The emergence and global dissemination of Severe Acute Respiratory Syndrome virus 2 (SARS-CoV-2) variants of concern (VOCs) have been described as the main factor driving the Coronavirus Disease 2019 pandemic. In Brazil, the Gamma variant dominated the epidemiological scenario during the first period of 2021. Many Brazilian regions detected the Delta variant after its first description and documented its spread. To monitor the introduction and spread of VOC Delta, we performed Polymerase Chain Reaction (PCR) genotyping and genome sequencing in ten regional sentinel units from June to October 2021 in the State of Minas Gerais (MG). We documented the introduction and spread of Delta, comprising 70 per cent of the cases 8 weeks later. Comparing the viral loads of the Gamma and Delta dominance periods, we provide additional evidence that the latter is more transmissible. The spread and dominance of Delta did not culminate in the increase in cases and deaths, suggesting that the vaccination may have restrained the epidemic growth. Analysis of 224 novel Delta genomes revealed that Rio de Janeiro state was the primary source for disseminating this variant in the state of MG. We present the establishment of Delta, providing evidence of its enhanced transmissibility and showing that this variant shift did not aggravate the epidemiological scenario in a high immunity setting.

Genetic variants of SARS-CoV-2 have been emerging and circulating in many places across the world. Rapid detection of these variants is essential since their dissemination can impact transmission rates, diagnostic procedures, disease severity, response to vaccines or patient management. Sanger sequencing has been used as the preferred approach for variant detection among circulating human immunodeficiency and measles virus genotypes. Using primers to amplify a fragment of the SARS-CoV-2 genome encoding part of the Spike protein, we showed that Sanger sequencing allowed us to rapidly detect the introduction and spread of three distinct SARS-CoV-2 variants in two major Brazilian cities. In both cities, after the predominance of variants closely related to the virus first identified in China, the emergence of the P.2 variant was quickly followed by the detection of the P1 variant, which became dominant in less than one month after it was first detected.

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) to detect SARS-CoV-2 RNA is an essential test to monitor the occurrence of COVID-19. A methodology is proposed for the determination of maximum pool size and adjustments of cut-off values of cycle threshold ($C_t$ in RT-qPCR pool testing, to compensate for the dilution caused by pooling. The trade-off between pool size and test sensitivity is stated explicitly. The procedure was designed to ensure that samples that would be detectable in individual testing remain detectable in pool testing. The proposed relaxation in cut-off is dependent on the pool size, allowing a relatively tight correction to avoid loss of detection of positive samples. The methodology was evaluated in a study of pool testing of adults attending a public emergency care unit, reference for COVID-19 in Belo Horizonte, Brazil, and presenting flu-like symptoms. Even samples on the edge of detectability in individual testing were detected correctly. The proposed procedure enhances the consistency of RT-qPCR pool testing by enforcing that the scales of detectability in pool processing and in individual sample processing are compatible. This may enhance the contribution of pool testing to large-scale testing for COVID-19.

The pool testing technique optimizes the number of tests performed and reduces the delivery time of results, which is an interesting strategy for the health crisis caused by the COVID-19 pandemic. This integrative review investigated studies in which pool testing was carried out for epidemiological or screening purposes to analyze its clinical or cost effectiveness and assessed the applicability of this method in high-, middle-, and low-income countries. This integrative review used primary studies published in the MEDLINE, EMBASE, Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), and Cochrane Library databases. A total of 435 studies were identified: 35.3% were carried out in Asia, 29.4% in Europe, 29.4% in North America, and 5.9% in Oceania. This review suggests that pool testing in the general population may be a useful surveillance strategy to detect new variants of SARS-CoV-2 and to evaluate the period of immunogenicity and global immunity from vaccines.

Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk and enhance clinical management. Optimal efficacy of COVID-19 antiviral medications relies on early administration within the initial 5 d of symptoms, assisting high-risk patients in avoiding hospitalization and improving survival chances. The complete blood count (CBC) can be an efficient and affordable option to find biomarkers that predict the COVID-19 prognosis due to infection-induced alterations in various blood parameters. This study aimed to associate hematological parameters with different COVID-19 clinical forms and utilizes them as disease outcome predictors. We performed a CBC in blood samples from 297 individuals with COVID-19 from Belo Horizonte, Brazil. Statistical analysis, as well as ROC Curves and machine learning Decision Tree algorithms were used to identify correlations, and their accuracy, between blood parameters and disease severity. In the initial 4 d of infection, traditional hematological COVID-19 alterations, such as lymphopenia, were not yet apparent. However, the monocyte percentage and granulocyte-to-lymphocyte ratio (GLR) proved to be reliable predictors for hospitalization, even in cases where patients exhibited mild symptoms that later progressed to hospitalization. Thus, our findings demonstrate that COVID-19 patients with monocyte percentages lower than 7.7% and a GLR higher than 8.75 are assigned to the hospitalized group with a precision of 86%. This suggests that these variables can serve as important biomarkers in predicting disease outcomes and could be used to differentiate patients at hospital admission for managing therapeutic interventions, including early antiviral administration. Moreover, they are simple parameters that can be useful in minimally equipped health care units.