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This paper aims to introduce a novel family of probability distributions by the well-known method of the T–X family of distributions. The proposed family is called a "Novel Generalized Exponent Power X Family" of distributions. A three-parameters special sub-model of the proposed method is derived and named a "Novel Generalized Exponent Power Weibull" distribution (NGEP-Wei for short). For the proposed family, some statistical properties are derived including the hazard rate function, moments, moment generating function, order statistics, residual life, and reverse residual life. The well-known method of estimation, the maximum likelihood estimation method is used for estimating the model parameters. Besides, a comprehensive Monte Carlo simulation study is conducted to assess the efficacy of this estimation method. Finally, the model selection criterion such as Akaike information criterion (AINC), the correct information criterion (CINC), the Bayesian information criterion (BINC), the Hannan–Quinn information criterion (HQINC), the Cramer–von-Misses (CRMI), and the ANDA (Anderson–Darling) are used for comparison purpose. The comparison of the NGEP-Wei with other rival distributions is made by Two COVID-19 data sets. In terms of performance, we show that the proposed method outperforms the other competing methods included in this study. [ABSTRACT FROM AUTHOR]

In this paper, we tackle the problem of forecasting future pandemics by training models with a COVID-19 time series. We tested this approach by producing one model and using it to forecast a non-trained time series; however, we limited this paper to the eight states with the highest population density in Mexico. We propose a generalized pandemic forecasting framework that transforms the time series into a dataset via three different transformations using random forest and backward transformations. Additionally, we tested the impact of the horizon and dataset window sizes for the training phase. A Wilcoxon test showed that the best transformation technique statistically outperformed the other two transformations with 100% certainty. The best transformation included the accumulated efforts of the other two plus a normalization that helped rescale the non-trained time series, improving the sMAPE from the value of 25.48 attained for the second-best transformation to 13.53. The figures in the experimentation section show promising results regarding the possibility of forecasting the early stages of future pandemics with trained data from the COVID-19 time series. [ABSTRACT FROM AUTHOR]

Copyright of Polish Statistician / Wiadomości Statystyczne is the property of State Treasury - Statistics Poland and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Coronavirus Disease 2019 (COVID-19) pandemic has had social and clinical effects over the healthcare system. Globally, over 314.019.135 confirmed cases and 5.507.370 deaths have been recorded at 12 January 2022, based on the Dashboard updated by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. The continuous rise in the number of asymptomatic, pre-symptomatic, and symptomatic patients has developed efficient and accessible models for prediction using Open Source Libraries and Cloud Services. This paper proposes different machine-learning algorithms to analyse the COVID-19 OpenData Resources from Mexico and Brazil, which represent the two major populations, economics and affected by disease countries in Latin America. This model uses only the COVID-19 patient's geographical, social conditions, economics conditions, clinical risk factors, symptom reports, and demographic data to predict recovery and death. The model of Mexico has an accuracy of 93% and the perceived mean of recall and the precision (F1 Score) of 0.79 on the dataset used. On the other hand, the model of Brazil has an accuracy of 69% and F1 score of 0.75 on the dataset studied. The result considers data from patients under the age of 0 and 120 years. The contribution of the work is the application of Big Data technologies and Machine Learning algorithms using Open Resource Libraries and Amazon Web Services (AWS) with the vision to improve the clinical diagnosis, even infectious disease with mathematical approaches. [ABSTRACT FROM AUTHOR]

In this paper, we investigate whether fertility and newborn health changed during the Covid-19 pandemic in Mexico. We use national administrative data and an event-study design to examine the impact of the Covid-19 pandemic on fertility and newborn health characteristics. Our findings suggest that Mexico's fertility declined temporarily as measured by conceptions that likely occurred during the stay-at-home order. Initially, the general fertility rate fell by 11–12 per cent but quickly rebounded and returned close to its original levels by the end of 2021. Newborn health also deteriorated during the pandemic. Instances of low birthweight and prematurity substantially increased, with both remaining elevated over the entire pandemic period. [ABSTRACT FROM AUTHOR]

Copyright of Revista Telos is the property of Revista Telos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper evaluates the potential responses of international labor mobility to the recent COVID-19 health shocks, using a New Economic Geography model inspired by recent events in Central and North America. The model suggests that the restraining impact of COVID-19 on migratory flows may retain potential emigrants in Mexico and Central America, enlarge the home market in the region, attract foreign and local businesses, and increase real wages. Moreover, this prediction unveils opportunities for the future from the opening of new, regular migratory pathways between Central America and Mexico. These would concentrate population and industry in Mexico, raise the market potential in the area and boost real wages in Mexico – and possibly in Central America as well – despite the partial deindustrialization of the Central American hinterland. [ABSTRACT FROM AUTHOR]

