "title": "Multiply simulated counts on public holidays",
      "concept": [
        "data simulation functions"
      ],
      "topics": [
        "add_holiday_effect"
      ]
    },
    {
      "page": "compare_results",
      "title": "Compare two collapsed result sets, column by column",
      "concept": [
        "quality control functions"
      ],
      "topics": [
        "compare_results"
      ]
    },
    {
      "page": "csfmt_ensemble_v3",
      "title": "Build a csfmt_ensemble_v3",
      "concept": [
        "ensemble format functions"
      ],
      "topics": [
        "csfmt_ensemble_v3"
      ]
    },
    {
      "page": "csfmt_interpret",
      "title": "Split every value column name of a table into its parts",
      "concept": [
        "naming grammar functions"
      ],
      "topics": [
        "csfmt_interpret"
      ]
    },
    {
      "page": "csfmt_parse",
      "title": "Split a measure column name into its parts",
      "concept": [
        "naming grammar functions"
      ],
      "topics": [
        "csfmt_parse"
      ]
    },
    {
      "page": "csfmt_reporting_triangle_v3",
      "title": "Build a csfmt_reporting_triangle_v3",
      "concept": [
        "reporting triangle functions"
      ],
      "topics": [
        "csfmt_reporting_triangle_v3"
      ]
    },
    {
      "page": "csfmt_var",
      "title": "Build a measure column name from its parts",
      "concept": [
        "naming grammar functions"
      ],
      "topics": [
        "csfmt_var"
      ]
    },
    {
      "page": "ens_add_rate",
      "title": "Add a rate to an ensemble",
      "concept": [
        "ensemble operations"
      ],
      "topics": [
        "ens_add_rate",
        "ens_add_rate.csfmt_ensemble_v3"
      ]
    },
    {
      "page": "ens_collapse",
      "title": "Collapse the draws of an ensemble to quantiles",
      "concept": [
        "ensemble operations"
      ],
      "topics": [
        "ens_collapse",
        "ens_collapse.csfmt_ensemble_v3"
      ]
    },
    {
      "page": "isoyearweek_week_start",
      "title": "The Monday that starts an ISO week",
      "concept": [
        "reporting triangle functions"
      ],
      "topics": [
        "isoyearweek_week_start"
      ]
    },
    {
      "page": "mem_thresholds_v1",
      "title": "Classify every draw into MEM intensity levels",
      "concept": [
        "ensemble operations"
      ],
      "topics": [
        "mem_thresholds_v1",
        "mem_thresholds_v1.csfmt_ensemble_v3"
      ]
    },
    {
      "page": "nowcast_backtest",
      "title": "Replay a nowcast method on past as-of dates",
      "concept": [
        "nowcast diagnostics"
      ],
      "topics": [
        "nowcast_backtest"
      ]
    },
    {
      "page": "nowcast_censor",
      "title": "Cut a reporting triangle back to what was known on a past date",
      "concept": [
        "nowcast diagnostics"
      ],
      "topics": [
        "nowcast_censor"
      ]
    },
    {
      "page": "nowcast_delay_ecdf_v1",
      "title": "Nowcast a reporting triangle from the delay pattern of settled weeks",
      "concept": [
        "nowcast engines"
      ],
      "topics": [
        "nowcast_delay_ecdf_v1",
        "nowcast_delay_ecdf_v1.csfmt_reporting_triangle_v3"
      ]
    },
    {
      "page": "nowcast_passthrough_to_ensemble_v1",
      "title": "Build an ensemble from a reporting triangle with no nowcast",
      "concept": [
        "nowcast engines"
      ],
      "topics": [
        "nowcast_passthrough_to_ensemble_v1"
      ]
    },
    {
      "page": "nowcast_score_v1",
      "title": "Score replayed nowcast quantiles against the settled truth",
      "topics": [
        "nowcast_score_v1"
      ]
    },
    {
      "page": "nowcast_truth",
      "title": "The settled total of each reference week",
      "concept": [
        "nowcast diagnostics"
      ],
      "topics": [
        "nowcast_truth"
      ]
    },
    {
      "page": "print.csfmt_ensemble_v3",
      "title": "Print a 'csfmt_ensemble_v3'",
      "concept": [
        "ensemble format functions"
      ],
      "topics": [
        "print.csfmt_ensemble_v3"
      ]
    },
    {
      "page": "q_label",
      "title": "Write a probability as a quantile label",
      "concept": [
        "naming grammar functions"
      ],
      "topics": [
        "q_label"
      ]
    },
    {
      "page": "q_value",
      "title": "Read the probability in a quantile label",
      "concept": [
        "naming grammar functions"
      ],
      "topics": [
        "q_value"
      ]
    },
    {
      "page": "qc_surveillance_data_v1",
      "title": "Check that a surveillance feed has data and is up to date",
      "concept": [
        "quality control functions"
      ],
      "topics": [
        "qc_surveillance_data_v1"
      ]
    },
    {
      "page": "qc_week_over_week_v1",
      "title": "Compare this week's run with last week's run",
      "concept": [
        "quality control functions"
      ],
      "topics": [
        "qc_week_over_week_v1"
      ]
    },
    {
      "page": "reporting_completion_trend_v1",
      "title": "Reporting speed by year and by recent month, in one table",
      "concept": [
        "reporting completion functions"
      ],
      "topics": [
        "reporting_completion_trend_v1"
      ]
    },
    {
      "page": "reporting_completion_v1",
      "title": "Measure how fast the counts of a reporting triangle arrive",
      "concept": [
        "reporting completion functions"
      ],
      "topics": [
        "reporting_completion_v1"
      ]
    },
    {
