baselinenowcast_df-class

baselinenowcast_df

A <code>baselinenowcast_df</code> object which contains point or probabilistic nowcasts
alongside reference dates and any additional metadata, in tidy data format.
Nowcasts are presented aggregated across delays, by reference date.

Nowcasting right-truncated epidemiological data is critical
for timely public health decision-making, as reporting delays can create
misleading impressions of declining trends in recent data. This package
provides nowcasting methods based on using empirical
delay distributions and uncertainty from past performance. It is also designed
to be used as a baseline method for developers of new nowcasting methods.
For more details on the performance of the method(s) in this package applied
to case studies of COVID-19 and norovirus, see our recent paper at
<https://wellcomeopenresearch.org/articles/10-614>. The package supports
standard data frame inputs with reference date, report date, and
count columns, as well as the direct use of reporting triangles, and is
compatible with 'epinowcast' objects. Alongside
an opinionated default workflow, it has a low-level pipe-friendly modular
interface, allowing context-specific workflows. It can accommodate a wide
spectrum of reporting schedules, including mixed patterns of reference and
reporting (daily-weekly, weekly-daily). It also supports sharing delay
distributions and uncertainty estimates between strata,
as well as custom uncertainty models and delay estimation methods.

Kaitlyn Johnson

baselinenowcast

Baseline Nowcasting for Right-Truncated Epidemiological Data

Emily Tyszka

Johannes Bracher

Sebastian Funk

Sam Abbott

Tim Taylor

baselinenowcast_df-class function

A <code>baselinenowcast_df</code> is a data.frame with the following columns:<dl>
<dt>reference_date</dt>
<dd>Dates corresponding to the reference times of the
nowcast.</dd><dt>pred_count</dt>
<dd>Numeric indicating the estimated total counts aggregated
across delays at each reference date.</dd><dt>draw</dt>
<dd>Integer indexing the sample from the probabilistic nowcast
distribution. If <code>output_type = "point"</code>, this will be set to 1.</dd><dt>output_type</dt>
<dd>Character string indicating whether the <code>pred_count</code>
represents a probabilistic draw from the observation model indicated by
<code>"samples"</code> or whether the <code>pred_count</code> is a point estimate indicated by
<code>"point"</code>.</dd>
</dl>See the corresponding reporting_triangle and
<code>baselinenowcast()</code> function
for more details on the required inputs to generate the object.

Structure

Nowcast Data.frame Object — baselinenowcast_df-class

A <code>baselinenowcast_df</code> is a data.frame with the following columns:<dl>
<dt>reference_date</dt>
<dd>Dates corresponding to the reference times of the
nowcast.</dd>

<dt>pred_count</dt>
<dd>Numeric indicating the estimated total counts aggregated
across delays at each reference date.</dd>

<dt>draw</dt>
<dd>Integer indexing the sample from the probabilistic nowcast
distribution. If <code>output_type = "point"</code>, this will be set to 1.</dd>

<dt>output_type</dt>
<dd>Character string indicating whether the <code>pred_count</code>
represents a probabilistic draw from the observation model indicated by
<code>"samples"</code> or whether the <code>pred_count</code> is a point estimate indicated by
<code>"point"</code>.</dd>


</dl>See the corresponding reporting_triangle and
<code>baselinenowcast()</code> function
for more details on the required inputs to generate the object.

baselinenowcast_df-class: Nowcast Data.frame Object

Description

Arguments

Value

Structure

See Also