In this paper, I explore what shapes the identities of digital nomads (DNs), a class of remote workers who travel and work concurrently. Through extensive fieldwork and interviews with 50 digital nomads conducted in seven co-working hostels in Mexico in 2022, I construct a theory of DN identity. I base this upon the frequent transformations they undergo in their Circumstances, which regularly change their worker identity. DNs relinquish traditional social determinants of identity, such as nationality and religion. They define their personal identities by their passions and interests, which are influenced by the people they meet. DNs exist in inherently transitive social spaces and, without rigid social roles to fulfil, they represent themselves authentically. They form close relationships with other long-term travellers to combat loneliness and homesickness. Digital nomads define their worker identities around their location independence. This study shows that DNs value their nomadic lifestyle above promotions and financial gain. They define themselves by productivity and professionalism to ensure the sustainability of their lifestyle. Furthermore, digital nomad coworking hubs serve focused, individual work, leaving workplace politics and strict 'office image' norms behind. Without fixed social and professional roles to play, digital nomads define themselves personally according to their ever-evolving passions and the sustainability of their nomadic life. Based on these findings, I present a cyclical framework for DN identity evolution which demonstrates how relational, logistical, and socio-personal flux evolves DN's worker identities. [ABSTRACT FROM AUTHOR]

COVID - 19 affected severely worldwide. The pandemic has caused many causalities in a very short span. The IoT-cloud-based healthcare model requirement is utmost in this situation to provide a better decision in the covid-19 pandemic. In this paper, an attempt has been made to perform predictive analytics regarding the disease using a machine learning classifier. This research proposed an enhanced KNN (k NearestNeighbor) algorithm eKNN, which did not randomly choose the value of k. However, it used a mathematical function of the dataset's sample size while determining the k value. The enhanced KNN algorithm eKNN has experimented on 7 benchmark COVID-19 datasets of different size, which has been gathered from standard data cloud of different countries (Brazil, Mexico, etc.). It appeared that the enhanced KNN classifier performs significantly better than ordinary KNN. The second research question augmented the enhanced KNN algorithm with feature selection using ACO (Ant Colony Optimization). Results indicated that the enhanced KNN classifier along with the feature selection mechanism performed way better than enhanced KNN without feature selection. This paper involves proposing an improved KNN attempting to find an optimal value of k and studying IoT-cloud-based COVID - 19 detection. [ABSTRACT FROM AUTHOR]

Copyright of Revista CienciaUAT is the property of Universidad Autonoma de Tamaulipas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper calculates the effects of the COVID-19 pandemic on educational outcomes for undergraduate business programs in Mexico. We use administrative data from the National Association of Universities and Institutions of Higher Education and a difference-in-differences empirical strategy to estimate the impact. We find a negative effect on intake, enrollment, and graduation outcomes. We also examine heterogeneous effects, showing that top business schools increased the number of intakes with respect to non-top schools. Furthermore, public schools were more negatively impacted than private schools in terms of graduation outcomes, while synchronous-learning programs reported a higher decrease on graduation rates than asynchronous-learning programs. [ABSTRACT FROM AUTHOR]

This paper develops a comparative assessment of the state of asylum in Brazil, Chile, Mexico, and Uruguay. It argues that an accelerated weakening of refugee protection, exacerbated during the pandemic, has taken place across the region. Faced with growing mixed flows, the region’s refugee framework has either been used as an ad hoc regularization mechanism or not been broadly used. Also, pandemic mitigation measures have further weakened access to asylum, through militarization and border closures, and a platitude of deterrence practices. These regressive practices may result in the undermining, abandonment and/or replacement of the region’s widely praised refugee governance. [ABSTRACT FROM AUTHOR]

Amid the backdrop of the COVID-19 pandemic, the living conditions of the population were dramatically altered, with social distancing measures and the looming threat to public health leaving a profound impact on people's lives. This study aims to assess the influence of COVID-19 on subjective well-being and overall quality of life in Mexico. A structural model with latent variables was used. Data were extracted from the National Self-Reported Well-being Survey (SWLS) from October 2020 and January 2021, featuring a robust sample size of 3615 residents from urban areas in Mexico, all aged 18 and above. Findings revealed that around 38% of the variance in overall life satisfaction in October 2020 and January 2021 could be attributed to Personal well-being (0.231), Personal satisfaction (0.320), Satisfaction with the environment (0.076), and Negative emotional states (−0.116). In comparison, October 2019 to January 2020 saw a lower 20% explained variance, primarily associated with Personal well-being (0.184), Personal satisfaction (0.270), and Satisfaction with the environment (0.052). Reliability assessments, including Cronbach's Alpha coefficients, Rho_a, and Composite Reliability, all surpassed 0.70 for each subscale. In addition, our study confirmed convergent validity, as the Average Variance Extracted (AVE) consistently exceeded 0.50 across all subscales, while the discriminant coefficient exceeded 0.70. [ABSTRACT FROM AUTHOR]

