Nowcasting the 2022 mpox outbreak in England.

IF 4.3 2区 生物学 PLoS Computational Biology Pub Date : 2023-09-18 eCollection Date: 2023-09-01 DOI:10.1371/journal.pcbi.1011463
Christopher E Overton, Sam Abbott, Rachel Christie, Fergus Cumming, Julie Day, Owen Jones, Rob Paton, Charlie Turner, Thomas Ward
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Abstract

In May 2022, a cluster of mpox cases were detected in the UK that could not be traced to recent travel history from an endemic region. Over the coming months, the outbreak grew, with over 3000 total cases reported in the UK, and similar outbreaks occurring worldwide. These outbreaks appeared linked to sexual contact networks between gay, bisexual and other men who have sex with men. Following the COVID-19 pandemic, local health systems were strained, and therefore effective surveillance for mpox was essential for managing public health policy. However, the mpox outbreak in the UK was characterised by substantial delays in the reporting of the symptom onset date and specimen collection date for confirmed positive cases. These delays led to substantial backfilling in the epidemic curve, making it challenging to interpret the epidemic trajectory in real-time. Many nowcasting models exist to tackle this challenge in epidemiological data, but these lacked sufficient flexibility. We have developed a nowcasting model using generalised additive models that makes novel use of individual-level patient data to correct the mpox epidemic curve in England. The aim of this model is to correct for backfilling in the epidemic curve and provide real-time characteristics of the state of the epidemic, including the real-time growth rate. This model benefited from close collaboration with individuals involved in collecting and processing the data, enabling temporal changes in the reporting structure to be built into the model, which improved the robustness of the nowcasts generated. The resulting model accurately captured the true shape of the epidemic curve in real time.

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现在预测2022年猴痘在英格兰的爆发。
2022年5月,在英国发现了一组猴痘病例,这些病例无法追溯到流行地区的近期旅行史。在接下来的几个月里,疫情加剧,英国报告的总病例超过3000例,类似的疫情也在全球范围内发生。这些疫情似乎与同性恋、双性恋和其他与男性发生性关系的男性之间的性接触网络有关。新冠肺炎大流行后,当地卫生系统紧张,因此对猴痘的有效监测对于管理公共卫生政策至关重要。然而,英国猴痘疫情的特点是,确诊阳性病例的症状出现日期和样本采集日期的报告大幅延迟。这些延迟导致了疫情曲线的大幅回填,使得实时解释疫情轨迹具有挑战性。目前存在许多模型来应对流行病学数据中的这一挑战,但这些模型缺乏足够的灵活性。我们使用广义加性模型开发了一个即时预报模型,该模型新颖地利用了个体水平的患者数据来校正英格兰的猴痘流行病曲线。该模型的目的是校正流行病曲线中的回填,并提供流行病状态的实时特征,包括实时增长率。该模型得益于与参与收集和处理数据的个人的密切合作,使报告结构的时间变化能够纳入模型,从而提高了生成的即时预报的稳健性。由此产生的模型实时准确地捕捉到了流行病曲线的真实形状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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