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.
Highlights
Kermack and McKendrick pioneered the application of differential equations to modelling the dynamics of disease systems that included susceptible (S), infected/infectious (E/I) and recovered (R; we use V to include vaccinated) classes of individuals [1]
We propose a more general approach to specific classes of systems’ models, where the basic system structure is fixed, but implementation of some elements can be and safely altered so that optional implementations are presented at runtime. We call such a design runtime alterable-model platforms. (RAMPs); and here we present a Java Runtime-Alterable-Model Platform (RAMP) implementation of the M-SEIR described in the previous subsection
We provide in table 3 the per cent of susceptible individuals and per cent of deaths due to COVID-19 1 year after the day on which more than 10 cases of COVID-19 were recorded to occur in the USA, Italy and Czech Republic (extracted from data provided at Worldometer)
Summary
Kermack and McKendrick pioneered the application of differential equations to modelling the dynamics of disease systems that included susceptible (S), infected/infectious (E/I) and recovered (R; we use V to include vaccinated) classes of individuals [1]. Our M-SEIR RAMP is designed to be used by individuals either with no coding skills, or with minimal coding skills if they desire to modify some of the process descriptions incorporated into the supplied platform It is sufficiently detailed, to allow the user to incorporate either supplied or user-altered versions of the following processes: (i) pathogen variant-specific shedding [19], environmental persistence [20], within-host replication [21] and mortality rates [22]; (ii) immunological waning with variant cross-immunity [23,24]; (iii) pathogen variant drift during transmission and within-host replication [25]; (iv) an adaptive contact rate [26]; (v) a time-dependent, uni- or agent infectors i shedding rates zi persistence rates h major strain probability within-host agent mutation mh ¢ h and replication major rates lh ¢. That our results and subsequent investigations using our M-SEIR RAMP will provide the kinds of quantitative analyses that can help formulate highly effective local- or country-level vaccination programs that avoid some of the vaccination rollout pitfalls revealed by our analysis, as well as encourage the adoption of effective adaptive vaccination programs
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