A runtime alterable epidemic model with genetic drift, waning immunity and vaccinations. Issue 184 (24th November 2021)

• Record Type: Journal Article
• Authors: Getz, Wayne M.; Salter, Richard; Luisa Vissat, Ludovica; Koopman, James S.; Simon, Carl P.
• Is Part Of: Journal of the Royal Society interface. Volume 18:Issue 184(2021)
• Publication Date: 2021-11-24
• Subjects: SEIR individual-based models -- escape mutations -- RAMPs -- SARS-CoV-2 -- pathogen variants -- vaccination; Physical sciences -- Research -- Periodicals; Life sciences -- Research -- Periodicals; Interdisciplinary research -- Periodicals; 570.5
• DOI: 10.1098/rsif.2021.0648
• Languages: English
• ISSNs: 1742-5689

Abstract

Abstract : We present methods for building a Java Runtime-Alterable-Model Platform (RAMP) of complex dynamical systems. We illustrate our methods by building a multivariant SEIR (epidemic) RAMP. Underlying our RAMP is an individual-based model that includes adaptive contact rates, pathogen genetic drift, waning and cross-immunity. Besides allowing parameter values, process descriptions and scriptable runtime drivers to be easily modified during simulations, our RAMP can used within R-Studio and other computational platforms. Process descriptions that can be runtime altered within our SEIR RAMP include pathogen variant-dependent host shedding, environmental persistence, host transmission and within-host pathogen mutation and replication. They also include adaptive social distancing and adaptive application of vaccination rates and variant-valency of vaccines. We present simulation results using parameter values and process descriptions relevant to the current COVID-19 pandemic. Our results suggest that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible variants, particularly if vaccine valencies are not adapted to deal with escape mutations. Our SEIR RAMP is designed for easy use by others. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared as stand-alone application programs.