serosim is an R package for simulating serological data from user-specified vaccine or infection-generated and antibody kinetics processes.
Seroanalytics
A directory of free, open-source tools for exploring, modeling and understanding serological data.
How to Use Seroanalytics
Simulate
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Visualise
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Model
Simulate
Generate synthetic serological data for testing and validation
Model Cross-Sectional Data
Analyze cross-sectional serological data with advanced statistical models
Rsero is an R package to estimate the annual force of infection using serological data. It provides tools for analyzing cross-sectional serological surveys and fitting serocatalytic models.
External package - not managed by seroanalytics
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. Part of the Epiverse Initiative.
External package - not managed by seroanalytics
serosv is an easy-to-use and efficient tool to estimate infectious diseases parameters (seroprevalence and force of infection) using serological data.
External package - not managed by seroanalytics
Model Longitudinal Data
Track antibody kinetics and immune responses over time
serosolver is an R package using a hierarchical model with a custom Markov chain Monte Carlo sampler to simultaneously infer antibody kinetics and infection histories from cross-sectional or longitudinal serological data.
epikinetics is an R package for Bayesian hierarchical modelling of antibody kinetics.
serojump is an R package providing tools for fitting serological models to antibody kinetics data using reversible-jump Markov Chain Monte Carlo (RJ-MCMC).