Background: During the coronavirus disease 2019 (COVID-19) pandemic, in patients treated for SARS-CoV-2 infection, infections with the Klebsiella pneumoniae bacteria producing New Delhi metallo-B-lactamase (NDM) carbapenemase in the USA, Brazil, Mexico, and Italy were observed, especially in intensive care units (ICUs). This study aimed to assess the impact of Klebsiella pneumoniae NDM infection and other bacterial infections on mortality in patients treated in ICUs due to COVID-19. Methods: The 160 patients who qualified for the study were hospitalized in ICUs due to COVID-19. Three groups were distinguished: patients with COVID-19 infection only (N = 72), patients with COVID-19 infection and infection caused by Klebsiella pneumoniae NDM (N = 30), and patients with COVID-19 infection and infection of bacterial etiology other than Klebsiella pneumoniae NDM (N = 58). Mortality in the groups and chosen demographic data; biochemical parameters analyzed on days 1, 3, 5, and 7; comorbidities; and ICU scores were analyzed. Results: Bacterial infection, including with Klebsiella pneumoniae NDM type, did not elevate mortality rates. In the group of patients who survived the acute phase of COVID-19 the prolonged survival time was demonstrated: the median overall survival time was 13 days in the NDM bacterial infection group, 14 days in the other bacterial infection group, and 7 days in the COVID-19 only group. Comparing the COVID-19 with NDM infection and COVID-19 only groups, the adjusted model estimated a statistically significant hazard ratio of 0.28 (p = 0.002). Multivariate analysis revealed that age, APACHE II score, and CRP were predictors of mortality in all the patient groups. Conclusion: In patients treated for SARS-CoV-2 infection acquiring a bacterial infection due to prolonged hospitalization associated with the treatment of COVID-19 did not elevate mortality rates. The data suggests that in severe COVID-19 patients who survived beyond the first week of hospitalization, bacterial infections, particularly Klebsiella pneumoniae NDM, do not significantly impact mortality. Multivariate analysis revealed that age, APACHE II score, and CRP were predictors of mortality in all the patient groups. [ABSTRACT FROM AUTHOR]

Accurate forecasting remains a challenge, even with advanced techniques like deep learning (DL), ARIMA, and Holt–Winters (H&W), particularly for chaotic phenomena such as those observed in several areas, such as COVID-19, energy, and financial time series. Addressing this, we introduce a Forecasting Method with Filters and Residual Analysis (FMFRA), a hybrid methodology specifically applied to datasets of COVID-19 time series, which we selected for their complexity and exemplification of current forecasting challenges. FMFFRA consists of the following two approaches: FMFRA-DL, employing deep learning, and FMFRA-SSA, using singular spectrum analysis. This proposed method applies the following three phases: filtering, forecasting, and residual analysis. Initially, each time series is split into filtered and residual components. The second phase involves a simple fine-tuning for the filtered time series, while the third phase refines the forecasts and mitigates noise. FMFRA-DL is adept at forecasting complex series by distinguishing primary trends from insufficient relevant information. FMFRA-SSA is effective in data-scarce scenarios, enhancing forecasts through automated parameter search and residual analysis. Chosen for their geographical and substantial populations and chaotic dynamics, time series for Mexico, the United States, Colombia, and Brazil permitted a comparative perspective. FMFRA demonstrates its efficacy by improving the common forecasting performance measures of MAPE by 22.91%, DA by 13.19%, and RMSE by 25.24% compared to the second-best method, showcasing its potential for providing essential insights into various rapidly evolving domains. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has demanded prompt actions from governments all over the world. In both developed and developing countries, national governments have had to make unprecedented decisions to face the extraordinary challenges posed by the pandemic. In this paper, we explore how, due to the limited intervention from the Mexican federal government (in terms of policy actions, funding mechanisms and acting as a coordinating agent), state governments stepped up to respond to the pandemic. We argue that Mexico's response was relatively decentralized and substantially shaped by individual subnational governments. Based on a new dataset of over 600 subnational governments' responses to the social and economic effects of the pandemic, we show that state governments decided to react to the pandemic with their own policy measures, responding locally to pressing concerns. Furthermore, we demonstrate that state government responses varied widely in their scope and ambition, which exacerbated the pandemic's uneven national effects. We further contend that the structural constraints of Mexico's federalism have had an impact on these reactions, as social policy responsibilities at the state and local levels have historically been opaque and fragmented and state governments lack the funding necessary to implement sufficient and innovative initiatives. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to identify what immediate actions can be taken by the North American hospitality and tourism industry to propel economic recovery in the industry. Design/methodology/approach: A selected cross-section of relevant and recent publications is reviewed. Current practices that are in use by practitioners in the hospitality and tourism community are examined and shared. Findings: This paper suggests that domestic tourism should be encouraged and that hospitality managers should: communicate what actions have been taken to mitigate Covid-19 transmission within their operations, understand what consumers want and need in a Covid-19 environment and embrace and leverage technology to its full potential. Originality/value: This paper should be of interest as it is speaks to today's challenges that confront the North American hospitality and tourism industry in the Covid-19 operating environment. [ABSTRACT FROM AUTHOR]

