prob_seroprev_time_by_age

This function calculates the probabilities of seropositivity by age based on
a time-varying FoI model.
It takes into account the FoI and the rate of seroreversion.

Estimating the force of infection from time varying, age varying, or constant
serocatalytic models from population based seroprevalence studies using a Bayesian framework,
including data simulation functions enabling the generation of serological surveys based on this
models. This tool also provides a flexible prior specification syntax for the force of infection
and the seroreversion rate, as well as methods to assess model convergence and comparison
criteria along with useful visualisation functions.

Zulma M. Cucunubá

serofoi

Bayesian Estimation of the Force of Infection from Serological
Data

Nicolás T. Domínguez

Ben Lambert

Pierre Nouvellet

Geraldine Gómez

Jaime A. Pavlich-Mariscal

Hugo Gruson

David Santiago Quevedo

Miguel Gámez

Sumali Bajaj

Everlyn Kamau

Richard Creswell

International Development Research Center (IDRC) 

Pontificia Universidad Javeriana 

prob_seroprev_time_by_age function

<dl><dt>foi</dt>
<dd>A dataframe containing the FoI values
for different years. It should have two columns: 'year' and 'foi'.</dd>
<dt>seroreversion_rate</dt>
<dd>A non-negative numeric value representing the
rate of seroreversion.</dd></dl>

Arguments

Generate probabilities of seropositivity by age based on a time-varying
Force-of-Infection (FoI) model. — prob_seroprev_time_by_age

<dl>

<dt>foi</dt>
<dd>A dataframe containing the FoI values
for different years. It should have two columns: 'year' and 'foi'.</dd>


<dt>seroreversion_rate</dt>
<dd>A non-negative numeric value representing the
rate of seroreversion.</dd>

</dl>

Generate probabilities of seropositivity by age based on a time-varying
Force-of-Infection (FoI) model.

prob_seroprev_time_by_age: Generate probabilities of seropositivity by age based on a time-varying Force-of-Infection (FoI) model.

Description

Usage

Value

Arguments