Situating teacher well-being in English language teaching

The global events of the 21st century, especially during its second decade, contributed to rising rates of mental and emotional health issues around the world, including depression, anxiety, and social isolation. These concerns, which were compounded by the COVID-19 pandemic, are reminding policymakers, scholars, and stakeholders in the field of education about the importance of well-being in schools and in learning. English language teachers' well-being directly affects their effectiveness, teaching practices, classroom atmosphere, teacher-student relationships, and students' well-being and performance, to name a few. In the same way that teacher preparation and knowledge affect teachers' performance, so does teacher well-being. With the purpose of situating teacher well-being in English language teaching (ELT), this chapter provides a brief overview of existing published works highlighting the effects of well-being on teachers' personal and professional lives. It introduces the topic of well-being and teacher well-being in ELT. The chapter divides the manuscript into three main sections, each addressing a salient topic affecting language teacher well-being-namely, emotions in ELT, work-life balance in ELT, and services and supports in ELT. It introduces the topic with a vignette, followed by a brief overview of the literature. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Analytical Performances of the COVISTIXTM Antigen Rapid Test for SARS-CoV-2 Detection in an Unselected Population (All-Comers).

The performance and validity of the COVISTIXTM rapid antigen test for the detection of SARS-CoV-2 were evaluated in an unselected population. Additionally, we assessed the influence of the Omicron SARS-CoV-2 variant in the performance of this antigen rapid test. Swab samples were collected at two point-of-care facilities in Mexico City from individuals that were probable COVID-19 cases, as they were either symptomatic or asymptomatic persons at risk of infection due to close contact with SARS-CoV-2 positive cases. Detection of the Omicron SARS-CoV-2 variant was performed in 91 positive cases by Illumina sequencing. Specificity and sensitivity of the COVISTIXTM rapid antigen test was 96% (CI 95% 94-98) and 81% (CI 95% 76-85), respectively. The accuracy parameters were not affected in samples collected after 7 days of symptom onset, and it was possible to detect almost 65% of samples with a Ct-value between 30 and 34. The COVISTIXTM antigen rapid test is highly sensitive (93%; CI 95% 88-98) and specific (98%; CI 95% 97-99) for detecting Omicron SARS-CoV-2 variant carriers. The COVISTIXTM rapid antigen test is adequate for examining asymptomatic and symptomatic individuals, including those who have passed the peak of viral shedding, as well as carriers of the highly prevalent Omicron SARS-CoV-2 variant.

Use of Virtual Tools in Teaching-Learning Processes: Advancements and Future Direction

Teaching-learning processes have been affected by the changes that the introduction of information and communication technologies are making to the current global dynamics. This study examines the trends and evolution of the application of virtual tools in teaching-learning processes. Using a bibliometric analysis, 104 articles retrieved using a search equation defined under the PRISMA methodology were analysed. The results allowed the identification of the most influential contributions, authors, and journals, as well as the trends of research carried out in the field, identifying the authors García-Peñalvo, Sénchez-Prieto and Olmos-Migueléñez as the main references in terms of productivity and impact, as well as the journal Computers in Human Behaviour as the most important in academic impact;additionally, it is identified that COVID-19 and online education are among the main emerging concepts, and higher education and the TAM are among the most solid in the research field. Similarly, the research carried out can be classified into four categories based on their main topic: the acceptance of technology;the design of instruments;the design of platforms;and relevant content. Among the main conclusions, it is mentioned that these tools provide aspects of flexibility, coverage and accessibility at all educational levels.

SARS-CoV-2 Genome Variations in Viral Shedding of an Immunocompromised Patient with Non-Hodgkin's Lymphoma.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) is the most transmissible ß-coronavirus in history, affecting all population groups. Immunocompromised patients, particularly cancer patients, have been highlighted as a reservoir to promote accumulation of viral mutations throughout persistent infection. CASE PRESENTATION: We aimed to describe the clinical course and SARS-CoV-2 mutation profile for 102 days in an immunocompromised patient with non-Hodgkin's lymphoma and COVID-19. We used RT-qPCR to quantify SARS-CoV-2 viral load over time and whole-virus genome sequencing to identify viral lineage and mutation profile. The patient presented with a persistent infection through 102 days while being treated with cytotoxic chemotherapy for non-Hodgkin's lymphoma and received targeted therapy for COVID-19 with remdesivir and hyperimmune plasma. All sequenced samples belonged to the BA.1.1 lineage. We detected nine amino acid substitutions in five viral genes (Nucleocapsid, ORF1a, ORF1b, ORF13a, and ORF9b), grouped in two clusters: the first cluster with amino acid substitutions only detected on days 39 and 87 of sample collection, and the second cluster with amino acid substitutions only detected on day 95 of sample collection. The Spike gene remained unchanged in all samples. Viral load was dynamic but consistent with the disease flares. CONCLUSIONS: This report shows that the multiple mutations that occur in an immunocompromised patient with persistent COVID-19 could provide information regarding viral evolution and emergence of new SARS-CoV-2 variants.

