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
Provides a rapid and computationally simple method for calculating seroconversion rates
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).
Other
Additional tools for serological analysis
An R package designed to quantify an individual’s antigenic landscape, which comprises hemagglutination inhibition (HAI) titers against a panel of influenza viruses isolated at various times or in different antigenic spaces.
External package - not managed by seroanalytics
R package for analyzing correlates of protection using Bayesian methods.
Serological Blog Posts
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1. WHAT DOES IT MEAN TO BE INFECTED?
Unpacking the blurred lines between biology, diagnosis, transmission, and immunity.
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2. A DUMMIES' GUIDE TO SEROLOGICAL ASSAYS
Not all test results mean the same thing. The trick is knowing which oracle to trust.
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3. CORRELATES OF PROTECTION: FUMBLING THROUGH THE TERMINOLOGY
The (confusing) statistical frameworks that could accelerate vaccine approvals.
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4. THE SHORTCUT TO VACCINE APPROVALS: WHEN BLOOD TESTS REPLACE CLINICAL TRIALS
A journey through history's successes (and stumbles).
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5. WHAT CAN I INFER FROM CROSS-SECTIONAL SEROLOGICAL DATA?
A Practical Primer.