Temporal spread and evolution of SARS-CoV-2 in the second pandemic wave in Brazil

A magnetic control enrichment technique combined with terahertz metamaterial biosensor for detecting SARS-CoV-2 spike protein

The highly contagious SARS-CoV-2 virus, responsible for the COVID-19 pandemic continues to pose significant challenges to public health. Developing new methods for early detection and diagnosis is crucial in combatting the disease, mitigating its impact and be prepared for future challenges in pandemic diseases. In this study, we propose a terahertz (THz) biosensing technology that capitalizes on the properties of THz metamaterial in conjunction with magnetic nanoparticles. This approach can accurately identify the SARS-CoV-2 spike protein by pinpointing its location on the THz resonance sources grooved surface. The magnetic nanoparticles are employed to selectively bind with target molecules, and migrate towards the THz metamaterial unit cell when exposed to an applied magnetic field. The presence of target molecules in to the metamaterial variation in the frequency, amplitude, and phase of the resonance response, thus enabling swift, accurate and sensitive detection. To assess the effectiveness of the proposed technique, we have conducted a comparative analysis between real samples on platforms controlled by magnetic manipulation and those without the control. It was confirmed that the proposed THz sensing method demonstrated a linear detection range spanning from 0.005 ng mL-1 to 1000 ng mL-1 with a detection limit of 0.002 ng mL-1. Furthermore, it exhibited a frequency shift of 24 GHz and a stability index of 95%. The THz biosensing technique may pave a new avenue in identifying and preempting the spread of potential pandemic diseases.

Associations of SARS-CoV-2 cycle threshold values with age, gender, sample collection setting, and pandemic period

Cycle threshold (Ct) values in COVID-19 reverse-transcription polymerase chain reaction (RT-PCR) tests estimate the viral load in biological samples. Studies have investigated variables associated with SARS-CoV-2 viral load, aiming to identify factors associated with higher transmissibility. Using the results from tests performed between May/2020-July/2022 obtained from the database of a referent hospital in Sao Paulo, Brazil, we investigated associations between Ct values and patient's age, gender, sample collection setting and pandemic period according to the predominant SARS-CoV-2 variant locally. We also examined variations in Ct values, COVID-19 incidence, mortality, and vaccination coverage over time. The study sample included 42,741 tests. Gender was not significantly associated with Ct values. Age, sample collection setting and the pandemic period were significantly associated with Ct values even after adjustment to the multivariable model. Results showed lower Ct values in older groups, during the Gamma and Delta periods, and in samples collected in emergency units; and higher Ct values in children under 10 years old, home-based tests, during the Omicron period. We found evidence of a linear trend in the association between age and Ct values, with Ct values decreasing as age increases. We found no clear temporal associations between Ct values and local indicators of COVID-19 incidence, mortality, or vaccination between February/2020-November/2022. Our findings suggest that SARS-CoV-2 Ct values, a proxy for viral load and transmissibility, can be influenced by demographic and epidemiological variables.

RT-LAMP Multicenter Study for SARS-CoV-2 Genome Molecular Detection in Brazilian Swab and Saliva Samples

Reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a rapid method that can replace RT-qPCR. A simple molecular assay for SARS-CoV-2 RNA detection in gold-standard diagnosis through swabs and alternative specimens such as saliva could be helpful in promoting genomic surveillance. A multicenter study was conducted to evaluate the RT-LAMP assay method as an alternative for the molecular detection of SARS-CoV-2 lineages in swab and saliva samples. A total of 350 swabs from individuals with (n = 276) or without (n = 74) COVID-19 tested by RT-qPCR were collected. Paired saliva was also collected from 90 individuals who had SARS-CoV-2 RNA that was detectable (n = 30) or undetectable (n = 60) via RT-qPCR. For the RT-LAMP methodology, six primers were used for ORF1 gene amplification. As for SARS-CoV-2 genotyping, 39 swabs had the whole genome sequenced by MinION. The sensitivity of RT-LAMP to the swab was 90.2%. For the swab samples with Ct ≤ 30, the sensitivity improved by 96%. Considering saliva with Ct ≤ 30 in RT-qPCR testing, the RT-LAMP sensitivity was 100%. The RT-LAMP specificity was 100% for both the swab and saliva samples. This RT-LAMP assay was capable of detecting all the SARS-CoV-2 lineages circulating in the Brazilian swab samples. The RT-LAMP method has significant potential for use in clinical routines since it was capable of detecting SARS-CoV-2 RNA in swab and saliva samples.