      "page": "reporting_triangle_matrix",
      "title": "Turn a reporting triangle into one count matrix per series",
      "concept": [
        "reporting triangle functions"
      ],
      "topics": [
        "reporting_triangle_matrix"
      ]
    },
    {
      "page": "rolling_slope_matrix",
      "title": "Rolling regression slope down every column of a matrix",
      "concept": [
        "short-term trend functions"
      ],
      "topics": [
        "rolling_slope_matrix"
      ]
    },
    {
      "page": "set_time_series_id",
      "title": "Add a content-hash series id to a data.table",
      "concept": [
        "ensemble format functions"
      ],
      "topics": [
        "set_time_series_id"
      ]
    },
    {
      "page": "short_term_trend",
      "title": "Estimate the short-term trend of a series",
      "concept": [
        "ensemble operations",
        "short-term trend functions"
      ],
      "topics": [
        "short_term_trend",
        "short_term_trend.csfmt_ensemble_v3",
        "short_term_trend.csfmt_rts_data_v1",
        "short_term_trend.csfmt_rts_data_v3"
      ]
    },
    {
      "page": "short_term_trend_sts_v1",
      "title": "Short-term trend alarms on a surveillance sts object",
      "concept": [
        "short-term trend functions"
      ],
      "topics": [
        "short_term_trend_sts_v1"
      ]
    },
    {
      "page": "signal_detection_hlm",
      "title": "Flag weeks above a historical limit",
      "concept": [
        "ensemble operations"
      ],
      "topics": [
        "signal_detection_hlm",
        "signal_detection_hlm.csfmt_ensemble_v3",
        "signal_detection_hlm.csfmt_rts_data_v1",
        "signal_detection_hlm.csfmt_rts_data_v3"
      ]
    },
    {
      "page": "simulate_baseline_data",
      "title": "Simulate daily counts with no outbreak",
      "concept": [
        "data simulation functions"
      ],
      "topics": [
        "simulate_baseline_data"
      ]
    },
    {
      "page": "simulate_seasonal_outbreak_data",
      "title": "Add seasonal outbreaks to simulated daily counts",
      "concept": [
        "data simulation functions"
      ],
      "topics": [
        "simulate_seasonal_outbreak_data"
      ]
    },
    {
      "page": "simulate_spike_outbreak_data",
      "title": "Add short outbreaks to the end of simulated daily counts",
      "concept": [
        "data simulation functions"
      ],
      "topics": [
        "simulate_spike_outbreak_data"
      ]
    },
    {
      "page": "validate_ensemble",
      "title": "Check the shape of a csfmt_ensemble_v3",
      "concept": [
        "ensemble format functions"
      ],
      "topics": [
        "validate_ensemble"
      ]
    }
  ],
  "_pkglogo": "https://github.com/niphr/csalert/raw/HEAD/man/figures/logo.png",
  "_readme": "https://github.com/niphr/csalert/raw/HEAD/README.md",
  "_rundeps": [
    "cli",
    "cpp11",
    "crayon",
    "csdata",
    "cstidy",
    "cstime",
    "data.table",
    "deldir",
    "digest",
    "farver",
    "generics",
    "ggplot2",
    "glm2",
    "glue",
    "gtable",
    "isoband",
    "labeling",
    "lattice",
    "lifecycle",
    "lubridate",
    "magrittr",
    "MASS",
    "Matrix",
    "matrixStats",
    "nlme",
    "polyclip",
    "polyCub",
    "R6",
    "RColorBrewer",
    "rlang",
    "S7",
    "scales",
    "sp",
    "spatstat.data",
    "spatstat.geom",
    "spatstat.univar",
    "spatstat.utils",
    "stringi",
    "stringr",
    "surveillance",
    "timechange",
    "vctrs",
    "viridisLite",
    "withr"
  ],
  "_vignettes": [
    {
      "source": "csalert.Rmd",
      "filename": "csalert.html",
      "title": "Start here: what csalert does and which parts to use",
      "author": "Richard Aubrey White",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What csalert is for",
        "Use the ensemble methods",
        "The current methods work on an ensemble",
        "The deprecated methods work on tables",
        "Where the data formats live",
        "What cannot be done yet",
        "Test data with a known truth"
      ],
      "created": "2026-08-06 06:22:40",
      "modified": "2026-09-24 10:30:17",
      "commits": 4
    },
    {
      "source": "pipeline.Rmd",
      "filename": "pipeline.html",
      "title": "The pipeline: from incomplete counts to published numbers",
      "author": "Richard Aubrey White",
      "engine": "knitr::rmarkdown",
      "headings": [
        "One rule: every stage takes the ensemble and returns it",
        "A synthetic reporting triangle",
        "1. Nowcast",
        "2. Validation: replay the method on the past",
        "The engine completes too much at horizon 0",
        "3. Reporting completion: how fast does the data arrive?",
        "What pct_delayD counts",
        "A worked reference week",
        "The weekday of the extract",
        "\"As of today\", for the weeks on screen",
        "A change in reporting speed: period = \"year\"",
        "Every number here depends on max_delay_days",
        "4. Rate: a nowcast numerator over a nowcast denominator",
        "5. Short-term trend on the rate",
        "Every week gets an interval, the settled weeks too",
        "What that interval is, and what it is not",
        "6. MEM intensity thresholds",
        "7. Signal detection: historical limits",
        "8. Collapse: the end of the chain",
        "9. Quality control",
        "The naming grammar",
        "Where next"
      ],
      "created": "2026-08-06 06:22:40",
      "modified": "2026-10-09 11:34:24",
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