Arthur Menezes
PhD student at Princeton University
The CEIRR CMC holds bi-monthly research tutorials that feature leading researchers who develop state-of-the-art computational methods to better understand respiratory viruses. These events are designed to facilitate in-depth discussions and provide ample opportunity for questions from the audience, with each tutorial lasting 1 hour and 30 minutes.
After you register, click on the Eventbrite event page for a zoom link.
Abstract
serosim is an open-source R package designed to aid inference from serological studies, by simulating data arising from user-specified vaccine and antibody kinetics processes using a random effects model. Serological data are used to assess population immunity by directly measuring individuals’ antibody titers. They uncover locations and/or populations which are susceptible and provide evidence of past infection or vaccination to help inform public health measures and surveillance. Both serological data and new analytical techniques used to interpret them are increasingly widespread. This creates a need for tools to simulate serological studies and the processes underlying observed titer values, as this will enable researchers to identify best practices for serological study design, and provide a standardized framework to evaluate the performance of different inference methods. serosim allows users to specify and adjust model inputs representing underlying processes responsible for generating the observed titer values like time-varying patterns of infection and vaccination, population demography, immunity and antibody kinetics, and serological sampling design in order to best represent the population and disease system(s) of interest. This package will be useful for planning sampling design of future serological studies, understanding determinants of observed serological data, and validating the accuracy and power of new statistical methods.
Note: CEIRR CMC events are open only to CEIRR participants. The meeting and discussion are confidential.