Modeling infectious diseases
Jacqueline Buros & Federica Gazzelloni
Registered Attendees (37) in Partnership with R-Ladies NYC Registered Attendees (39)
April 2023 speakers are Jacqueline Buros, experienced in biostatistics and bioinformatics, she is the author of the survivalstan package and a contributor to the rstanarm package, and Federica Gazzelloni, independent researcher and statistician, author the Oregonfrogs package.
In this talk a deterministic and a Bayesian version of the SIR model is presented.
The deterministic SIR model is a mathematical model used to understand the spread of infectious diseases in a population, assuming that the population is homogeneous and the disease spreads at a constant rate. The Bayesian SIR model, on the other hand, incorporates uncertainty and variability in the model parameters, allowing for more accurate predictions and better decision-making. It uses Bayesian inference to estimate the probability distribution of the model parameters, given the observed data.
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