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Draw the Dashboard Charts (Epidemic Curve, Trend, and Rt)

Source: R/app_charts.R
episodic_charts.Rd

These functions build the three time-series charts used throughout the EpiSODIC dashboard and outbreak reports: an epidemic curve, a trend chart against the expected baseline, and an effective reproduction number (\(R_t\)) chart. Each takes the small, already-summarised data frame the app itself works with, so they are also useful for reproducing a dossier's chart in your own report or presentation. All three return a static ggplot2::ggplot object that can be printed, saved with ggplot2::ggsave(), or further customised with additional ggplot2 layers.

Usage

episodic_ui_epi_curve_chart(
  curve,
  lang = Sys.getenv("EPISODIC_LANGUAGE"),
  accent = NULL
)

episodic_ui_trend_chart(
  trend,
  lang = Sys.getenv("EPISODIC_LANGUAGE"),
  accent = NULL
)

episodic_ui_rt_chart(rt, lang = Sys.getenv("EPISODIC_LANGUAGE"), accent = NULL)

Arguments

curve

A data frame with one row per day: sample_date (Date), n_cases (case count), and incomplete (logical, TRUE for the most recent day(s) where reporting is still catching up - these are drawn at reduced opacity as a visual reminder not to over-interpret a downturn that is really just a reporting lag). Optionally nowcast_low, nowcast_mid and nowcast_high: the 5%, 50% and 95% quantiles of a day's expected final count once reporting is complete, drawn as a line with an open point at the median on the days that have them (NA elsewhere).

lang

Language for axis labels: "en", "ar", "nl", "fr", "de", "hi", "zh", or "es", or a regional variant of one ("en-US", "es-419"). Defaults to the EPISODIC_LANGUAGE environment variable, falling back to "en" if that is unset.

accent

Fill colour for the bars. Defaults to the palette's primary, which every chart in the dashboard uses for its main series; the status colours are kept for marks that mean something (thresholds, positivity).

trend

A data frame with one row per week: week_start (Date), n_cases (observed count), expected (the Farrington baseline), and upperbound (the alarm threshold, shown as a shaded band).

rt

A data frame with one row per estimation window: window_end (Date), mean (point estimate of \(R_t\)), and lower/upper (95% credible interval). A dashed reference line is drawn at \(R_t = 1\), the threshold between a shrinking and a growing outbreak. The y axis is on a log2 scale, labelled in \(R_t\) itself, so that a halving and a doubling sit the same distance either side of that line.

Value

A ggplot2::ggplot object.

Examples

curve <- data.frame(
  sample_date = seq(as.Date("2025-01-01"), by = "day", length.out = 14),
  n_cases = c(1, 0, 2, 1, 3, 2, 4, 3, 5, 2, 1, 0, 1, 2),
  incomplete = c(rep(FALSE, 12), TRUE, TRUE)
)
episodic_ui_epi_curve_chart(curve, lang = "en")

trend <- data.frame(
  week_start = seq(as.Date("2025-01-06"), by = "week", length.out = 8),
  n_cases = c(2, 3, 1, 4, 6, 5, 3, 2),
  expected = c(2, 2, 2, 2, 2, 2, 2, 2),
  upperbound = c(4, 4, 4, 4, 4, 4, 4, 4)
)
episodic_ui_trend_chart(trend, lang = "en")

rt <- data.frame(
  window_end = seq(as.Date("2025-01-08"), by = "day", length.out = 5),
  mean = c(1.4, 1.3, 1.1, 0.9, 0.8),
  lower = c(1.0, 0.9, 0.8, 0.6, 0.5),
  upper = c(1.8, 1.7, 1.4, 1.2, 1.1)
)
episodic_ui_rt_chart(rt)