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英国医疗卫生和社区检测中 SARS-CoV-2 感染的检出率。

Ascertainment rate of SARS-CoV-2 infections from healthcare and community testing in the UK.

机构信息

Royal (Dick) School of Veterinary Studies and the Roslin Institute, University of Edinburgh, Midlothian, UK.

Royal (Dick) School of Veterinary Studies and the Roslin Institute, University of Edinburgh, Midlothian, UK; Unit Veterinary Public Health and Epidemiology, University of Veterinary Medicine, Vienna, Austria; Complexity Science Hub Vienna, Austria.

出版信息

J Theor Biol. 2023 Feb 7;558:111333. doi: 10.1016/j.jtbi.2022.111333. Epub 2022 Nov 5.

Abstract

The proportion of SARS-CoV-2 infections ascertained through healthcare and community testing is generally unknown and expected to vary depending on natural factors and changes in test-seeking behaviour. Here we use population surveillance data and reported daily case numbers in the United Kingdom to estimate the rate of case ascertainment. We mathematically describe the relationship between the ascertainment rate, the daily number of reported cases, population prevalence, and the sensitivity of PCR and Lateral Flow tests as a function time since exposure. Applying this model to the data, we estimate that 20%-40% of SARS-CoV-2 infections in the UK were ascertained with a positive test with results varying by time and region. Cases of the Alpha variant were ascertained at a higher rate than the wild type variants circulating in the early pandemic, and higher again for the Delta variant and Omicron BA.1 sub-lineage, but lower for the BA.2 sub-lineage. Case ascertainment was higher in adults than in children. We further estimate the daily number of infections and compare this to mortality data to estimate that the infection fatality rate increased by a factor of 3 during the period dominated by the Alpha variant, and declined in line with the distribution of vaccines. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

摘要

通过医疗保健和社区检测确定的 SARS-CoV-2 感染比例通常是未知的,预计会因自然因素和检测寻求行为的变化而有所不同。在这里,我们使用人群监测数据和英国报告的每日病例数来估计病例检出率。我们将检出率、每日报告病例数、人群流行率以及 PCR 和侧向流动测试的敏感性之间的关系用数学方法描述为暴露后时间的函数。将该模型应用于数据,我们估计英国 20%-40%的 SARS-CoV-2 感染通过阳性检测得到确定,结果因时间和地区而异。与大流行早期流行的野生型变异相比,Alpha 变体的病例检出率更高,Delta 变体和 Omicron BA.1 亚系更高,而 BA.2 亚系则更低。成人的病例检出率高于儿童。我们进一步估计了每日感染人数,并将其与死亡率数据进行比较,估计在 Alpha 变体主导的时期,感染病死率增加了 3 倍,并随着疫苗的分布而下降。本文是作为“建模 COVID-19 和为未来大流行做准备”主题特刊的一部分提交的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e7f/9636607/3fdf08e541e3/gr1_lrg.jpg

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