A runtime alterable epidemic model with genetic drift, waning immunity, and vaccinations

In this paper, 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 is easily integrated into other computational platforms, such as our illustrated example with R-Studio. Processes 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 do not adapt to escape mutations. Our SEIR RAMP is designed for easy-use by individuals and groups involved in formulating social-distancing and adaptive vaccination rollout policies. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared among researchers and policymakers as stand alone applications programs.