impute.incid

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

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

impute.incid function

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

Arguments

Author

Optimiziation routine for incidence imputation — impute.incid

<dl>

 <dt>CD.optim.vect</dt>
<dd>Vector of two elements (multiplicative factor, log(highest imputed data) to be optimized</dd>

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

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

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

</dl>

impute.incid: Optimiziation routine for incidence imputation

Description

Usage

Value

Arguments

Author

Details