covid_delay_dist: Delay distribution from COVID-19 pandemic.
In incidental: Implements Empirical Bayes Incidence Curves

Daily case, hospitalization, and death proportions.

1	covid_delay_dist

A data frame with 61 entries and 4 columns.

days: number of days since infection
case: proportion of cases confirmed by a test that are recorded on that day
hospitalization: proportion of cases that become hospitalized that are hospitalized on that day
death: proportion of cases that result in death that die on that day

Time from incidence to symptoms: Lauer et al., "Estimated Incubation Period of COVID-19", ACC (2020). https://www.acc.org/latest-in-cardiology/journal-scans/2020/05/11/15/18/the-incubation-period-of-coronavirus-disease.

Time from symptoms to recorded cases: Case line data from Florida through 2020-07-14 with same day waits removed. https://open-fdoh.hub.arcgis.com/datasets/florida-covid19-case-line-data.

Time from symptoms to hospitalization: Wang et al., "Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China", JAMA (2020). https://jamanetwork.com/journals/jama/fullarticle/2761044.

Time from hospitalization to death: Lewnard et al. "Incidence, clinical outcomes, and transmission dynamics of severe coronavirus disease 2019 in California and Washington: prospective cohort study", BJM (2020). https://www.bmj.com/content/369/bmj.m1923.long

incidental documentation built on Sept. 16, 2020, 5:07 p.m.