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of EconoQuantum is the property of Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we examine transborder commuters' experiences (i.e. individuals who commute between U.S. and Mexican border cities frequently) during the Covid-19 pandemic, with keen attention to the links between racial capitalism and temporality. We address two interrelated issues: first, we unpack how the United States framed the pandemic through the metaphor of war and the production of the categories of 'essential work(er)' and 'essential travel' to ensure racial capitalism's surplus labor and continuation. These categories function like a double-edged sword, tying racialized populations to racial capitalism's temporality to exploit them while excluding privileged others. We argue that Covid-19's temporality conflicts with racial capitalism's temporality. While the former relies on the deceleration of everyday life, the latter depends on constant acceleration driven by profit-seeking. Using queer and feminist theoretical lenses, we then demonstrate how U.S. Covid-19 border restrictions at land ports of entry exacerbated transborder commuters' cross-border travels and privileged some based on legal status. As a result, they used public Facebook groups to navigate and comprehend new commuting conditions, disidentifying with the United States' official pandemic framing and producing their own. This shared experience catalyzed 'digital transborder kinships' or temporally-bound socialities rooted in relational care, advocacy, and knowledge production. [ABSTRACT FROM AUTHOR]

Background: Ioannidis et al. (2020) reported a standardized estimate of scientific productivity obtained from a worldwide database of 6,880,389 scientists who published at least 5 papers picked up by the Scopus database, and elaborated a ranking of ca. 120,000 scientists by both whole trajectory (career-long) impact and their current impact at year 2019. The goal of our paper is to contextualize Latin American ecologists' contribution at the world level based on the four most scientifically productive countries in the region. Methods and findings: Ioannidis et al. (2020) proposed a composite index that is the sum of six scientometric indicators: (1) The number of allocites, (2) the h index, (3) a per capita corrected version of h, (4) the allocites received as single author, (5) those received as single + first author, and (6) those as single + first + last author. We selected data for ecologists from Argentina, Brazil, Chile, and Mexico and comparatively analyzed their productivity according to the proposed index. We also compared these data with those obtained from a global sample of the top ecologists worldwide. Conclusions: Based on Ioannidis et al.'s proposition to evaluate scientific productivity we extract three lessons: (1) It does not pay to publish many papers; what counts is the number of allocites (i.e., self-citations do not add up). (2) Either be single, first, or last author; it does not pay to be in the middle of an authorship line. (3) Even worse it is to be among many co-authors because the proposed index allocates credits on a per capita basis. [ABSTRACT FROM AUTHOR]

Throughout the early stages of the COVID-19 pandemic in Mexico (August—December 2020), we closely followed a cohort of n = 100 healthcare workers. These workers were initially seronegative for Immunoglobulin G (IgG) antibodies against SARS-CoV-2, the virus that causes COVID-19, and maintained close contact with patients afflicted by the disease. We explored the database of demographic, physiological and laboratory parameters of the cohort recorded at baseline to identify potential risk factors for infection with SARS-CoV-2 at a follow-up evaluation six months later. Given that susceptibility to infection may be a systemic rather than a local property, we hypothesized that a multivariate statistical analysis, such as MANOVA, may be an appropriate statistical approach. Our results indicate that susceptibility to infection with SARS-CoV-2 is modulated by sex. For men, different physiological states appear to exist that predispose to or protect against infection, whereas for women, we did not find evidence for divergent physiological states. Intriguingly, male participants who remained uninfected throughout the six-month observation period, had values for mean arterial pressure and waist-to-hip ratio that exceeded the normative reference range. We hypothesize that certain risk factors that worsen the outcome of COVID-19 disease, such as being overweight or having high blood pressure, may instead offer some protection against infection with SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Background. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19). It is estimated that more than half of new infections are transmitted by asymptomatic people; therefore, the isolation of symptomatic people is not enough to control the spread of the disease. Methods. A total of 171 unvaccinated young adults (18–35 years) from Sonora, Mexico, who underwent a structured survey to identify prior COVID-19 infections, were included in this study. A qualitative determination of anti-SARS-CoV-2 antibodies in serum was performed by lateral flow immunoassay (Certum IgG/IgM Rapid Test™ cassette kit) and neutralizing antibodies were also determined (GenScript cPass assay). Results. A total of 36 people reported a history of COVID-19 infection, and 135 reported no history of COVID-19. In contrast, 49.6% (67/135) of individuals who had not reported a previous SARS-CoV-2 infection were seropositive to the rapid anti-SARS-CoV-2 antibody test, and 48.1% (65/135) of them had neutralizing antibodies. Conclusions. These results suggest that in young adults, SARS-CoV-2 infections could be asymptomatic in a high percentage of individuals, which could contribute in part to the slow control of the current pandemic due to the large number of asymptomatic cases that are contagious and that could be a silent spread of the virus. [ABSTRACT FROM AUTHOR]

A spatial survival analysis was performed to identify some of the factors that influence the survival of patients with COVID-19 in the states of Guerrero, México, and Chihuahua. The data that we analyzed correspond to the period from 28 February 2020 to 24 November 2021. A Cox proportional hazards frailty model and a Cox proportional hazards model were fitted. For both models, the estimation of the parameters was carried out using the Bayesian approach. According to the DIC, WAIC, and LPML criteria, the spatial model was better. The analysis showed that the spatial effect influences the survival times of patients with COVID-19. The spatial survival analysis also revealed that age, gender, and the presence of comorbidities, which vary between states, and the development of pneumonia increase the risk of death from COVID-19. [ABSTRACT FROM AUTHOR]

