SEIRS+ Model Framework

This package implements models of generalized SEIRS infectious disease dynamics with extensions that allow us to study the effect of social contact network structures, heterogeneities, stochasticity, and interventions, such as social distancing, testing, contact tracing, and isolation.

Latest Major Release: 1.0 (9 Aug 2020)

Version 1.0 of the seirsplus package as well as the code and documentation presented in this repository represent COVID modeling frameworks developed in 2020 and early 2021.

🔶 Upcoming Major Release: 2.0 (Feb 2022)

Ongoing modeling and code development with collaborators have advanced the SEIRS+ framework we use internally considerably since the last major package release.

A major Version 2.0 public release of the SEIRS+ framework package and documentation is planned for early February — watch this space! If you would like access to the Version 2.0 code or further information before this public release, please do not hesitate to reach out.

New Features in Version 2.0 include:

• Top-to-bottom redesign of package to make SEIRS+ a versatile framework not only for accessible rapid COVID modeling but also for network epidemiology research more broadly.
• Fully customizable compartment models for flexible implementation of any disease state model, and pre-configured compartment models for COVID-19 contexts and other common diseases.
• Features for tracking transmission chain lineages and infector/infectee characteristics.
• Expanded support for parameterizable implementations of testing, tracing, isolation, deisolation, and social distancing non-pharmaceutical intervention scenarios.
• Support for vaccination, including multiple vaccine types and multi-dose vaccine courses.
• Support for scenarios with emerging disease variants
• Run-time improvements (i.e., Gillespie tau leaping supported)
• Many other features
• Comprehensive testing suite for developers and contributors
• As always, emphasis on ease of use.

Overview

Full documentation of this package's models, code, use cases, examples, and more can be found on the wiki

Basic SEIRS Model	Extended SEIRS Model
Model Description	Model Description
SEIRSNetworkModel docs SEIRSModel docs	ExtSEIRSNetworkModel docs
Basic SEIRS Mean-field Model Demo Basic SEIRS Network Model Demo	Extended SEIRS Community TTI Demo Extended SEIRS Workplace TTI Demo

SEIRS Dynamics

The foundation of the models in this package is the classic SEIR model of infectious disease. The SEIR model is a standard compartmental model in which the population is divided into susceptible (S), exposed (E), infectious (I), and recovered (R) individuals. A susceptible member of the population becomes infected (exposed) when making a transmissive contact with an infectious individual and then progresses to the infectious and finally recovered states. In the SEIRS model, recovered individuals may become resusceptible some time after recovering (although re-susceptibility can be excluded if not applicable or desired).