Rule-based epidemic models

• Main Authors: Cavaliere, M. (Author), Danos, V. (Author), Manheim, D. (Author), Panovska-Griffiths, J. (Author), Waites, W. (Author)
• Format: Article
• Language: English
• Published: Academic Press 2021
• Subjects: Article; biological model; Chemical master equation; communicable disease; computer simulation; contact examination; Contact Tracing; coronavirus disease 2019; disease simulation; disease spread; disease transmission; epidemic; Epidemics; Epidemiological modelling; epidemiology; hand washing; human; infectious disease; mathematical model; model test; Models, Biological; Models, Statistical; numerical model; reproducibility; rule based model; Rule-based modelling; semantics; statistical model; Stochastic simulation; stochasticity; vector borne disease; viral clearance
• Online Access: View Fulltext in Publisher

 Rule-based models generalise reaction-based models with reagents that have internal state and may be bound together to form complexes, as in chemistry. An important class of system that would be intractable if expressed as reactions or ordinary differential equations can be efficiently simulated when expressed as rules. In this paper we demonstrate the utility of the rule-based approach for epidemiological modelling presenting a suite of seven models illustrating the spread of infectious disease under different scenarios: wearing masks, infection via fomites and prevention by hand-washing, the concept of vector-borne diseases, testing and contact tracing interventions, disease propagation within motif-structured populations with shared environments such as schools, and superspreading events. Rule-based models allow to combine transparent modelling approach with scalability and compositionality and therefore can facilitate the study of aspects of infectious disease propagation in a richer context than would otherwise be feasible. © 2021 The Author(s)