Wastewater-based epidemiology to predict emerging new SARS-CoV-2 variants

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In a recent study posted to the medRxiv* preprint server researchers established and validated a strong approach for deducing public health-relevant epidemiological metrics, like relative variant abundance and variant-specific reproduction numbers, from wastewater (WW)-derived deep sequenced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes in the context of a national-scale wastewater-based epidemiology (WBE) initiative.

Study: National-scale surveillance of emerging SARS-CoV-2 variants in wastewater. Image Credit: CKA/ShutterstockStudy: National-scale surveillance of emerging SARS-CoV-2 variants in wastewater. Image Credit: CKA/Shutterstock

SARS-CoV-2 surveillance is critical to discover variants with different epidemiological features. Individual instances can be sequenced using WBE, which is unbiased and complimentary. National WBE surveillance programs, on the other hand, have not been widely deployed, and data analysis remains difficult.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

About the study

In this investigation, samples from selected wastewater treatment plants (WWTP) across Austria were collected between December 1, 2020, to September 15, 2021. The amount of the SARS-CoV-2 genome was measured by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in all samples, with internal spike-in controls used to calculate absolute copy number per volume.

Three distinct laboratories were used to collect wastewater, pre-process it, and perform quantitative screening. Amplicon-based whole genome deep sequencing was used to examine a total of 2,093 representative samples from 95 different WWTPs across Austria. A PCR amplicon-based deep sequencing workflow was used to analyze the obtained sequencing data. The researchers aimed to create a reliable and error-tolerant approach for detecting and quantifying various viral variants, which they called VaQuERo (Variant Quantification in Sewage designed for Robustness).

Discussion and conclusion

The researchers showed that the recently developed VaQuERo method can reliably deduce relative viral variant frequencies from WW. For the first time, it was demonstrated that WBE variant surveillance and case-based epidemiology accord qualitatively and quantitatively on a wide scale. The onset, length, and magnitude of variant prevalence are all quite consistent.

The comprehensive testing technique employed in Austria, as well as the longitudinal and transversal breadth of the disclosed and publicly published WW sequencing data, support the robustness of this finding. In terms of single-case detection sensitivity, the researchers highlighted that the accuracy of sequencing-based WBE is dependent on the prevalence and population size of the catchment area.

When there are too many positive instances in a catchment region, the signal of a single case becomes undetected in the total signal. A low prevalence rate causes a large dilution of virions in the WW, making it difficult to detect the overall signal. The researchers found that an absolute signal >2 cases or a relative signal >2.38 percent could be consistently detected with the specified relationship of (time-variable) prevalence and catchment size. As a result, the proposed method could be useful for surveying and identifying novel viral variants soon after their geographical introduction.

The method for sorting mutations based on their frequencies across multiple samples serves as a proof of concept and can be used in conjunction with the VaQuERo approach to identify emerging mutation constellations and investigate their temporal and spatial development patterns, which is based on the variant definition. Based on individual patient samples, a strong confirmation that the inferred constellations are truly unique haplotypes is still needed.

The findings show that WBE accurately reproduces epidemiological screening programs with a high spatiotemporal resolution, fewer samples, and less logistical effort. The virus aggregates in the WW represent the entire virus population, in contrast to the traditional method of aggregating consensus sequences of virus isolates from individual patients. This comprehensive view of the population presents opportunities and is likely to generate value for WBE.

In population genomics, it is well understood that a large sample rate benefits specific applications. The researchers aimed to integrate the two domains by using nucleotide diversity as a surrogate for introductions by tying the concept of nucleotide diversity to fundamental epidemiological metrics like prevalence and mobility. According to the findings, the absolute case number is imprinted in the observed nucleotide diversity. Mobility, on the other hand, had no influence. The dynamic distinctions in the appearance of Alpha and Delta viruses may hold the key to a better understanding and prediction of future virus population fluctuations.

In conclusion, this large-scale study highlights the utility of sequencing-based WW surveillance in the current SARS-CoV-2 pandemic, as well as its potential impact on improved worldwide surveillance of other infectious illnesses in the future.

We provide a framework to predict emerging variants de novo and infer variant-specific reproduction numbers from wastewater.”

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • May 11 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Saurabh Chaturvedi

Written by

Saurabh Chaturvedi

Saurabh Chaturvedi is a freelance writer from Jaipur, India. He is a gold medalist in Masters in Pharmaceutical Chemistry and has extensive experience in medical writing. He is passionate about reading and enjoys watching sci-fi movies.

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