SEIRmodeller

SEIRmodeller is a software package designed to simulate and analyze SEIR-type epidemiological models. It provides a modular framework for constructing compartmental models with Susceptible, Exposed, Infected, and Recovered populations and supports extensions with additional compartments such as hospitalized or vaccinated states. The project emphasizes flexibility for exploring theoretical scenarios as well as fitting models to real-world data.

Model construction is governed by user-defined parameters for transmission, incubation, and recovery, as well as time-varying modifiers such as interventions or seasonality. SEIRmodeller supports both deterministic simulations via differential equations and stochastic simulations, enabling a range of analyses from quick sensitivity checks to probabilistic forecasting.

Core components include model definitions, solver backends for ordinary differential equations or stochastic processes, data interfaces for importing incidence or prevalence data, and utilities for parameter estimation, calibration, and uncertainty quantification. Outputs commonly include time-series plots, summary statistics, and scenario comparison reports.

Typical uses include evaluating intervention strategies, estimating basic reproduction numbers, and comparing different public health responses. The tool is used in academic research, public health planning, and educational settings to illustrate how changes in contact rates or delays influence outbreak dynamics.

Limitations include assumptions of homogeneous mixing and potential identifiability challenges for some parameters. Results depend on data quality and model specification. The project aims to be transparent and interoperable, with emphasis on reproducibility and extensibility.