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The epidemic process and the reporting process

Source: R/diagnostic_plot.R
plot_epidemic_process.Rd

[Stable]

The same cases, counted on two different clocks. Comparing the two is the single most useful thing you can do to tell a real outbreak from a reporting artifact.

  • plot_epidemic_process() counts by event date – when the cases actually happened. Epidemics grow and shrink smoothly, so this curve should be smooth.

  • plot_reporting_process() counts by report date – when news of them arrived. Reporting is administrative, so this curve is spiky: weekends, holidays and backlog releases all show up here.

A lone spike in the reporting process with nothing under it in the epidemic process is a batch – a day the system cleared its inbox, not a day people got sick. A spike in both is a genuine surge.

Usage

plot_reporting_process(
  x,
  plotly = FALSE,
  axis = c("report", "revision"),
  by_revision_type = TRUE,
  palette = .tbl_now_palette()
)

plot_epidemic_process(
  x,
  plotly = FALSE,
  axis = c("report", "revision"),
  palette = .tbl_now_palette()
)

Arguments

x

A tbl_now() object.

plotly

If TRUE, return an interactive plotly widget (hover, zoom) instead of a static ggplot2 plot. Default FALSE.

axis

Which time axis to draw: "report" (default) or "revision". On the revision axis the picture answers the laboratory's version of the question – when results arrived, rather than when reports did. Needs a revision process (see add_revision_date()); cases still "pending" have no revision date and are left out.

by_revision_type

Logical (default TRUE), plot_reporting_process() only. Stack each bar by how the arrivals it counts eventually resolved – confirmed, pending, retracted and unknown, in the palette's outcome colours (see tbl_now_palette()) – so a day whose reports were mostly taken back is visible as such rather than as an ordinary day. Ignored on an object with no revision axis. It cannot be taken from count-cumulative data, which records running totals rather than cases, and warns and draws the unsplit bars there.

palette

A named colour palette (see tbl_now_palette()). These two panels draw bars and nothing else, so they take no size or linewidth.

Value

A ggplot2 object (or a plotly widget when plotly = TRUE).

Details

Both are facetted by stratum when the object has strata.

See also

diagnostic_plot(), which draws these alongside the rest of the reporting-process gallery; plot_observed_cases() for the epidemic process with the incompleteness cutoff marked; diagnose_batches() to test a suspicious spike rather than eyeball it.

Examples

data(denguedat)
dn <- tbl_now(denguedat, onset_week, report_week, verbose = FALSE)

# When cases happened: smooth, because epidemics are.
plot_epidemic_process(dn)


# When news of them arrived: spikier, because reporting is administrative.
plot_reporting_process(dn)