This study examines the influence of the Covid-19 pandemic on anxiety and depression symptoms among college students, paying special attention to gender-related differences. To do that, we use data from a special survey applied to all students from one of Mexico's largest universities six months after the start of the Covid-19 pandemic. The survey was applied online through the university's IT platform, obtaining a response rate of 48.2% and a final sample of 66,067 students. We follow an empirical strategy commonly found in the literature that involves the use of a Negative Binomial Regression Model on two mental health scales: the Hamilton Anxiety Scale and the Zung Depression Scale. The loss of household income and the resulting necessity to participate in the labor market, as well as the lack of sufficient infrastructure to face confinement and online study, were identified as the two main pathways via which the Covid-19 pandemic harmed the mental health of college students. Although female students presented higher rates of anxiety and depression and were more affected by the vulnerable economic and labor conditions of their families, male students were more affected by the lack of availability of space and equipment to attend online classes at home. Since the most economically disadvantaged students experience higher rates of anxiety and depression, particularly among women, this could have medium and long-term effects in terms of economic and gender inequality. These findings highlight the need for specific prevention and intervention initiatives to alleviate anxiety and depression. [ABSTRACT FROM AUTHOR]

Background: Mexico is one of the countries with the greatest excess death due to COVID-19. Chiapas, the poorest state in the country, has been particularly affected. Faced with an exacerbated shortage of health professionals, medical supplies, and infrastructure to respond to the pandemic, the non-governmental organization Compañeros En Salud (CES) implemented a COVID-19 infection prevention and control program to limit the impact of the pandemic in the region. We evaluated CES's implementation of a community health worker (CHW)-led contact tracing intervention in eight rural communities in Chiapas. Methods: Our retrospective observational study used operational data collected during the contract tracing intervention from March 2020 to December 2021. We evaluated three outcomes: contact tracing coverage, defined as the proportion of named contacts that were located by CHWs, successful completion of contact tracing, and incidence of suspected COVID-19 among contacts. We described how these outcomes changed over time as the intervention evolved. In addition, we assessed associations between these three main outcomes and demographic characteristics of contacts and intervention period (pre vs. post March 2021) using univariate and multivariate logistic regression. Results: From a roster of 2,177 named contacts, 1,187 (54.5%) received at least one home visit by a CHW and 560 (25.7%) had successful completion of contact tracing according to intervention guidelines. Of 560 contacts with complete contact tracing, 93 (16.6%) became suspected COVID-19 cases. We observed significant associations between sex and coverage (p = 0.006), sex and complete contact tracing (p = 0.049), community of residence and both coverage and complete contact tracing (p < 0.001), and intervention period and both coverage and complete contact tracing (p < 0.001). Conclusions: Our analysis highlights the promises and the challenges of implementing CHW-led COVID-19 contact tracing programs. To optimize implementation, we recommend using digital tools for data collection with a human-centered design, conducting regular data quality assessments, providing CHWs with sufficient technical knowledge of the data collection system, supervising CHWs to ensure contact tracing guidelines are followed, involving communities in the design and implementation of the intervention, and addressing community member needs and concerns surrounding stigmatization arising from lack of privacy. [ABSTRACT FROM AUTHOR]

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Objective: We report the effect of COVID-19 confinement on some psychological variables associated with mental health: Stress perception, types of coping strategies during crises, and some components related to resilience. Method: A national sample of the Mexican population was considered in a total of 2775 people whose ages ranged from 15 years and older. Questionnaires that met the psychometric criteria (reliability and validity) to be used in Latino samples were used. Results: The results showed that older people experienced less stress and displayed more efficient coping behaviors. Discussion: Regarding the exploration of some components associated with resilience, it was found that family constitutes an important interpersonal resource for coping with the crisis related to confinement due to the COVID-19 pandemic. In the future, it is proposed to make comparisons of the psychological factors evaluated to detect and analyze possible fluctuations due to the prevalence of epidemic conditions. [ABSTRACT FROM AUTHOR]

