RESUMO
The COVID-19 pandemic continues to impact health systems globally and robust surveillance is critical for pandemic control, however not all countries can sustain community surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but little is known about how river and informal sewage in low-income countries can be used for environmental surveillance of SARS-CoV-2. In Malawi, a country with limited community-based COVID-19 testing capacity, we explored the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020 - January 2022, we collected water from up to 112 river or informal sewage sites/month, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predated peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights wastewater can be used for detecting emerging waves, identifying variants of concern and function as an early warning system in settings with no formal sewage systems.
RESUMO
The world has moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but decision-makers require confidence that it can be applied to a national scale and is comparable to individual testing data. We analysed 19,911 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from >70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , Águas Residuárias , Vigilância Epidemiológica Baseada em Águas Residuárias , COVID-19/epidemiologia , Genômica , Inglaterra/epidemiologiaRESUMO
The COVID-19 pandemic has profoundly impacted health systems globally and robust surveillance has been critical for pandemic control, however not all countries can currently sustain community pathogen surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but less is known about the utility of water surveillance of pathogens in low-income countries. Here we show how wastewater surveillance of SAR-CoV-2 can be used to identify temporal changes and help determine circulating variants quickly. In Malawi, a country with limited community-based COVID-19 testing capacity, we explore the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020-May 2022, we collect water from up to 112 river or defunct wastewater treatment plant sites, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predate peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights how wastewater can be used to detect emerging waves, identify variants of concern, and provide an early warning system in settings with no formal sewage systems.
Assuntos
COVID-19 , Águas Residuárias , Humanos , Esgotos , SARS-CoV-2 , Teste para COVID-19 , Pandemias , Rios , COVID-19/diagnóstico , COVID-19/epidemiologia , Vigilância Epidemiológica Baseada em Águas Residuárias , ÁguaRESUMO
Wastewater-based epidemiology has been used extensively throughout the COVID-19 (coronavirus disease 19) pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public-health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants; yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants of concern (VOCs) (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15th and 18th December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers. Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.