censored.deviation

When first records of incidence are unavailable, tries to impute censored
cases to rebuild longer epidemic vector.

internal

Estimation of reproduction numbers for disease outbreak, based on
incidence data. The R0 package implements several documented methods. It is
therefore possible to compare estimations according to the methods used.
Depending on the methods requested by user, basic reproduction number
(commonly denoted as R0) or real-time reproduction number (referred to as
R(t)) is computed, along with a 95% Confidence Interval. Plotting outputs
will give different graphs depending on the methods requested : basic
reproductive number estimations will only show the epidemic curve
(collected data) and an adjusted model, whereas real-time methods will also
show the R(t) variations throughout the outbreak time period. Sensitivity
analysis tools are also provided, and allow for investigating effects of
varying Generation Time distribution or time window on estimates.

Thomas Obadia

Estimation of R0 and Real-Time Reproduction Number from
Epidemics

censored.deviation function

<dl><dt>optim.vect</dt>
<dd>Vector of two elements <code>c(multiplicative factor, log(highest imputed data))</code> corresponding to initial values.</dd>
<dt>epid</dt>
<dd>Original epidemic vector, output of <code>check.incid()</code>.</dd>
<dt>R0</dt>
<dd>Assumed R0 value for the original epidemic vector.</dd>
<dt>GT</dt>
<dd>Generation time distribution to be used for computations.</dd></dl>

Arguments

Author

Deviation between theorietical incidence and observed data. — censored.deviation

<dl>

<dt>optim.vect</dt>
<dd>Vector of two elements <code>c(multiplicative factor, log(highest imputed data))</code> corresponding to initial values.</dd>


<dt>epid</dt>
<dd>Original epidemic vector, output of <code>check.incid()</code>.</dd>


<dt>R0</dt>
<dd>Assumed R0 value for the original epidemic vector.</dd>


<dt>GT</dt>
<dd>Generation time distribution to be used for computations.</dd>

</dl>

censored.deviation: Deviation between theorietical incidence and observed data.

Description

Usage

Value

Arguments

Author

Details