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无症状 COVID-19 病例的人群水平中位循环阈值 (Ct) 值可预测未来病例的轨迹。

Population-level median cycle threshold (Ct) values for asymptomatic COVID-19 cases can predict the trajectory of future cases.

机构信息

Cancer Biology Lab, Institute of Microbiology and Molecular Genetics, University of the Punjab, Lahore, Pakistan.

Cancer Research Centre (CRC), University of the Punjab, Lahore, Pakistan.

出版信息

PLoS One. 2023 Mar 9;18(3):e0281899. doi: 10.1371/journal.pone.0281899. eCollection 2023.

Abstract

BACKGROUND

Recent studies indicate that the population-level SARS-CoV-2 cycle threshold (Ct) values can inform the trajectory of the pandemic. The presented study investigates the potential of Ct values in predicting the future of COVID-19 cases. We also determined whether the presence of symptoms could change the correlation between Ct values and future cases.

METHODS

We examined the individuals (n = 8660) that consulted different sample collection points of a private diagnostic center in Pakistan for COVID-19 testing between June 2020 and December 2021. The medical assistant collected clinical and demographic information. The nasopharyngeal swab specimens were taken from the study participants and real-time reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect SARS-CoV-2 in these samples.

RESULTS

We observed that median Ct values display significant temporal variations, which show an inverse relationship with future cases. The monthly overall median Ct values negatively correlated with the number of cases occurring one month after specimen collection (r = -0.588, p <0.05). When separately analyzed, Ct values for symptomatic cases displayed a weak negative correlation (r = -0.167, p<0.05), while Ct values from asymptomatic cases displayed a stronger negative correlation (r = -0.598, p<0.05) with the number of cases in the subsequent months. Predictive modeling using these Ct values closely forecasted the increase or decrease in the number of cases of the subsequent month.

CONCLUSIONS

Decreasing population-level median Ct values for asymptomatic COVID-19 cases appear to be a leading indicator for predicting future COVID-19 cases.

摘要

背景

最近的研究表明,人群水平的 SARS-CoV-2 循环阈值 (Ct) 值可以反映大流行的轨迹。本研究探讨了 Ct 值预测 COVID-19 病例未来情况的潜力。我们还确定了症状的存在是否会改变 Ct 值与未来病例之间的相关性。

方法

我们检查了 2020 年 6 月至 2021 年 12 月期间在巴基斯坦私人诊断中心不同样本采集点接受 COVID-19 检测的个体(n=8660)。医疗助理收集了临床和人口统计学信息。从研究参与者中采集鼻咽拭子标本,并使用实时逆转录聚合酶链反应 (RT-PCR) 检测这些样本中的 SARS-CoV-2。

结果

我们观察到中位数 Ct 值显示出显著的时间变化,与未来病例呈反比关系。每月总体中位数 Ct 值与标本采集后一个月发生的病例数呈负相关(r=-0.588,p<0.05)。单独分析时,有症状病例的 Ct 值显示出较弱的负相关(r=-0.167,p<0.05),而无症状病例的 Ct 值与随后几个月的病例数呈更强的负相关(r=-0.598,p<0.05)。使用这些 Ct 值进行的预测建模密切预测了随后一个月病例数的增加或减少。

结论

无症状 COVID-19 病例人群水平中位数 Ct 值的降低似乎是预测未来 COVID-19 病例的一个领先指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e920/9997994/27a09c0af7dc/pone.0281899.g001.jpg

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