Molecular evolution of SARS-CoV-2 from December 2019 to August 2022

Severe acute respiratorysyndrome coronavirus-2 (SARS-CoV-2) pandemic spread rapidly and this scenario is concerning worldwide, presenting more than 590 million coronavirus disease 2019 cases and 6.4 million deaths. The emergence of novel lineages carrying several mutations in the spike protein has raised additional public health concerns worldwide during the pandemic. The present study review and summarizes the temporal spreading and molecular evolution of SARS-CoV-2 clades and variants worldwide. The evaluation of these data is important for understanding the evolutionary histories of SARSCoV-2 lineages, allowing us to identify the origins of each lineage of this virus responsible for one of the biggest pandemics in history. A total of 2897 SARS-CoV-2 whole-genome sequences with available information from the country and sampling date (December 2019 to August 2022), were obtained and were evaluated by Bayesian approach. The results demonstrated that the SARS-CoV-2 the time to the most recent common ancestor (tMRCA) in Asia was 2019-12-26 (highest posterior density 95% [HPD95%]: 2019-12-18; 2019-12-29), in Oceania 2020-01-24 (HPD95%: 2020-01-15; 2020-01-30), in Africa 2020-02-27 (HPD95%: 2020-02-21; 2020-03-04), in Europe 2020-02-27 (HPD95%: 2020-02-20; 2020-03-06), in North America 2020-03-12 (HPD95%: 2020-03-05; 2020-03-18), and in South America 2020-03-15 (HPD95%: 2020-03-09; 2020-03-28). Between December 2019 and June 2020, 11 clades were detected (20I [Alpha] and 19A, 19B, 20B, 20C, 20A, 20D, 20E [EU1], 20F, 20H [Beta]). From July to December 2020, 4 clades were identified (20J [Gamma, V3], 21 C [Epsilon], 21D [Eta], and 21G [Lambda]). Between January and June 2021, 3 clades of the Delta variant were detected (21A, 21I, and 21J). Between July and December 2021, two variants were detected, Delta (21A, 21I, and 21J) and Omicron (21K, 21L, 22B, and 22C). Between January and June 2022, the Delta (21I and 21J) and Omicron (21K, 21L, and 22A) variants were detected. Finally, between July and August 2022, 3 clades of Omicron were detected (22B, 22C, and 22D). Clade 19A was first detected in the SARS-CoV-2 pandemic (Wuhan strain) with origin in 2019-12-16 (HPD95%: 2019-12-15; 2019-12-25); 20I (Alpha) in 2020-11-24 (HPD95%: 2020-11-15; 2021-12-02); 20H (Beta) in 2020-11-25 (HPD95%: 2020-11-13; 2020-11-29); 20J (Gamma) was 2020-12-21 (HPD95%: 2020-11-05; 2021-01-15); 21A (Delta) in 2020-09-20 (HPD95%: 2020-05-17; 2021-02-03); 21J (Delta) in 2021-02-26 (2020-11-02; 2021-04-24); 21M (Omicron) in 2021-01-25 (HPD95%: 2020-09-16; 2021-08-08); 21K (Omicron) in 2021-07-30 (HPD95%: 2021-05-30; 2021-10-19); 21L (Omicron) in 2021-10-03 (HPD95%: 2021-04-16; 2021-12-23); 22B (Omicron) in 2022-01-25 (HPD95%: 2022-01-10; 2022-02-05); 21L in 2021-12-20 (HPD95%: 2021-05-16; 2021-12-31). Currently, the Omicron variant predominates worldwide, with the 21L clade branching into 3 (22A, 22B, and 22C). Phylogeographic data showed that Alpha variant originated in the United Kingdom, Beta in South Africa, Gamma in Brazil, Delta in India, Omicron in South Africa, Mu in Colombia, Epsilon in the United States of America, and Lambda in Peru. The COVID-19 pandemic has had a significant impact on global health worldwide and the present study provides an overview of the molecular evolution of SARS-CoV-2 lineage clades (from the Wuhan strain to the currently circulating lineages of the Omicron).

Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records

Background

COVID-19 caused more than 622 thousand deaths in Brazil. The infection can be asymptomatic and cause mild symptoms, but it also can evolve into a severe disease and lead to death. It is difficult to predict which patients will develop severe disease. There are, in the literature, machine learning models capable of assisting diagnose and predicting outcomes for several diseases, but usually these models require laboratory tests and/or imaging.

Methods

We conducted a observational cohort study that evaluated vital signs and measurements from patients who were admitted to Hospital das Clínicas (São Paulo, Brazil) between March 2020 and October 2021 due to COVID-19. The data was then represented as univariate and multivariate time series, that were used to train and test machine learning models capable of predicting a patient’s outcome.

Results

Time series-based machine learning models are capable of predicting a COVID-19 patient’s outcome with up to 96% general accuracy and 81% accuracy considering only the first hospitalization day. The models can reach up to 99% sensitivity (discharge prediction) and up to 91% specificity (death prediction).

Conclusions

Results indicate that time series-based machine learning models combined with easily obtainable data can predict COVID-19 outcomes and support clinical decisions. With further research, these models can potentially help doctors diagnose other diseases.

Modeling approaches for early warning and monitoring of pandemic situations as well as decision support

The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare systems against pandemic situations. In response, many population-level computational modeling approaches have been proposed for predicting outbreaks, spatiotemporally forecasting disease spread, and assessing as well as predicting the effectiveness of (non-) pharmaceutical interventions. However, in several countries, these modeling efforts have only limited impact on governmental decision-making so far. In light of this situation, the review aims to provide a critical review of existing modeling approaches and to discuss the potential for future developments.

Retrospective Analysis of the SARS-CoV-2 Infection Profile in COVID-19 Positive Patients in Vitoria da Conquista, Northeast Brazil

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for causing Coronavirus Disease-2019 (COVID-19), a heterogeneous clinical condition that manifests varying symptom severity according to the demographic profile of the studied population. While many studies have focused on the spread of COVID-19 in large urban centers in Brazil, few have evaluated medium or small cities in the Northeast region. The aims of this study were: (i) to identify risk factors for mortality from SARS-CoV-2 infection, (ii) to evaluate the gene expression patterns of key immune response pathways using nasopharyngeal swabs of COVID-19 patients, and (iii) to identify the circulating SARS-CoV-2 variants in the residents of a medium-sized city in Northeast Brazil. A total of 783 patients infected with SARS-CoV-2 between May 2020 and August 2021 were included in this study. Clinical-epidemiological data from patients who died and those who survived were compared. Patients were also retrospectively divided into three groups based on disease severity: asymptomatic, mild, and moderate/severe. Samples were added to a qPCR array for analyses of 84 genes involved with immune response pathways and sequenced using the Oxford Nanopore MinION technology. Having pre-existing comorbidity; being male; having cardiovascular disease, diabetes, and/or chronic obstructive pulmonary disease; and PCR cycle threshold (Ct) values under 22 were identified as risk factors for mortality. Analysis of the expression profiles of inflammatory pathway genes showed that the greater the infection severity, the greater the activation of inflammatory pathways, triggering the cytokine storm and downregulating anti-inflammatory pathways. Viral genome analysis revealed the circulation of multiple lineages, such as B.1, B.1.1.28, Alpha, and Gamma, suggesting that multiple introduction events had occurred over time. This study's findings help identify the specific strains and increase our understanding of the true state of local health. In addition, our data demonstrate that epidemiological and genomic surveillance together can help formulate public health strategies to guide governmental actions.

