The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

值得关注的 SARS-CoV-2 变体和感兴趣的变体的不断出现强调了对新变体进行早期检测和流行病学监测的必要性。我们对瑞士三个地点的 122 个废水样本进行了基因组测序，以监测 SARS-CoV-2 的 B.1.1.7（Alpha）、B.1.351（Beta）和 P.1（Gamma）变种在当地的传播情况。人口水平。我们设计了一种名为 COJAC（共现调整分析和调用）的生物信息学方法，该方法使用携带多个变体特异性特征突变的读取对作为低频变体的可靠指标。 COJAC 的应用显示，在临床样本中首次报告之前，在长达 13 天的时间里，在瑞士两个城市的废水中可以观察到 Alpha 变种的局部爆发。通过分析另外 1,339 个废水样本，我们进一步证实了 COJAC 能够及早检测出 Delta 变种的新出现变种。虽然单个废水样本的测序数据对于量化变异相对流行率的精度有限，但我们表明，重复和紧密啮合的纵向测序不仅可以稳健估计局部流行率，还可以稳健估计任何变异的传播适应性优势。我们的结论是，基因组测序和我们的计算分析可以更早地基于比临床样本少得多的样本，提供对废水样本中新出现变异的流行率和适应性的群体水平估计。我们的框架经常用于瑞士和英国的大型国家项目。