The EpiFusion Analysis Framework - Software tool for joint phylodynamic and epidemiological outbreak analysis - version 1

Aug 28, 2026

Uploaded by Paura

Epidemiology and viral phylodynamics share disease control goals but differ in concepts, methods, and data, creating both complementary strengths and distinct limitations. EpiFusion was introduced as a framework for joint inference of outbreak characteristics using phylogenetic and case incidence data with particle filtering, enabling estimation of effective reproduction numbers. This article provides analysis vignettes using the EpiFusionUtilities R package and a Java implementation, including an added option to input a posterior distribution over phylogenetic trees. The examples support usability, reproducible workflows, and open research.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages32

Reading Time1 h 21 min

AccessFree to download

Introduction

EpiFusion Analysis Framework overview

Software components and workflow

Data inputs and posterior phylogenetic trees

SOFTWARE TOOL ARTICLE The EpiFusion Analysis Framework for joint phylodynamic and epidemiological analysis of outbreak characteristics [version 1; peer review: 2 approved, 1 approved with reservations] Ciara Judge 1-3, Oliver Brady 1,2, Sarah Hill3 1 Department of Infectious Disease Epidemiology and Dynamics, London School of Hygiene and Tropical Medicine Faculty of Epidemiology and Population Health, London, England, UK 2Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK 3 Department of Pathobiology and Population Sciences, The Royal Veterinary College, Hatfield, England, UK v1 First published: 28 Mar 2025, 14:345 [https://doi.org/10.12688/f1000research.162719.1](https://doi.org/10.12688/f1000research.162719.1) [Latest published:](Latest published: 28 Mar 2025)[ 28 Mar 2025](Latest published: 28 Mar 2025), 14:345 [https://doi.org/10.12688/f1000research.162719.1](https://doi.org/10.12688/f1000research.162719.1) Abstract The fields of epidemiology and viral phylodynamics share the ultimate goal of disease control, but concepts, methodologies and data employed by each differ in ways that confer complementary strengthsand different areas of weakness. We recently introduced EpiFusion, a model for joint inference of outbreak characteristics using phylogenetic and case incidence data via particle filtering and demonstrated its usage to infer the effective reproduction number of simulated and real outbreaks. Here we provide a series of vignettes demonstrating data analysis using the EpiFusion Analysis Framework, consisting of the R package EpiFusionUtilities and the Java program in which the model is implemented, including an example using a new feature incorporated since EpiFusion’s last description: the option to provide a phylogenetic tree posterior as the phylogenetic data input to the program. By outlining these examples, we aim to improve the usability of our model, and promote workflow reproducibility and open research. Keywords research software, phylodynamics, epidemiology, joint inference, effective reproduction number, infectious disease, modelling, R, java, particle filtering This article is included in the Bioinformatics gateway. Open Peer Review | Approval Status | | | | --- | --- | --- | | 1 | 2 | 3 | | version 1
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28 Mar 2025 | | | 1. Vijaykrishna Dhanasekaran, The University of Hong Kong, Hong Kong, Hong Kong Ruopeng Xie, The University of Hong Kong, Hong Kong, Hong Kong 2. Claire Guinat , Interactions Hôtes-Agents Pathogènes (IHAP), Université de Toulouse, INRAE, Toulouse, France 3. Leo A Featherstone, The University of Melbourne, Melbourne, Australia Any reports and responses or comments on the article can be found at the end of the article. Corresponding author: Ciara Judge ([ciara.judge@lshtm.ac.uk](ciara.judge@lshtm.ac.uk)) Author roles: Judge C: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing; Brady O: Conceptualization, Methodology, Project Administration, Supervision, Writing – Review & Editing; Hill S: Conceptualization, Methodology, Project Administration, Supervision, Writing – Review & Editing Competing interests: No competing interests were disclosed. Grant information: CJ was supported by a Bloomsbury Colleges PhD Studentship and a National University of Ireland Denis Phelan Scholarship. OJB was supported by a UK Medical Research Council Career Development Award (MR/V031112/1) . SCH was supported by a Sir Henry Wellcome Postdoctoral Fellowship from the Wellcome Trust (220414/Z/20/Z) [[https://welcome.org/](https://welcome.org/)]. For the purpose of open access, the authors have applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The

FAQs

What problem does the EpiFusion Analysis Framework target?

It enables joint inference of outbreak characteristics by combining phylogenetic information with case incidence data to support epidemiological understanding and disease control goals.

What tools are included in the framework?

The framework consists of a Java command-line implementation of the EpiFusion model and the EpiFusionUtilities R package for data and output processing.

What new data input option is demonstrated in this version?

An option is presented to provide a phylogenetic tree posterior as the phylogenetic data input to the program.

Aug 28, 2026

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