Probability of hospitalisation and death among COVID-19 patients with comorbidity during outbreaks occurring in Mexico City.

Background: We compared the probability of hospitalization and death caused by COVID-19 in patients with comorbidities during three periods defined for this study: first-wave (FW), interwave period (IP), and second-wave (SW) observed in Mexico City. Methods: In this registry-based study, we included individuals over 20 years of age. During the FW (symptomatic), the IP, and the SW (symptomatic and asymptomatic), participants were diagnosed using nasopharyngeal swabs. Symptomatic individuals with risk factors for serious disease or death were referred to the hospital. SARS-CoV-2 infection was defined by RT-qPCR in all hospitalized patients. All data were added to the SISVER database. Bayesian analysis and False Discovery Rate were used for further evaluation. Results: The study included 2 260 156 persons (mean age of 43.1 years). Of these, 8.6% suffered from DM, 11.6% arterial hypertension, and 9.7% obesity. Of the total, 666 694 persons tested positive (29.5%). Of the infected persons, a total of 85 587 (12.8%) were hospitalized: 24 023 in the FW; 16 935 in the IP, and 44 629 in the SW. Of the hospitalized patients, there were 42 979 deaths (50.2%), in the FW, 11 964 (49.8%), in the IP, 6794 (40.1%), and in the SW 24 221 (54.3%). The probability of death among individuals hospitalized with or without comorbidities increased consistently in all age groups. A significant increase in the Fatality Rate was observed in individuals with comorbidities (1.36E-19< = FDR< = 3.36E-2). A similar trend was also observed in individuals without comorbidities (1.03E-44< = FDR< = 5.58E-4). Conclusions: The data from this study show a considerable increase in the number of detected cases of infection between the FW and SW. In addition, 12.8% of those infected were hospitalized for severe COVID-19. A high mortality rate was observed among hospitalized patients (>50%). An age-dependent probability of death was observed with a positive trend in hospitalized patients with and without comorbidities.

