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Front Med (Lausanne) ; 9: 806611, 2022.
Article in English | MEDLINE | ID: covidwho-1731797

ABSTRACT

BACKGROUND: P.1 lineage (Gamma) was first described in the State of Amazonas, northern Brazil, in the end of 2020, and has emerged as a very important variant of concern (VOC) of SARS-CoV-2 worldwide. P.1 has been linked to increased infectivity, higher mortality, and immune evasion, leading to reinfections and potentially reduced efficacy of vaccines and neutralizing antibodies. METHODS: The samples of 276 patients from the State of Amazonas were sent to a central referral laboratory for sequencing by gold standard techniques, through Illumina MiSeq platform. Both global and regional phylogenetic analyses of the successfully sequenced genomes were conducted through maximum likelihood method. Multiple alignments were obtained including previously obtained unique human SARS-CoV-2 sequences. The evolutionary histories of spike and non-structural proteins from ORF1a of northern genomes were described and their molecular evolution was analyzed for detection of positive (FUBAR, FEL, and MEME) and negative (FEL and SLAC) selective pressures. To further evaluate the possible pathways of evolution leading to the emergence of P.1, we performed specific analysis for copy-choice recombination events. A global phylogenomic analysis with subsampled P.1 and B.1.1.28 genomes was applied to evaluate the relationship among samples. RESULTS: Forty-four samples from the State of Amazonas were successfully sequenced and confirmed as P.1 (Gamma) lineage. In addition to previously described P.1 characteristic mutations, we find evidence of continuous diversification of SARS-CoV-2, as rare and previously unseen P.1 mutations were detected in spike and non-structural protein from ORF1a. No evidence of recombination was found. Several sites were demonstrated to be under positive and negative selection, with various mutations identified mostly in P.1 lineage. According to the Pango assignment, phylogenomic analyses indicate all samples as belonging to the P.1 lineage. CONCLUSION: P.1 has shown continuous evolution after its emergence. The lack of clear evidence for recombination and the positive selection demonstrated for several sites suggest that this lineage emergence resulted mainly from strong evolutionary forces and progressive accumulation of a favorable signature set of mutations.

2.
Pathogens ; 10(8)2021 Aug 05.
Article in English | MEDLINE | ID: covidwho-1341705

ABSTRACT

Almost a year after the COVID-19 pandemic had begun, new lineages (B.1.1.7, B.1.351, P.1, and B.1.617.2) associated with enhanced transmissibility, immunity evasion, and mortality were identified in the United Kingdom, South Africa, and Brazil. The previous most prevalent lineages in the state of Rio Grande do Sul (RS, Southern Brazil), B.1.1.28 and B.1.1.33, were rapidly replaced by P.1 and P.2, two B.1.1.28-derived lineages harboring the E484K mutation. To perform a genomic characterization from the metropolitan region of Porto Alegre, we sequenced viral samples to: (i) identify the prevalence of SARS-CoV-2 lineages in the region, the state, and bordering countries/regions; (ii) characterize the mutation spectra; (iii) hypothesize viral dispersal routes by using phylogenetic and phylogeographic approaches. We found that 96.4% of the samples belonged to the P.1 lineage and approximately 20% of them were assigned as the novel P.1.2, a P.1-derived sublineage harboring signature substitutions recently described in other Brazilian states and foreign countries. Moreover, sequences from this study were allocated in distinct branches of the P.1 phylogeny, suggesting multiple introductions in RS and placing this state as a potential diffusion core of P.1-derived clades and the emergence of P.1.2. It is uncertain whether the emergence of P.1.2 and other P.1 clades is related to clinical or epidemiological consequences. However, the clear signs of molecular diversity from the recently introduced P.1 warrant further genomic surveillance.

3.
Rev Med Virol ; 31(4): e2200, 2021 07.
Article in English | MEDLINE | ID: covidwho-956754

ABSTRACT

Population-based prevalence surveys of Covid-19 contribute to establish the burden of infection, the role of asymptomatic and mild infections in transmission, and allow more precise decisions about reopen policies. We performed a systematic review to evaluate qualitative aspects of these studies, assessing their reliability and compiling practices that can influence the methodological quality. We searched MEDLINE, EMBASE, bioRxiv and medRxiv, and included cross-sectional studies using molecular and/or serological tests to estimate the prevalence of Covid-19 in the general population. Survey quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. A correspondence analysis correlated methodological parameters of each study to identify patterns related to higher, intermediate and lower risks of bias. The available data described 37 surveys from 19 countries. The majority were from Europe and America, used antibody testing, and reached highly heterogeneous sample sizes and prevalence estimates. Minority communities were disproportionately affected by Covid-19. Important risk of bias was detected in four domains: sample size, data analysis with sufficient coverage, measurements in standard way and response rate. The correspondence analysis showed few consistent patterns for high risk of bias. Intermediate risk of bias was related to American and European studies, municipal and regional initiatives, blood samples and prevalence >1%. Low risk of bias was related to Asian studies, nationwide initiatives, reverse-transcriptase polymerase chain reaction tests and prevalence <1%. We identified methodological standards applied worldwide in Covid-19 prevalence surveys, which may assist researchers with the planning, execution and reporting of future population-based surveys.


Subject(s)
COVID-19/epidemiology , Population Surveillance , COVID-19/diagnosis , COVID-19 Testing/methods , Humans , Mass Screening/methods , Population Surveillance/methods , Prevalence
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