serofoi is an R package to estimate the Force-of-Infection (FoI) of a given pathogen from age-disaggregated population-based cross-sectional serosurveys, using a Bayesian framework. The package provides a set of features for assessing model fitting, convergence and visualisation.
serofoi relies on the rstan
package, which provides an R interface for the Stan programming language
for statistical Bayesian modelling. Particularly, serofoi
relies on the use of a Hamiltonian Monte Carlo (HMC) algorithm
implemented by Stan for Markov chain Monte Carlo (MCMC)
sampling. The implemented methods are outlined in (Cucunubá et al. 2017) and (Carrera et al. 2020) (see FoI
Models for further details). A compelling mathematical treatment of
the implemented serocatalytic models can be found in (Kamau et al. 2025).
serofoi is part of the Epiverse Initiative.
You can install serofoi from CRAN using:
install.packages("serofoi")You can install the development version of serofoi from GitHub running:
if(!require("pak")) install.packages("pak")
pak::pak("epiverse-trace/serofoi")or:
if(!require("remotes")) install.packages("remotes")
remotes::install_github("epiverse-trace/serofoi")serofoi provides some minimal serosurvey datasets that can
be used to test out the package. For instance, the dataset
chagas2012 contains seroprevalence measures of IgG
antibodies against Trypanosoma cruzi infection corresponding to a
serological survey conducted in Colombia during 2012 on a rural
indigenous community that is known to present long-term endemic
transmission
# Load example dataset chagas2012 included with the package
data(chagas2012)
head(chagas2012, 5)
#> survey_year n_sample n_seropositive age_min age_max
#> 1 2012 34 0 1 1
#> 2 2012 25 0 2 2
#> 3 2012 35 1 3 3
#> 4 2012 29 0 4 4
#> 5 2012 36 0 5 5A visualisation of the serological data can be obtained using the
function plot_serosurvey:
plot_serosurvey(chagas2012, bin_serosurvey = TRUE, size_text = 15)
Seroprevalence plot for the chagas2012 dataset.
Here, the error bars correspond to the binomial confidence interval and the point size represents the sample size for each age group.
A constant FoI model can easily be implemented by means of
fit_seromodel:
seromodel <- fit_seromodel(serosurvey = chagas2012)For further details on how to visualise the results and other available models, please refer to the online documentation.
Contributors to the project include:
Zulma M. Cucunubá (author, maintainer)
Nicolás Torres (author)
Ben Lambert (author)
Pierre Nouvellet (author)
Geraldine Gómez (contributor)
Jaime A. Pavlich-Mariscal (contributor)
Miguel Gamez (contributor)
Hugo Gruson (contributor)
David Santiago Quevedo (contributor)
Everlyn Kamau (contributor)
Richard Creswell (contributor)
Sumali Bajaj (contributor)
More details on how to use serofoi can be found in the online documentation as package vignettes, under “Articles”.
To report a bug please open an issue.
Contributions to serofoi are welcomed. Please follow the package contributing guide.
Please note that the serofoi project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.