Actividades de farmacia asistencial durante la pandemia por la Covid-19

Introducción: el personal de las farmacias en los diferentes escenarios de acción realiza actividades que contribuyen con la salud pública y la pandemia es un momento oportuno para destacar el quehacer en pro del bienestar de las personas en las comunidades. Método: esta es una investigación descriptiva a partir de documentos en inglés y español en el periodo 2020-2021, con apoyo de las palabras clave, de los sitios Pub-MEDLINE, LILACS, Ebscohost, Springer, la biblioteca científica electrónica en línea SciELO y Google Scholar. Resultados: se describen las actividades de a) prestación de servicios esenciales, b) medidas preventivas y de asesoramiento sobre los comportamientos de las personas, c) la importancia del rol en educación, asesoría y consejería, d) acciones en el ámbito de la farmacia de la comunidad, e) acciones en el ámbito de la farmacia clínica hospitalaria, f ) las mejoras farmacéuticas en Europa respecto a los programas de inmunizaciones, g) los principales desafíos que enfrenta el campo de la Farmacia, h) el reporte de los resultados de experiencias en diversos contextos: opiniones de usuarios/profesionales en medicina/farmacia o estudiantes de farmacia, los comportamientos de las personas y los resultados de varias investigaciones. Conclusiones: las actividades contribuyen a obtener mejores resultados ante la pandemia de la Covid-19, se consolidan, retoman y proyectan acciones que imponen desafíos en pro del bienestar de las personas en las comunidades, en algunos contextos se realizan con una calidad adecuada mientras en otras hay falencias o debilidades que deben ser subsanadas de manera oportuna.Alternate : Introdução: os profissionais da farmácia nos diferentes cenários de atuação realizam atividades que contribuem para a saúde pública e a atual pandemia é um momento oportuno que destaca o trabalho pelo bem-estar das pessoas nas comunidades. Método: trata-se de uma pesquisa descritiva com base em documentos em inglês e espanhol no período 2020-2021, apoiados por palavras-chave, dos sites Pub- MEDLINE, LILACS, ebscohost, Springer, biblioteca científica eletrônica online SciELo e Google Scholar. Resultados: são descritas as actividades de a) prestação de serviços essenciais, b) medidas preventivas e aconselhamento sobre o comportamento das pessoas, c) a importância do papel na educação, conselhio e aconselhamento, d) acções no domínio da farmácia comunidade, e) acções no domínio da farmácia clínica hospitalar, f ) melhorias farmacêuticas na Europa relativamente aos programas de imunização, g) os principais desafios que se colocam ao domínio da farmácia, h) relatar os resultados das experiências em vários contextos: opiniões dos utilizadores/profissionais da medicina/estudantes de farmácia ou de farmácia, o comportamento das pessoas e os resultados de várias investigações. Conclusões: as atividades contribuem para a obtenção de melhores resultados frente à pandemia Covid-19, são consolidadas, retomadas e projetam ações que impõem desafios em prol do bem-estar das pessoas nas comunidades, em alguns contextos são realizadas fora com uma qualidade adequada, enquanto em outros há deficiências ou pontos fracos que devem ser corrigidos em tempo hábil.Alternate : Introduction: Pharmacy personnel in different action scenarios carry out activities contributing to public health ant the current pandemic is an opportune moment to highlights the work that help the well-being of people in the communities. Method: A descriptive research based on documents in English and Spanish for period 2020-2021 with the support of keywords from the sites Pub-MEDLINE, LILACS, ebscohost, Springer, SciElo online scientific electronic library and Google Scholar. Results: This article describes the activities of a) provision of essential services, b) preventive measures and advice on people´s behaviors, c) the importance of the role in education, advisory and counseling, d) actions in the field of pharmacy of the community, e) actions in th field of hospital clinical pharmacy, f ) pharmaceutical improvements in Europe regarding immunization programs, g) main challenges facing the field of pharmacy, h) reporting the results of experiences in various contexts: opinions of users/professionals in medicine/pharmacy or pharmacy students, people's behaviors and the results of various investigations. Conclusions: Activities contribute to obtaining better results in the face of the Covid-19 pandemic, some of them are consolidated, retaken and projected actions that impose challenges in favor of the well-being people in communities, in some contexts they are carried out with an adequate quality while in others there are shormocings or weaknesses that must be corrected in a timely manner.

COVID-19 Biomarkers Recognition & Classification Using Intelligent Systems

Background: SARS-CoV-2 has paralyzed mankind due to its high transmissibility and its associated mortality, causing millions of infections and deaths worldwide. The search for gene expression biomarkers from the host transcriptional response to infection may help understand the underlying mechanisms by which the virus causes COVID-19. This research proposes a smart methodology integrating different RNA-Seq datasets from SARS-CoV-2, other respiratory diseases, and healthy patients. Methods: The proposed pipeline exploits the functionality of the ‘KnowSeq’ R/Bioc package, integrating different data sources and attaining a significantly larger gene expression dataset, thus endowing the results with higher statistical significance and robustness in comparison with previous studies in the literature. A detailed preprocessing step was carried out to homogenize the samples and build a clinical decision system for SARS-CoV-2. It uses machine learning techniques such as feature selection algorithm and supervised classification system. This clinical decision system uses the most differentially expressed genes among different diseases (including SARS-Cov-2) to develop a four-class classifier. Results: The multiclass classifier designed can discern SARS-CoV-2 samples, reaching an accuracy equal to 91.5%, a mean F1-Score equal to 88.5%, and a SARS-CoV-2 AUC equal to 94% by using only 15 genes as predictors. A biological interpretation of the gene signature extracted reveals relations with processes involved in viral responses. Conclusion: This work proposes a COVID-19 gene signature composed of 15 genes, selected after applying the feature selection ‘minimum Redundancy Maximum Relevance’ algorithm. The integration among several RNA-Seq datasets was a success, allowing for a considerable large number of samples and therefore providing greater statistical significance to the results than in previous studies. Biological interpretation of the selected genes was also provided.

Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection.

