Judge Ciara, Brady Oliver, Hill Sarah
Department of Infectious Disease Epidemiology and Dynamics, London School of Hygiene and Tropical Medicine Faculty of Epidemiology and Population Health, London, England, UK.
Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
F1000Res. 2025 Mar 28;14:345. doi: 10.12688/f1000research.162719.1. eCollection 2025.
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 strengths and 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.
流行病学和病毒系统动力学领域有着疾病控制的共同终极目标，但两者所采用的概念、方法和数据在某些方面存在差异，这些差异赋予了它们互补的优势和不同的弱点领域。我们最近推出了EpiFusion，这是一种通过粒子滤波利用系统发育和病例发病率数据联合推断疫情特征的模型，并展示了其用于推断模拟和实际疫情的有效繁殖数的用途。在这里，我们提供了一系列示例，展示了使用EpiFusion分析框架进行数据分析的过程，该框架由R包EpiFusionUtilities和实现该模型的Java程序组成，包括一个使用自上次描述EpiFusion以来新纳入的功能的示例：提供系统发育树后验作为程序系统发育数据输入的选项。通过概述这些示例，我们旨在提高我们模型的可用性，并促进工作流程的可重复性和开放研究。