Background: The social distancing policies implemented by the health authorities during the COVID-19 pandemic in Mexico and elsewhere led to major changes in teaching strategies for college undergraduates. So far, there is limited data regarding the impact of the lockdown on the academic stress and mental health of these students. Objective: To assess the occurrence of academic difficulties, anxiety, depression, and academic stressors resulting in somatization with subsequent coping strategies linked to the pandemic. Materials and methods: A cross-sectional study was conducted with 728 medical students (years 1-5). A purposely designed questionnaire to assess academic difficulties associated with the pandemic was administered electronically. The validated Goldberg anxiety and depression scale was also used, as well as the SISCO-II inventory on academic stress. Results: Screening for anxiety and depression led to a prevalence of 67.9 and 81.3%, respectively. Most relevant stressors, reported always or nearly always, included professors' evaluations (63.9%), and reading overload of academic papers (50.6%). Factorial analyses showed that women were more prone to stress than men (p < 0.001). Somatization symptomatology included drowsiness or increased need of sleep, anxiety, anguish, desperation, chronic fatigue, and sleep disorders. Common coping strategies included practicing a hobby, done always or nearly always by 65% of students with high stress, and 34% of those with low stress (p < 0.001). Conclusion: There was a relevant impact of the mandatory lockdown during COVID-19 pandemic on the mental health of medical students reflected in the high prevalence rates of anxiety, depression, and stressors in the studied population pointing to the need for designing and implementing preventive strategies to deal with the effects of lockdowns. [ABSTRACT FROM AUTHOR]

Copyright of Dixi is the property of Universidad Cooperativa de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A documentary review was carried out on the production and publication of research papers related to the study of the variabl e Connectivity and Management of Technological Supplies in Educational Institutions during Covid-19 in Latin America. The purpose of the bibliometric analysis proposed in this document is to know the main characteristics of the volume of publications registered in Scopus database during the period between 2020 and the first semester of 2021 in Latin American countries, achieving the identification of 32 publications in total. The information provided by this platform was organized by means of graphs and figures, categorizing the information by Year of Publication, Country of Origin, Area of Knowledge and Type of Publication. Once these characteristics were described, the position of different authors regarding the proposed topic was referenced by means of a qualitative analysis. Among the main findings of this research, it is found that Mexico, with 10 publications, is the Latin American country with the highest production. The area of knowledge that made the greatest contribution to the construction of bibliographic material related to the study of Connectivity and Supply Management was Social Sciences with 19 published documents, and the type of publication that was most used during the period mentioned above was the journal article, which represents 66% of the total scientific production. [ABSTRACT FROM AUTHOR]

Copyright of Investigación Económica is the property of Universidad Nacional Autonoma de Mexico, Facultad de Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Innovar: Revista de Ciencias Administrativas y Sociales is the property of Universidad Nacional de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Innovar: Revista de Ciencias Administrativas y Sociales is the property of Universidad Nacional de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Regional Science Policy & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The impact of Covid pandemic is inequitable on countries of the world. While some countries have rebounded despite a severe case of pandemic influence, such as the US, some others did not receive as hard a shock of the disease. In this paper, the authors focus on the Covid-19 effects on macroeconomies of the US, Canada and Mexico - three countries that signed the newly adopted Free Trade Agreement after North American Free Trade Agreement (NAFTA). It is seen that the Covid effects are drastically different in these economies, with the US getting the worst of it. Policies adopted were precautionary in Mexico, but quite liberal in the US and Canada. The trade agreement clauses had to be either modified or completely discarded. The immigration problem at the southern border of the US has added more burden on the trade agreement. The paper discusses these aspects. [ABSTRACT FROM AUTHOR]

The objective was to evaluate the Modified Early Warning Score in patients hospitalized for COVID-19 plus chronic disease. Methods: Retrospective observational study, 430 hospitalized patients with COVID-19 and chronic disease. Instrument, Modified Early Warning Score (MEWS). Data analysis, with Cox and logistic regression, to predict survival and risk. Results: Of 430 patients, 58.6% survived, and 41.4% did not. The risk was: low 53.5%, medium 23.7%, and high 22.8%. The MEWS score was similar between survivors 3.02, p 0.373 (95% CI: −0.225–0.597) and non-survivors 3.20 (95% CI: −0.224–0.597). There is a linear relationship between MEWS and mortality risk R 0.920, ANOVA 0.000, constant 4.713, and coefficient 4.406. The Cox Regression p 0.011, with a risk of deterioration of 0.325, with a positive coefficient, the higher the risk, the higher the mortality, while the invasive mechanical ventilation coefficient was negative −0.757. By providing oxygen and ventilation, mortality is lower. Conclusions: The predictive value of the modified early warning score in patients hospitalized for COVID-19 and chronic disease is not predictive with the MEWS scale. Additional assessment is required to prevent complications, especially when patients are assessed as low-risk. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has deeply influenced the economy of all nations, and Mexico is no exception. This effect is distinct for different groups of the population, with variable socio-economic and demographic characteristics, that live in regions of contrasting features. An efficient apparatus for measuring expenditure variations and tendency is the National Household Income and Expenditure Survey performed by the National Institute of Statistics and Geography in accordance with the international standardization established at the Canberra Conference; the latter permits, every two years, for different surveys to be comparable in time and space. Hence, in Mexico, there are three surveys for 2018, 2020, and 2022. The results of the comparison indicate that different groups of the Mexican population have experienced the pandemic with multiple impacts, apparently without large proportional variation regarding expenditure but with greater variation in time-use conditions. Moreover, it became apparent that even though the lower strata of Mexico's population have fewer proportional variations concerning income after the COVID-19 outburst, they must incorporate more family members into working activities to achieve a survival line; the latter results in the abandonment of school from various young household members that will negatively impact the quality of their lives in the long term. [ABSTRACT FROM AUTHOR]