SARS-CoV-2 is a coronavirus family member that appeared in China in December 2019 and caused the disease called COVID-19, which was declared a pandemic in 2020 by the World Health Organization. In recent months, great efforts have been made in the field of basic and clinical research to understand the biology and infection processes of SARS-CoV-2. In particular, transcriptome analysis has contributed to generating new knowledge of the viral sequences and intracellular signaling pathways that regulate the infection and pathogenesis of SARS-CoV-2, generating new information about its biology. Furthermore, transcriptomics approaches including spatial transcriptomics, single-cell transcriptomics and direct RNA sequencing have been used for clinical applications in monitoring, detection, diagnosis, and treatment to generate new clinical predictive models for SARS-CoV-2. Consequently, RNA-based therapeutics and their relationship with SARS-CoV-2 have emerged as promising strategies to battle the SARS-CoV-2 pandemic with the assistance of novel approaches such as CRISPR-CAS, ASOs, and siRNA systems. Lastly, we discuss the importance of precision public health in the management of patients infected with SARS-CoV-2 and establish that the fusion of transcriptomics, RNA-based therapeutics, and precision public health will allow a linkage for developing health systems that facilitate the acquisition of relevant clinical strategies for rapid decision making to assist in the management and treatment of the SARS-CoV-2-infected population to combat this global public health problem.

Towards the development of an epitope-focused vaccine for SARS-CoV-2.

The rapid spread of COVID-19 on all continents and the mortality induced by SARS-CoV-2 virus, the cause of the pandemic coronavirus disease 2019 (COVID-19) has motivated an unprecedented effort for vaccine development. Inactivated viruses as well as vaccines focused on the partial or total sequence of the Spike protein using different novel platforms such us RNA, DNA, proteins, and non-replicating viral vectors have been developed. The high global need for vaccines, now and in the future, and the emergence of new variants of concern still requires development of accessible vaccines that can be adapted according to the most prevalent variants in the respective regions. Here, we describe the immunogenic properties of a group of theoretically predicted RBD peptides to be used as the first step towards the development of an effective, safe and low-cost epitope-focused vaccine. One of the tested peptides named P5, proved to be safe and immunogenic. Subcutaneous administration of the peptide, formulated with alumina, induced high levels of specific IgG antibodies in mice and hamsters, as well as an increase of IFN-γ expression by CD8+ T cells in C57 and BALB/c mice upon in vitro stimulation with P5. Neutralizing titers of anti-P5 antibodies, however, were disappointingly low, a deficiency that we will attempt to resolve by the inclusion of additional immunogenic epitopes to P5. The safety and immunogenicity data reported in this study support the use of this peptide as a starting point for the design of an epitope restricted vaccine.

MULTIDISCIPLINARY MANAGEMENT ON PEUTZ-JEGHERS SYNDROME SUSPICION: A CASE REPORT

A 15-year-old woman presented with maxillary odontogenic pain. Extraorally: multiple bluish and dark brown mucocutaneous maculae in periocular, perinasal, perioral skin, and in fingers of both hands. Intraorally: multiple dark brown maculae in gingival, palatine, labial, and bilateral buccal mucosa. She referred occasional abdominal pain. Patient was referred to oral and maxillofacial pathology because Peutz-Jeghers syndrome was suspected. She was also evaluated by pediatric, clinical genetics, and gastroenterology. Genetic-molecular tests, abdominal and pelvic ultrasound, endoscopy, and colonoscopy were requested. A nonspecific growth was detected in the left ovary, so the patient was referred to gynecology. The case is currently being followed, but due to the COVID-19 pandemic, not all complementary tests have been performed. Diagnosis and management of Peutz-Jeghers syndrome must be multidisciplinary by the presence of gastrointestinal polyps and higher risk for developing cancer. Dental surgeons are in a favorable position to make the initial suspicion of the disease.

An RBD-Based Diagnostic Method Useful for the Surveillance of Protective Immunity against SARS-CoV-2 in the Population.

