Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were “novel” SNVs that had not yet been identified in the global clinical-derived data as of 17^th June 2020 (the day after our last wastewater sampling date). However, between 17^th of June 2020 and 20^th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 很可能是由人畜共患病溢出事件引起的，并已导致全球大流行。公共卫生应对措施主要是通过对有症状的个人进行监测和接触者追踪，然后采取隔离和其他预防措施来减轻进一步传播。在这次大流行期间，还利用了基因组流行病学和废水流行病学（WBE）等非传统监测方法。基因组流行病学利用 SARS-CoV-2 基因组的高通量测序来了解本地和国际传播事件以及循环变异的多样性。WBE 使用废水来分析社区传播，因为众所周知 SARS-CoV-2 通过身体排泄物排出。由于有症状和无症状的个体都会产生废水输入，因此我们假设，与单独的临床测试和测序相比，所得的全人群排泄物汇总样本可以更全面地了解社区中传播的 SARS-CoV-2 基因组多样性。在这项研究中，我们分析了来自美国 11 个州的 91 个废水样本，其中大部分样本来自美国亚利桑那州马里科帕县。为了评估人群规模的病毒多样性，我们对 52 个样本的数据进行了单核苷酸变异 (SNV) 分析，这些样本的序列读取的 SARS-CoV-2 基因组覆盖率超过 90%，并将这些 SNV 与那些样本进行了比较。在临床患者的基因组测序中检测到。我们确定了 7973 个 SNV，^{2020 年6}月（我们上次废水采样日期的第二天）。然而，2020年6月17^{日至20日期间}2020 年 11 月，近一半的新型 SNV 已在临床衍生数据中检测到。利用每个样本中存在的 SNV 组合，我们确定了该样本中存在的更可能的谱系，并将它们与采样日期之前在北美观察到的谱系进行比较。废水衍生的 SARS-CoV-2 序列数据表明，样本群落中循环的谱系比临床衍生数据中显示的谱系要多。主坐标分析根据测序样本内的遗传变异确定了种群结构的模式，具有与多样性增加相关的明显趋势，这可能是由于相对于采样日期感染个体的数量较多。