Gamma variant vertically transmitted from a mild symptomatic pregnant woman associated with fatal neonatal COVID

Herein we describe a mild symptomatic real-time reverse transcriptase- polymerase chain reaction-confirmed coronavirus 2 (SARS-CoV-2) infection in a pregnant woman who gave birth to a preterm infant, 32 weeks gestational age. The neonate was immediately isolated after delivery and developed severe respiratory disease that progressed to multisystem inflammatory syndrome and death on the seventh day of life.

Genome sequencing detected the P.1 (gamma) variant in samples obtained at hospital admission (mother) and on the first (10h) and 13th days of life (neonate). Complete homology (mother's and newborn's sequences) confirmed vertical transmission.

To our knowledge, this is the first report of vertically-transmitted SARS-CoV-2 P.1 (gamma) variant in a mild symptomatic infection in pregnancy associated with fatal COVID in a neonate.

Temporal spread and evolution of SARS-CoV-2 in the second pandemic wave in Brazil

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic spread rapidly and this scenario is concerning in South America, mainly in Brazil that presented more than 21 million coronavirus disease 2019 cases and 590 000 deaths. The recent emergence of novel lineages carrying several mutations in the spike protein has raised additional public health concerns worldwide. The present study describes the temporal spreading and evolution of SARS-CoV2 in the beginning of the second pandemic wave in Brazil, highlighting the fast dissemination of the two major concerning variants (P.1 and P.2). A total of 2507 SARS-CoV-2 whole-genome sequences (WGSs) with available information from the country (Brazil) and sampling date (July 2020-February 2021), were obtained and the frequencies of the lineages were evaluated in the period of the growing second pandemic wave. The results demonstrated the increasing prevalence of P.1 and P.2 lineages in the period evaluated. P.2 lineage was first detected in the middle of 2020, but a high increase occurred only in the last trimester of this same year and the spreading to all Brazilian regions. P.1 lineage emerged even later, first in the North region in December 2020 and really fast dissemination to all other Brazilian regions in January and February 2021. All SARS-CoV-2 WGSs of P.1 and P.2 were further separately evaluated with a Bayesian approach. The rates of nucleotide and amino acid substitutions were statistically higher in P.1 than P.2 (p < 0.01). The phylodynamic analysis demonstrated that P.2 gradually spread in all the country from September 2020 to January 2021, while P.1 disseminated even faster from December 2020 to February 2021. Skyline plots of both lineages demonstrated a slight rise in the spreading for P.2 and exponential growth for P.1. In conclusion, these data demonstrated that the P.1 (recently renamed as Gamma) and P.2 lineages have predominated in the second pandemic wave due to the very high spreading across all geographic regions in Brazil at the end of 2020 and beginning of 2021.

Clusters of SARS-CoV-2 Lineage B.1.1.7 Infection after Vaccination with Adenovirus-Vectored and Inactivated Vaccines

A SARS-CoV-2 B.1.1.7 variant of concern (VOC) has been associated with increased transmissibility, hospitalization, and mortality. This study aimed to explore the factors associated with B.1.1.7 VOC infection in the context of vaccination. On March 2021, we detected SARS-CoV-2 RNA in nasopharyngeal samples from 14 of 22 individuals vaccinated with a single-dose of ChAdOx1 (outbreak A, n = 26), and 22 of 42 of individuals with two doses of the CoronaVac vaccine (outbreak B, n = 52) for breakthrough infection rates for ChAdOx1 of 63.6% and 52.4% for CoronaVac. The outbreaks were caused by two independent clusters of the B.1.1.7 VOC. The serum of PCR-positive symptomatic SARS-CoV-2-infected individuals had ~1.8-3.4-fold more neutralizing capacity against B.1.1.7 compared to the serum of asymptomatic individuals. These data based on exploratory analysis suggest that the B.1.1.7 variant can infect individuals partially immunized with a single dose of an adenovirus-vectored vaccine or fully immunized with two doses of an inactivated vaccine, although the vaccines were able to reduce the risk of severe disease and death caused by this VOC, even in the elderly.