After more than two years, the COVID-19 pandemic is still ongoing and evolving all over the world; human herd immunity against SARS-CoV-2 increases either by infection or by unprecedented mass vaccination. A substantial change in population immunity is expected to contribute to the control of transmission. It is essential to monitor the extension and duration of the population's immunity to support the decisions of health authorities in each region and country, directed to chart the progressive return to normality. For this purpose, the availability of simple and cheap methods to monitor the levels of relevant antibodies in the population is a widespread necessity. Here, we describe the development of an RBD-based ELISA for the detection of specific antibodies in large numbers of samples. The recombinant expression of an RBD-poly-His fragment was carried out using either bacterial or eukaryotic cells in in vitro culture. After affinity chromatography purification, the performance of both recombinant products was compared by ELISA in similar trials. Our results showed that eukaryotic RBD increased the sensitivity of the assay. Interestingly, our results also support a correlation of the eukaryotic RBD-based ELISA with other assays aimed to test for neutralizing antibodies, which suggests that it provides an indication of protective immunity against SARS-CoV-2.

Endotheliitis, Shunts, and Ventilation-Perfusion Mismatch in Coronavirus Disease 2019: A Literature Review of Disease Mechanisms.

The severe acute respiratory syndrome coronavirus 2 pandemic has continued to impact global health. However, while immunity acquired by vaccines has been developed, 40% of the world's population has still not been vaccinated. Economic problems associated with acquiring novel therapies, misinformation, and differences in treatment protocols have generated catastrophic results, especially in low-resource countries. Understanding the pathophysiological aspects of coronavirus disease and the therapeutic strategies that have been validated to date is essential for successful medical care. In this review, I summarize the historical aspects of the virus, molecules involved in infecting the host, and consequences of viral interactions with and in tissues.

Determination of the Severity and Percentage of COVID-19 Infection through a Hierarchical Deep Learning System.

The coronavirus disease 2019 (COVID-19) has caused millions of deaths and one of the greatest health crises of all time. In this disease, one of the most important aspects is the early detection of the infection to avoid the spread. In addition to this, it is essential to know how the disease progresses in patients, to improve patient care. This contribution presents a novel method based on a hierarchical intelligent system, that analyzes the application of deep learning models to detect and classify patients with COVID-19 using both X-ray and chest computed tomography (CT). The methodology was divided into three phases, the first being the detection of whether or not a patient suffers from COVID-19, the second step being the evaluation of the percentage of infection of this disease and the final phase is to classify the patients according to their severity. Stratification of patients suffering from COVID-19 according to their severity using automatic systems based on machine learning on medical images (especially X-ray and CT of the lungs) provides a powerful tool to help medical experts in decision making. In this article, a new contribution is made to a stratification system with three severity levels (mild, moderate and severe) using a novel histogram database (which defines how the infection is in the different CT slices for a patient suffering from COVID-19). The first two phases use CNN Densenet-161 pre-trained models, and the last uses SVM with LDA supervised learning algorithms as classification models. The initial stage detects the presence of COVID-19 through X-ray multi-class (COVID-19 vs. No-Findings vs. Pneumonia) and the results obtained for accuracy, precision, recall, and F1-score values are 88%, 91%, 87%, and 89%, respectively. The following stage manifested the percentage of COVID-19 infection in the slices of the CT-scans for a patient and the results in the metrics evaluation are 0.95 in Pearson Correlation coefficient, 5.14 in MAE and 8.47 in RMSE. The last stage finally classifies a patient in three degrees of severity as a function of global infection of the lungs and the results achieved are 95% accurate.

Effect of High Altitude on the Survival of COVID-19 Patients in Intensive Care Unit: A Cohort Study.

Purpose: The effect of high altitude ( ≥ 1500 m) and its potential association with mortality by COVID-19 remains controversial. We assessed the effect of high altitude on the survival/discharge of COVID-19 patients requiring intensive care unit (ICU) admission for mechanical ventilation compared to individuals treated at sea level. Methods: A retrospective cohort multi-center study of consecutive adults patients with a positive RT-PCR test for COVID-19 who were mechanically ventilated between March and November 2020. Data were collected from two sea-level hospitals and four high-altitude hospitals in Ecuador. The primary outcome was ICU and hospital survival/discharge. Survival analysis was conducted using semi-parametric Cox proportional hazards models. Results: Of the study population (n = 670), 35.2% were female with a mean age of 58.3 ± 12.6 years. On admission, high-altitude patients were more likely to be younger (57.2 vs. 60.5 years old), presented with less comorbidities such as hypertension (25.9% vs. 54.9% with p-value <.001) and diabetes mellitus (20.5% vs. 37.2% with p-value <.001), less probability of having a capillary refill time > 3 sec (13.7% vs. 30.1%, p-value <.001), and less severity-of-illness condition (APACHE II score, 17.5 ± 8.1 vs. 20 ± 8.2, p < .01). After adjusting for key confounders high altitude is associated with significant higher probabilities of ICU survival/discharge (HR: 1.74 [95% CI: 1.46-2.08]) and hospital survival/discharge (HR: 1.35 [95% CI: 1.18-1.55]) than patients treated at sea level. Conclusions: Patients treated at high altitude at any time point during the study period were 74% more likely to experience ICU survival/discharge and 35% more likely to experience hospital survival/discharge than to the sea-level group. Possible reasons for these findings are genetic and physiological adaptations due to exposure to chronic hypoxia.