Background: Recent U.S. immigration policy has increasingly focused on asylum deterrence and has been used extensively to rapidly deport and deter asylum-seekers, leaving thousands of would-be asylum-seekers waiting indefinitely in Mexican border cities, a large and growing proportion of whom are pregnant and parenting women. In the border city of Tijuana, Mexico, these women are spending unprecedented durations waiting under unsafe humanitarian conditions to seek safety in the U.S, with rising concerns regarding increases in gender-based violence (GBV) among this population during the COVID-19 pandemic. Given existing gaps in evidence, we aimed to describe the lived experiences of GBV in the context of asylum deterrence policies among pregnant and parenting asylum-seeking women at the Mexico-U.S. border. Methods: Within the community-based Maternal and Infant Health for Refugee & Asylum-Seeking Women (MIHRA) study, we conducted semi-structured qualitative interviews with 30 asylum-seeking women in Tijuana, Mexico between June and December 2022. Eligible women had been pregnant or postpartum since March 2020, were 18–49 years old, and migrated for the purposes of seeking asylum in the U.S. Drawing on conceptualizations of structural and legal violence, we conducted a thematic analysis of participants' experiences of GBV in the context of asylum deterrence policies and COVID-19. Results: Pregnant and parenting asylum-seeking women routinely faced multiple forms of GBV perpetuated by asylum deterrence policies at all stages of migration (pre-migration, in transit, and in Tijuana). Indefinite wait times to cross the border and inadequate/unsafe shelter exacerbated further vulnerability to GBV. Repeated exposure to GBV contributed to poor mental health among women who reported feelings of fear, isolation, despair, shame, and anxiety. The lack of supports and legal recourse related to GBV in Tijuana highlighted the impact of asylum deterrence policies on this ongoing humanitarian crisis. Conclusion: Asylum deterrence policies undermine the health and safety of pregnant and parenting asylum-seeking women at the Mexico-U.S. border. There is an urgent need to end U.S. asylum deterrence policies and to provide respectful, appropriate, and adequately resourced humanitarian supports to pregnant and parenting asylum-seeking women in border cities, to reduce women's risk of GBV and trauma. [ABSTRACT FROM AUTHOR]

In this study, we consider the initial effects of the COVID-19 pandemic on family formation and dissolution. We use national microdata covering all marriages and divorces in Mexico, an event-study design and a difference-in-difference specification. Our findings indicate that over March through December of 2020, marriage rates declined by 54% and divorce rates by 43%. By the end of 2020, divorce rates recover back to baseline levels, but marriage rates remain 30% below the 2017–2019 baseline level. Overall, our findings suggest that marital dissolutions quickly recovered (6 months into the pandemic), but at the end of 2020, family formation remained at persistently lower levels. [ABSTRACT FROM AUTHOR]

The number of research papers interested in studying the social dimension of supply chain sustainability and resilience is increasing in the literature. However, the social dimension is complex, with several uncertainty variables that cannot be expressed with a traditional Boolean logic of totally true or false. To cope with uncertainty, Fuzzy Logic allows the development of models to obtain crisp values from the concept of fuzzy linguistic variables. Using the Structural Equation Model by Partial Least Squares (SEM-PLS) and Evolutionary Fuzzy Knowledge, this research aims to analyze the predictive power of social sustainability characteristics on supply chain resilience performance in the context of the COVID-19 pandemic with representative cases from Mexico and Chile. We validate our approach using the Chile database for training our model and the Mexico database for testing. The fuzzy knowledge database has a predictive power of more than 80%, using social sustainability features as inputs regarding supply chain resilience in the context of the COVID-19 pandemic disruption. To our knowledge, no works in the literature use fuzzy evolutionary knowledge to study social sustainability in correlation with resilience. Moreover, our proposed approach is the only one that does not require a priori expert knowledge or a systematic mathematical setup. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Economía (Universidad Autónoma de Yucatán) is the property of Universidad Autonoma de Yucatan, Facultad de Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The new pandemic caused by the COVID-19 virus has generated an overload in the quality of medical care in clinical centers around the world. Causes that originate this fact include lack of medical personnel, infrastructure, medicines, among others. The rapid and exponential increase in the number of patients infected by COVID-19 has required an efficient and speedy prediction of possible infections and their consequences with the purpose of reducing the health care quality overload. Therefore, intelligent models are developed and employed to support medical personnel, allowing them to give a more effective diagnosis about the health status of patients infected by COVID-19. This paper aims to propose an alternative algorithmic analysis for predicting the health status of patients infected with COVID-19 in Mexico. Different prediction models such as KNN, logistic regression, random forests, ANN and majority vote were evaluated and compared. The models use risk factors as variables to predict the mortality of patients from COVID-19. The most successful scheme is the proposed ANN-based model, which obtained an accuracy of 90% and an F1 score of 89.64%. Data analysis reveals that pneumonia, advanced age and intubation requirement are the risk factors with the greatest influence on death caused by virus in Mexico. [ABSTRACT FROM AUTHOR]

