Broadwick: a framework for computational epidemiology

O'Hare, A., Lycett, S. , Doherty, T., Salvador, L. and Kao, R. (2016) Broadwick: a framework for computational epidemiology. BMC Bioinformatics, 17, 65. (doi: 10.1186/s12859-016-0903-2) (PMID:26846686) (PMCID:PMC4743398)

Abstract

Motivation: Modelling disease outbreaks often involves incorporating the wealth of data that is gathered during modern outbreaks into complex mathematical or computational models of disease transmission. Incorporating this data into simple compartmental models is often difficult so complex computational models are required. In this paper we introduce a new framework written in Java for building and running epidemiological models that efficiently handles epidemiological data and reduces much of the boilerplate code that often accompanies these types of models. Results: Broadwick version 1.1 consists of 5,289 lines of Java source code (72 classes and 20 top-level packages, not including examples and unit test code) providing packages for stochastic simulations, parameter inference using Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods. Each algorithm used is fully customisable with sensible defaults (e.g. the MCMC algorithm uses a Gaussian random walk for the Markov Chain and a Metropolis-Hastings algorithm as the rejection algorithm) but these can be easily overridden by custom algorithms as required. Availability: The source code is object-oriented, modular in design and freely available at https://github.com/EPICScotland/Broadwick under the Apache License, Version 2.0 license.

• Item Type: Articles
• Additional Information: This work was funded by the Scottish Government Rural and Environment Science and Analytical Services Division, as part of the Centre of Expertise in Animal Disease Outbreaks (EPIC) and EPIC sub-contract 55987_4.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Salvador, Dr Liliana and O'Hare, Dr Anthony and Doherty, Mr Thomas and Kao, Professor Rowland and Lycett, Dr Samantha
• Authors: O'Hare, A., Lycett, S., Doherty, T., Salvador, L., and Kao, R.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: BMC Bioinformatics
• Publisher: Biomed Central
• ISSN: 1471-2105
• Copyright Holders: Copyright © 2016 O’Hare et al.
• First Published: First published in BMC Bioinformatics 17:65
• Publisher Policy: Reproduced under a Creative Commons License