新冠肺炎疫情检测准确性与有效防控——以新加坡为例

Guang Cheng, S. Y. Gao, Yancheng Yuan, Chenxiao Zhang, Zhichao Zheng
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引用次数: 0

摘要

本研究考察了在检测能力有限和无限两种情况下,2019冠状病毒病(COVID-19)检测准确性(即灵敏度和特异性)对疫情发展的影响。我们扩展了经典的易感-暴露-感染-恢复模型,以纳入测试准确性,并比较了不同敏感性和特异性下大流行的进展。我们发现,只有具备足够的检测能力,高灵敏度检测才能有效减少感染总数。然而,由于检测能力有限,交叉感染率较高,当敏感性超过一定阈值时,感染病例总数可能会增加。尽管有可能采用灵敏度更高的检测方法来识别更多的感染者,但出现了更多的假阳性病例,这浪费了有限的检测能力,减缓了对感染病例的发现。我们的研究结果表明,仅提高检测灵敏度并不总能有效地控制大流行,这表明政策制定者在设计COVID-19等传染病的控制措施时,特别是在检测能力有限的情况下,应在高灵敏度和高假阳性率之间取得平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Test Accuracy and Effective Control of the COVID-19 Pandemic: A Case Study in Singapore
This study examines the impact of coronavirus disease 2019 (COVID-19) test accuracy (i.e., sensitivity and specificity) on the progression of the pandemic under two scenarios of limited and unlimited test capacity. We extend the classic susceptible– exposed–infectious–recovered model to incorporate test accuracy and compare the progression of the pandemic under various sensitivities and specificities. We find that high-sensitivity tests effectively reduce the total number of infections only with sufficient testing capacity. Nevertheless, with limited test capacity and a relatively high cross-infection rate, the total number of infected cases may increase when sensitivity is above a certain threshold. Despite the potential for higher sensitivity tests to identify more infected individuals, more false positive cases occur, which wastes limited testing capacity, slowing down the detection of infected cases. Our findings reveal that improving test sensitivity alone does not always lead to effective pandemic control, indicating that policymakers should balance the trade-off between high sensitivity and high false positive rates when designing containment measures for infectious diseases, such as COVID-19, particularly when navigating limited test capacity.
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