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      Detection of SARS-CoV-2 in wastewater as an earlier predictor of COVID-19 epidemic peaks in Venezuela

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          Abstract

          Wastewater-based epidemiological surveillance has proven to be a useful and cost-effective tool for detecting COVID-19 outbreaks. Here, our objective was to evaluate its potential as an early warning system in Venezuela by detecting SARS-CoV-2 RNA in wastewater and its correlation with reported cases of COVID-19. Viral RNA was concentrated from wastewater collected at various sites in Caracas (northern Venezuela), from September 2021 to July 2023, using the polyethylene glycol (PEG) precipitation method. Viral quantification was performed by RT-qPCR targeting the N1 and ORF1ab genes. A significant association ( p < 0.05) was found between viral load in wastewater and reported cases of COVID-19 up to six days after sampling. During the whole study, two populated areas of the city were persistent hotspots of viral infection. The L452R mutation, suggestive of the presence of the Delta variant, was identified in the only sample where a complete genomic sequence could be obtained. Significant differences ( p < 0.05) between the physicochemical conditions of the wastewater samples positive and negative for the virus were found. Our results support proof of concept that wastewater surveillance can serve as an early warning system for SARS-CoV-2 outbreaks, complementing public health surveillance in those regions where COVID-19 is currently underreported.

          Supplementary Information

          The online version contains supplementary material available at 10.1038/s41598-024-78982-3.

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              UFBoot2: Improving the Ultrafast Bootstrap Approximation

              Abstract The standard bootstrap (SBS), despite being computationally intensive, is widely used in maximum likelihood phylogenetic analyses. We recently proposed the ultrafast bootstrap approximation (UFBoot) to reduce computing time while achieving more unbiased branch supports than SBS under mild model violations. UFBoot has been steadily adopted as an efficient alternative to SBS and other bootstrap approaches. Here, we present UFBoot2, which substantially accelerates UFBoot and reduces the risk of overestimating branch supports due to polytomies or severe model violations. Additionally, UFBoot2 provides suitable bootstrap resampling strategies for phylogenomic data. UFBoot2 is 778 times (median) faster than SBS and 8.4 times (median) faster than RAxML rapid bootstrap on tested data sets. UFBoot2 is implemented in the IQ-TREE software package version 1.6 and freely available at http://www.iqtree.org.
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                Author and article information

                Contributors
                alejandra.zamora@gmail.com , alejandra.zamora@ucv.ve
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 November 2024
                8 November 2024
                2024
                : 14
                : 27294
                Affiliations
                [1 ]Laboratorio de Ecología de Microorganismos, Centro de Ecología Aplicada, Instituto de Zoología y Ecología Tropical, Facultad de Ciencias, Universidad Central de Venezuela (UCV), ( https://ror.org/05kacnm89) Caracas, Venezuela
                [2 ]Laboratorio de Virología Molecular, Centro de Microbiología y Biología Celular, Instituto Venezolano de Investigaciones Científicas (IVIC), ( https://ror.org/02ntheh91) Altos de Pipe, Miranda Venezuela
                [3 ]Centro de Ecología y Evolución, Instituto de Zoología y Ecología Tropical, Facultad de Ciencias, Universidad Central de Venezuela (UCV), ( https://ror.org/05kacnm89) Caracas, Venezuela
                Article
                78982
                10.1038/s41598-024-78982-3
                11549330
                7b5956bd-85ed-4bc8-b717-31e7bbfcd9ea
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                : 3 June 2024
                : 5 November 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100013696, Fondo Nacional de Ciencia y Tecnología;
                Award ID: 20220PGP62
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                wastewater,sars-cov-2,covid-19,early warning,epidemiology,venezuela,molecular biology,environmental microbiology,infectious-disease diagnostics,virology,ecology,ecological epidemiology,microbial ecology

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