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    This paper aims to review the main sludge concentration methods used for SARS-CoV-2 detection in sewage sludge samples, discussing the main methods and sample volume related to increased viral load. In addition, we aim to evaluate the countries associated with increased positivity rates for SARS-CoV-2 in sludge samples. This systematic methodology was registered in PROSPERO and followed the PRISMA guidelines. The search was carried out in the SciELO, PubMed/MEDLINE, Lilacs, and Google Scholar databases in January-March 2022. Quantitative studies with conclusive results were included in this review. Concentration methods (polyethylene glycol (PEG), PEG + NaCl, gravity thickening, skimmed milk flocculation, ultrafiltration, filtration using charged filters, primary sedimentation, and anaerobic digestion), as well as detection methods (RTqPCR and reverse transcription droplet digital PCR assay) were evaluated in this review. The SPSS v23 software program was used for statistical analysis. PEG (with or without NaCl addition) and gravity thickening were the most used sludge concentration methods to detect SARS-CoV-2. The main method associated with increased viral load (>2,02 × 10^4 copies/mL) was PEG + NaCl (p < 0.05, Mann-Whitney test). The average positivity rate for SARS-CoV-2 in sludge samples was 61 %, and a correlation was found between the sludge volume and the viral load (ro 0.559, p = 0.03, Spearman correlation). The sludge volume may influence the SARS-CoV-2 load since the virus can adhere to solid particles in these samples. Other factors may be associated with SARS-CoV-2 load, including the methods used; especially PEG + NaCl may result in a high viral load detected in sludge, and may provide a suitable pH for SARS-CoV-2 recovery. Copyright © 2022 Elsevier B.V. All rights reserved.

    Citation

    Alice Barros Câmara, Júlia Bonfante, Marília Gueler da Penha, Sérvio Túlio Alves Cassini, Regina de Pinho Keller. Detecting SARS-CoV-2 in sludge samples: A systematic review. The Science of the total environment. 2022 Nov 09;859(Pt 1):160012

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    PMID: 36368397

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