Karr Jonathan, Malik-Sheriff Rahuman S, Osborne James, Gonzalez-Parra Gilberto, Forgoston Eric, Bowness Ruth, Liu Yaling, Thompson Robin, Garira Winston, Barhak Jacob, Rice John, Torres Marcella, Dobrovolny Hana M, Tang Tingting, Waites William, Glazier James A, Faeder James R, Kulesza Alexander
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, United Kingdom.
Front Syst Biol. 2022;2. doi: 10.3389/fsysb.2022.822606. Epub 2022 Mar 7.
During the COVID-19 pandemic, mathematical modeling of disease transmission has become a cornerstone of key state decisions. To advance the state-of-the-art host viral modeling to handle future pandemics, many scientists working on related issues assembled to discuss the topics. These discussions exposed the reproducibility crisis that leads to inability to reuse and integrate models. This document summarizes these discussions, presents difficulties, and mentions existing efforts towards future solutions that will allow future model utility and integration. We argue that without addressing these challenges, scientists will have diminished ability to build, disseminate, and implement high-impact multi-scale modeling that is needed to understand the health crises we face.
在新冠疫情期间，疾病传播的数学建模已成为关键国家决策的基石。为了推进最先进的宿主病毒建模以应对未来的大流行，许多从事相关问题研究的科学家齐聚一堂进行讨论。这些讨论揭示了导致模型无法重复使用和整合的可重复性危机。本文档总结了这些讨论，提出了困难，并提及了为实现未来解决方案所做的现有努力，这些努力将使未来的模型具有实用性和可整合性。我们认为，如果不应对这些挑战，科学家构建、传播和实施理解我们所面临的健康危机所需的高影响力多尺度建模的能力将会减弱。
