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新冠时代传染病模型的可重复性。

Reproducibility of COVID-era infectious disease models.

机构信息

Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia.

Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia; College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Australia; Commonwealth Scientific Industrial Research Organisation (CSIRO), Townsville, Australia.

出版信息

Epidemics. 2024 Mar;46:100743. doi: 10.1016/j.epidem.2024.100743. Epub 2024 Jan 23.

Abstract

Infectious disease modelling has been prominent throughout the COVID-19 pandemic, helping to understand the virus' transmission dynamics and inform response policies. Given their potential importance and translational impact, we evaluated the computational reproducibility of infectious disease modelling articles from the COVID era. We found that four out of 100 randomly sampled studies released between January 2020 and August 2022 could be completely computationally reproduced using the resources provided (e.g., code, data, instructions) whilst a further eight were partially reproducible. For the 100 most highly cited articles from the same period we found that 11 were completely reproducible with a further 22 partially reproducible. Reflecting on our experience, we discuss common issues affecting computational reproducibility and how these might be addressed.

摘要

传染病建模在整个 COVID-19 大流行期间一直很突出,有助于了解病毒的传播动态并为应对政策提供信息。鉴于它们的潜在重要性和转化影响,我们评估了 COVID 时代传染病建模文章的计算可重复性。我们发现,在 2020 年 1 月至 2022 年 8 月期间随机抽样的 100 项研究中,有 4 项可以使用提供的资源(例如代码、数据、说明)完全进行计算重现,而另外 8 项则部分可重现。对于同一时期被引用最多的 100 篇文章,我们发现其中 11 篇可以完全重现,另外 22 篇部分重现。在反思我们的经验时,我们讨论了影响计算可重复性的常见问题以及如何解决这些问题。

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