covid19_sa

<p>An aggregated subset of the COVID-19 Data Repository for South Africa
created, maintained and hosted by Data Science for Social Impact research
group, led by Dr. Vukosi Marivate.</p>

datasets

Provides methods to simulate and analyse the size and length
of branching processes with an arbitrary offspring distribution. These
can be used, for example, to analyse the distribution of chain sizes
or length of infectious disease outbreaks, as discussed in Farrington
et al. (2003) <doi:10.1093/biostatistics/4.2.279>.

James M. Azam

epichains

Simulating and Analysing Transmission Chain Statistics Using
Branching Process Models

Sebastian Funk

Flavio Finger

Zhian N. Kamvar

Hugo Gruson

Karim Mané

Pratik Gupte

Joshua W. Lambert

covid19_sa function


<div class="section" id="covid-sa">
<h3><code>covid19_sa</code></h3><p></p><p>
</p><p>A data frame with 19 rows and 2 columns:</p><dl>
<dt>date</dt>
<dd><p>Date case was reported</p></dd><p></p><p><dt>cases</dt>
<dd><p>Number of cases</p></dd></p><p>
</p></dl><p></p><p></p></div>


Format

COVID-19 Data Repository for South Africa — covid19_sa


<div class='section' id='covid-sa'>
<h3><code>covid19_sa</code></h3>


<p>A data frame with 19 rows and 2 columns:</p><dl>
<dt>date</dt>
<dd><p>Date case was reported</p></dd>

<dt>cases</dt>
<dd><p>Number of cases</p></dd>


</dl>

</div>


COVID-19 Data Repository for South Africa

covid19_sa: COVID-19 Data Repository for South Africa

Description

Usage

Arguments

Format

`covid19_sa`

Details