Determination of the Severity and Percentage of COVID-19 Infection through a Hierarchical Deep Learning System

The coronavirus disease 2019 (COVID-19) has caused millions of deaths and one of the greatest health crises of all time. In this disease, one of the most important aspects is the early detection of the infection to avoid the spread. In addition to this, it is essential to know how the disease progresses in patients, to improve patient care. This contribution presents a novel method based on a hierarchical intelligent system, that analyzes the application of deep learning models to detect and classify patients with COVID-19 using both X-ray and chest computed tomography (CT). The methodology was divided into three phases, the first being the detection of whether or not a patient suffers from COVID-19, the second step being the evaluation of the percentage of infection of this disease and the final phase is to classify the patients according to their severity. Stratification of patients suffering from COVID-19 according to their severity using automatic systems based on machine learning on medical images (especially X-ray and CT of the lungs) provides a powerful tool to help medical experts in decision making. In this article, a new contribution is made to a stratification system with three severity levels (mild, moderate and severe) using a novel histogram database (which defines how the infection is in the different CT slices for a patient suffering from COVID-19). The first two phases use CNN Densenet-161 pre-trained models, and the last uses SVM with LDA supervised learning algorithms as classification models. The initial stage detects the presence of COVID-19 through X-ray multi-class (COVID-19 vs. No-Findings vs. Pneumonia) and the results obtained for accuracy, precision, recall, and F1-score values are 88%, 91%, 87%, and 89%, respectively. The following stage manifested the percentage of COVID-19 infection in the slices of the CT-scans for a patient and the results in the metrics evaluation are 0.95 in Pearson Correlation coefficient, 5.14 in MAE and 8.47 in RMSE. The last stage finally classifies a patient in three degrees of severity as a function of global infection of the lungs and the results achieved are 95% accurate.

End-point RT-PCR based on a conservation landscape for SARS-COV-2 detection.

End-point RT-PCR is a suitable alternative diagnostic technique since it is cheaper than RT-qPCR tests and can be implemented on a massive scale in low- and middle-income countries. In this work, a bioinformatic approach to guide the design of PCR primers was developed, and an alternative diagnostic test based on end-point PCR was designed. End-point PCR primers were designed through conservation analysis based on kmer frequency in SARS-CoV-2 and human respiratory pathogen genomes. Highly conserved regions were identified for primer design, and the resulting PCR primers were used to amplify 871 nasopharyngeal human samples with a previous RT-qPCR based SARS-CoV-2 diagnosis. The diagnostic test showed high accuracy in identifying SARS-CoV-2-positive samples including B.1.1.7, P.1, B.1.427/B.1.429 and B.1.617.2/ AY samples with a detection limit of 7.2 viral copies/µL. In addition, this test could discern SARS-CoV-2 infection from other viral infections with COVID-19-like symptomatology. The designed end-point PCR diagnostic test to detect SARS-CoV-2 is a suitable alternative to RT-qPCR. Since the proposed bioinformatic approach can be easily applied in thousands of viral genomes and over highly divergent strains, it can be used as a PCR design tool as new SARS-CoV-2 variants emerge. Therefore, this end-point PCR test could be employed in epidemiological surveillance to detect new SARS-CoV-2 variants as they emerge and propagate.

Early Genomic, Epidemiological, and Clinical Description of the SARS-CoV-2 Omicron Variant in Mexico City.