We simulate the short- and long-term distributional consequences of COVID-19 in the four largest Latin American economies: Argentina, Brazil, Colombia, and Mexico. We show that the short-term impact on income inequality and poverty can be very significant, but that additional spending on social assistance more than offsets the effect in Brazil. The offsetting effect is significant in Argentina and Colombia and nil in Mexico, where there has been no such expansion. We find that a universal basic income that would have produced the same reduction in the poverty gap as actual policies would have cost slightly more but would have benefited the poor (the nonpoor) slightly less (more). To project the longterm consequences, we estimate the impact of the pandemic on school achievement and its intergenerational persistence. We use information on school closures, educational mitigation policies, and account for educational losses related to health shocks and parental job loss. Our findings show that in all four countries the impact is strongly asymmetric and affects particularly the high-school completion rates of children from disadvantaged families. Our simulations suggest that mitigation policies seem to have a minor impact on containing these negative effects. [ABSTRACT FROM AUTHOR]

The mortality risk factors for coronavirus disease (COVID‐19) must be early predicted, especially for severe cases, to provide intensive care before they develop to critically ill immediately. This paper aims to develop an optimized convolution neural network (CNN) for predicting mortality risk factors for COVID‐19 patients. The proposed model supports two types of input data clinical variables and the computed tomography (CT) scans. The features are extracted from the optimized CNN phase and then applied to the classification phase. The CNN model's hyperparameters were optimized using a proposed genetic‐based adaptive momentum estimation (GB‐ADAM) algorithm. The GB‐ADAM algorithm employs the genetic algorithm (GA) to optimize Adam optimizer's configuration parameters, consequently improving the classification accuracy. The model is validated using three recent cohorts from New York, Mexico, and Wuhan, consisting of 3055, 7497,504 patients, respectively. The results indicated that the most significant mortality risk factors are: CD 8+ T Lymphocyte (Count), D‐dimer greater than 1 Ug/ml, high values of lactate dehydrogenase (LDH), C‐reactive protein (CRP), hypertension, and diabetes. Early identification of these factors would help the clinicians in providing immediate care. The results also show that the most frequent COVID‐19 signs in CT scans included ground‐glass opacity (GGO), followed by crazy‐paving pattern, consolidations, and the number of lobes. Moreover, the experimental results show encouraging performance for the proposed model compared with different predicting models. [ABSTRACT FROM AUTHOR]

As a result of the COVID-19 pandemic, various joint efforts have been made to support the creation of vaccines. Different projects have been under development, of which some are in the clinical evaluation stage and others in are in phase III with positive results. The aim of this paper was to describe the current situation of the development and production of vaccines available to the population to facilitate future research and continue developing and proposing ideas for the benefit of the population. So, we carried out a systematic review using databases such as PubMed, ScienceDirect, SciELO, and MEDLINE, including keywords such as "vaccines," "COVID-19," and "SARS-CoV-2". We reviewed the development and production of the anti-COVID vaccine and its different platforms, the background leading to the massive development of these substances, and the most basic immune aspects for a better understanding of their physiological activity and the immune response in those who receive the vaccine. We also analyzed immunization effects in populations with any medical or physiological conditions (such as immunosuppression, people with comorbidities, and pregnancy), as well as the response to immunization with heterologous vaccines and the hybrid immunity (the combination of natural immunity to SARS-CoV-2 with immunity generated by the vaccine). Likewise, we address the current situation in Mexico and its role in managing the vaccination process against SARS-CoV-2 at the national and international levels. There are still many clinical and molecular aspects to be described, such as the duration of active immunity and the development of immunological memory, to mention some of the most important ones. However, due to the short time since the global vaccination roll-out and that it has been progressive (not counting children and people with medical conditions), it is premature to say whether a second vaccination schedule will be necessary for the near future. Thus, it is essential to continue with health measures. [ABSTRACT FROM AUTHOR]

The great majority of people in developing countries depend on the informal economy for their livelihoods. In countries that rely heavily on tourism, pandemics and related confinements make these individual even more socioeconomically vulnerable. This paper critically explores the immediate socioeconomic effects on the informal tourism economy of confinement measures associated with the corona virus-19 pandemic, as seen from a social vulnerability perspective. Mexico is one of the countries that depends the most on tourism and the informal economy, so this nation was selected for an exploratory case study. The results suggest that many workers in the informal tourism sector were affected immediately by – and their vulnerability increased because of – pandemic-related confinements. These restrictive measures' imposition on the entire population highlighted Mexico's deep social inequalities. Recommendations are offered of how to protect vulnerable individuals involved in the informal tourism economy. [ABSTRACT FROM AUTHOR]

Copyright of Mexican Journal of Economics & Finance / Revista Mexicana de Economia y Finanzas is the property of Instituto Mexicano de Ejecutivos de Finanzas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Campus Virtuales is the property of Campus Virtuales and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)