The SC-COSMO modeling framework enables modeling of the epidemiology of COVID-19 for diverse populations and geographies. At its core, it is an age-structured, multi-compartment susceptible-exposed-infected-recovered (AS-MC-SEIR) model implemented in the R programming language. The model incorporates realistic demography and patterns of contacts sufficient for transmission. The model also incorporates non-pharmaceutical interventions (NPIs) (e.g., “social distancing”) timing and effects on reductions in con
Full technical details of the SC-COSMO modeling framework are posted in the Resources section ; here, we provide a brief technical overview of its capabilities. Because the framework is intended to be used for modeling many different populations and geographies, it also includes the ability to easily load/parametrize population- and geography-specific inputs that are generally publicly available (e.g., the age-structure of a given county), methods to infer setting-specific inputs that may not be available (
The SC-COSMO team is a diverse group of faculty and graduate students.