Omicron is the most mutated SARS-CoV-2 variant-a factor that can affect transmissibility, disease severity, and immune evasiveness. Its genomic surveillance is important in cities with millions of inhabitants and an economic center, such as Mexico City. Results. From 16 November to 31 December 2021, we observed an increase of 88% in Omicron prevalence in Mexico City. We explored the R346K substitution, prevalent in 42% of Omicron variants, known to be associated with immune escape by monoclonal antibodies. In a phylogenetic analysis, we found several independent exchanges between Mexico and the world, and there was an event followed by local transmission that gave rise to most of the Omicron diversity in Mexico City. A haplotype analysis revealed that there was no association between haplotype and vaccination status. Among the 66% of patients who have been vaccinated, no reported comorbidities were associated with Omicron; the presence of odynophagia and the absence of dysgeusia were significant predictor symptoms for Omicron, and the RT-qPCR Ct values were lower for Omicron. Conclusions. Genomic surveillance is key to detecting the emergence and spread of SARS-CoV-2 variants in a timely manner, even weeks before the onset of an infection wave, and can inform public health decisions and detect the spread of any mutation that may affect therapeutic efficacy.

Territorial Strategy of Medical Units for Addressing the First Wave of the COVID-19 Pandemic in the Metropolitan Area of Mexico City: Analysis of Mobility, Accessibility and Marginalization.

BACKGROUND: The COVID-19 pandemic has caused an exponential increase in the demand for medical care worldwide. In Mexico, the COVID Medical Units (CMUs) conversion strategy was implemented. OBJECTIVE: To evaluate the CMU coverage strategy in the Mexico City Metropolitan Area (MCMA) by territory. MATERIALS: The CMU directory was used, as were COVID-19 infection and mobility statistics and Mexican 2020 census information at the urban geographic area scale. The degree of urban marginalization by geographic area was also considered. METHOD: Using descriptive statistics and the calculation of a CMU accessibility index, population aggregates were counted based on coverage radii. In addition, two regression models are proposed to explain (1) the territorial and temporal trend of COVID-19 infections in the MCMA and (2) the mobility of the COVID-infected population visiting medical units. RESULTS: The findings of the evaluation of the CMU strategy were (1) in the MCMA, COVID-19 followed a pattern of contagion from the urban center to the periphery; (2) given the growth in the number of cases and the overload of medical units, the population traveled greater distances to seek medical care; (3) after the CMU strategy was evaluated at the territory level, it was found that 9 out of 10 inhabitants had a CMU located approximately 7 km away; and (4) at the metropolitan level, the lowest level of accessibility to the CMU was recorded for the population with the highest levels of marginalization, i.e., those residing in the urban periphery.

The Evolutionary Landscape of SARS-CoV-2 Variant B.1.1.519 and Its Clinical Impact in Mexico City.

The SARS-CoV-2 pandemic is one of the most concerning health problems around the globe. We reported the emergence of SARS-CoV-2 variant B.1.1.519 in Mexico City. We reported the effective reproduction number (Rt) of B.1.1.519 and presented evidence of its geographical origin based on phylogenetic analysis. We also studied its evolution via haplotype analysis and identified the most recurrent haplotypes. Finally, we studied the clinical impact of B.1.1.519. The B.1.1.519 variant was predominant between November 2020 and May 2021, reaching 90% of all cases sequenced in February 2021. It is characterized by three amino acid changes in the spike protein: T478K, P681H, and T732A. Its Rt varies between 0.5 and 2.9. Its geographical origin remain to be investigated. Patients infected with variant B.1.1.519 showed a highly significant adjusted odds ratio (aOR) increase of 1.85 over non-B.1.1.519 patients for developing a severe/critical outcome (p = 0.000296, 1.33-2.6 95% CI) and a 2.35-fold increase for hospitalization (p = 0.005, 1.32-4.34 95% CI). The continuous monitoring of this and other variants will be required to control the ongoing pandemic as it evolves.

Acceptability of Clinical Trials on COVID-19 during Pregnancy among Pregnant Women and Healthcare Providers: A Qualitative Study.

Participation of pregnant women in clinical trials entails challenges mainly related to concerns about the risks for fetuses. We undertook a qualitative study from June to October 2020 to assess the acceptability of participating in COVID-19 clinical trials among pregnant women in Spain. Phenomenology and grounded theory were used as methodological approaches. Semi-structured interviews were conducted with 24 pregnant women and six healthcare providers. Women were unsure if pregnancy was a risk factor to acquire the infection or to develop severe disease and expressed the limited information they had received, which led to uncertainties and emotional suffering. They had concerns regarding participation in clinical trials on COVID-19, regardless of the drug under study. Healthcare providers alluded to the importance of involving pregnant women's relatives at the recruitment visit of the clinical trial. These findings may be useful to facilitate pregnant women's participation in clinical trials.