covid_delay_dist

Daily case, hospitalization, and death proportions.

datasets

Make empirical Bayes incidence curves from reported case data using a specified delay distribution.

Lauren Hannah

incidental

Implements Empirical Bayes Incidence Curves

Andrew Miller

Nicholas Foti

Joseph Futoma

Apple, Inc. 

covid_delay_dist function

A data frame with 61 entries and 4 columns.<dl class="dl-horizontal">
 <dt>days</dt><dd>number of days since infection</dd>
 <dt>case</dt><dd>proportion of cases confirmed by a test that are recorded on that day</dd>
 <dt>hospitalization</dt><dd>proportion of cases that become hospitalized that are hospitalized on that day</dd>
 <dt>death</dt><dd>proportion of cases that result in death that die on that day</dd>
</dl>

Format

Delay distribution from COVID-19 pandemic. — covid_delay_dist

A data frame with 61 entries and 4 columns.<dl class='dl-horizontal'>
 <dt>days</dt><dd>number of days since infection</dd>
 <dt>case</dt><dd>proportion of cases confirmed by a test that are recorded on that day</dd>
 <dt>hospitalization</dt><dd>proportion of cases that become hospitalized that are hospitalized on that day</dd>
 <dt>death</dt><dd>proportion of cases that result in death that die on that day</dd>
</dl>

covid_delay_dist: Delay distribution from COVID-19 pandemic.

Description

Usage

Arguments

Format