利用捕获蚊虫病毒载量追踪西尼罗病毒（West Nile virus）传播动态
Tracking West Nile virus dynamics using viral loads from trapped mosquitoes
一项基于捕获蚊虫池 Ct 值的多尺度模型分析显示，PCR 阳性蚊虫中相当比例可能不具传染性，仅用二值化数据会丢失与传播风险相关的病毒载量信息。研究分析了回顾性蚊虫监测的混合池 Ct 值，发现其变异无法仅由实验室因素解释，据此构建了连接混合池 Ct 值、蚊虫与鸟类宿主体内异质性病毒动力学及季节性传播的多尺度模型。模型提示阳性池 Ct 值反映的是潜在具传染性与非传染性蚊虫的混合。研究者进一步提出仅用混合池 Ct 值区分传染性与非传染性流行率的方法，总体流行率估计与标准二值化方法相当，且在高流行率下标准方法失效时仍保持准确。
来源：eLife · doi.org
Mosquito-borne virus transmission is increasing globally. Due to a lack of effective vaccines or targeted treatments, mitigation relies on reducing human exposure to infectious mosquitoes. Entomological surveillance provides estimates of human risk by quantifying the prevalence of arboviruses in mosquito populations. Testing of pooled mosquitoes via RT-qPCR is often used to infer infection prevalence; however, these data are often binarised and ignore semi-quantitative cycle threshold (Ct values) that may provide valuable information on virus kinetics, mosquito infectiousness, and ultimately human risk. West Nile virus (WNV) is a globally distributed arbovirus and endemic to the United States. In this study, we analysed pooled Ct values from retrospective mosquito surveillance and found substantial variation that could not be explained by laboratory factors alone. To understand how underlying viral load and epidemiological dynamics might explain this variation, we developed a multi-scale model linking pooled Ct values to heterogeneous within-host viral kinetics in mosquitoes and birds and seasonal transmission dynamics. Our modelling suggests that Ct values from positive pools might reflect a mixture of potentially infectious and non-infectious mosquitoes, indicating that a substantial proportion of PCR-positive mosquitoes might not contribute to transmission. We then developed a method to estimate mosquito infection prevalence using only pooled Ct values that distinguishes infectious from non-infectious prevalence. Estimates of overall prevalence were comparable to standard methods using binarised data and remained accurate at higher prevalences where standard approaches fail. Overall, these findings demonstrate that entomological viral load data reflect biologically meaningful variation in mosquito infection status that is lost through binarisation. Accounting for heterogeneous mosquito viral kinetics can improve interpretation of surveillance data and estimates of transmission risk, with implications for arbovirus surveillance beyond WNV.