Adaptive vaccination may be needed to extirpate COVID-19: Results from a runtime-alterable strain-drift and waning-immunity model

Getz, W. M.; Salter, R.; Vissat, L. L.; Koopman, J. S.; Simon, C. P.

We developed an elaborated susceptible-infected-recovered (SIR) individual-based model (IBM) with pathogen strain drift, waning and cross immunity, implemented as a novel Java Runtime-Alterable-Model Platform (J-RAMP). This platform allows parameter values, process formulations, and scriptable runtime drivers to be easily added at the start of simulation. It includes facility for integration into the R statistical and other data analysis platforms. We selected a set of parameter values and process descriptions relevant to the current COVID-19 pandemic. These include pathogen-specific shedding, environmental persistence, host transmission and mortality, within-host pathogen mutation and replication, adaptive social distancing, and time dependent vaccine rate and strain valency specifications. Our simulations illustrate that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible strains. Our study highlights the need for adaptive vaccination rollouts, which depend on reliable real-time monitoring and surveillance of strain proliferation and reinfection data needed to ensure that vaccines target emerging strains and constrain escape mutations. Together with such data, our platform has the potential to inform the design of vaccination programs that extirpate rather than exacerbate local outbreaks. Finally, our RAMP concept promotes the development of highly flexible models that can be easily shared among researchers and policymakers not only addressing healthcare crises, but other types of environmental crises as well.