The Untimely Dismissal of Workers with Disabilities in the Private Sector, during the Covid-19 Pandemic in Ecuador

Since March 2020, as a result of the health crisis caused by Covid-19, Ecuador has faced a sensitive panorama in the field of labor relations. The so-called states of emergency, which gave rise to restrictions on freedom of movement and assembly, led to the suspension of activities to safeguard the health of the population;and;consequently, in the issuance of new rules and guidelines for workers. Undoubtedly, a devasting scenario wordwide;and specifically for Ecuador, where, in addition to losing human lives, significant sources of work were lost and working conditions were modified to the detriment of workers, regardless of their condition. From this perspective, in this paper the labor regulations that were applied during the pandemic caused by Covid-19 are analyzed, in contrast to the norm applicable to disabled workers subject to the Labor Code, to finally, propose the procedural scenario that faces this priority care group in the courts of the country.

Design and validation of a low-cost emergency mechanical ventilator in response to the pandemic caused by COVID-19

In this paper, the redesign and construction of a low- cost, open-source, emergency mechanical ventilator prototype is presented, in response to the shortage of mechanical ventilators caused by the COVID-19 pandemic in low- and middle-income countries. This redesign took as its starting point an open-source mechanical ventilator already validated through preclinical testing in a porcine animal model. The objective ofthis work was to improve the previous device, with changes in hardware and software, which resulted in a lower-cost device with greater replicability, maintaining the functional characteristics previously obtained with the base ventilator, verified by means of a mechanical ventilator calibrator. Results show a stable and precise behavior, and with an adequate operating range in accordance with the WHO and MHRA requirements, with a maximum error of 4.97% for pressure and 8.23% for tidal volume measurements. © 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

Real-Time Estimation of Alternative Stress Index for Low-Cost, Mechanical Ventilators for Emergency Use

Stress index is a useful indicator in mechanical ventilation to assess improper ventilation settings. It can indicate tidal overdistension or tidal recruitment, which are two major mechanisms of ventilator-induced lung injury. However, it's implementation require dedicated hardware and software and is not a widespread parameter used in commercial ventilators. In this work, an alternative, simple way to visually inspect the concavity of the pressure-time curve during mechanical ventilation is presented, by calculating the pressure difference of the pressure-time curve. This proves useful when implemented in low-cost emergency devices, such as those designed to cope with the COVID-19 pandemic, because of the reduced computational load required to perform its calculation. The method was implemented in a low-cost emergency mechanical ventilator and tested with an artificial lung for a proof-of-concept. Results show that this alternative method can be effectively used to qualitatively assess the concavity of the pressure-time curve.

COVID-19 Pulmonary Lesion Classification Using CNN Software in Chest X-ray with Quadrant Scoring Severity Parameters

The Sars-Cov2 virus has caused the worst health emergency of the last decade. Furthermore, new strains make the fight against COVID-19 appear far from over. The virus causes a severe acute respiratory syndrome that can lead to death. Effective identification of lung damage by chest radiography using deep learning methods could be advantageous for imaging physicians in differentiating people who need to be admitted to an intensive care unit (ICU) from people that don’t require medical attention, to avoid the collapse of health systems. This article describes the development of a deep learning model to classify and assess lung injuries with a protocol for lung injury quantification. The model is based on U-Net segmentation and injury classification according to the RALE score system. Kaggle platform was used to obtain the chest radiography dataset and MATLAB to generate the mask dataset for training. Finally, each lung is divided in 4 quadrants for lesion quantification. An accuracy of 92.86% was obtained in the segmentation process and 100% in the process of classifying levels of lung lesions. © 2022, Springer Nature Switzerland AG.

Response to COVID-19 for the care of the Mexican migrant population in the southern United States

One of the current questions is about the impact of the pandemic caused by Covid-19, SARS-CoV-2 on the most vulnerable groups of people. In general, it has been documented that the pandemic is affecting different populations unequally. Therefore, this exploratory work investigates the impact that Covid-19 is having on the population of Mexican immigrants residing in United States. To do this, a sample of Mexican migrants who have been treated through the Program of Mobile Health and Welfare Units of the United States-Mexico Border Health Commission in the cities of Phoenix and Tucson, Arizona, is considered. The work also explores and analyzes the first actions carried out in the border region by government actors from both countries. Among the results, it stands out that more than half of the population reported having diabitis mellitus, a moderate or high fat and sugar diet and little physical activity;Thus, it was also observed that they are a population with an average stay in the United States of around 12 years, with a level lower than high school and a low level of English, and work in low-wage occupations. © 2021, Universidad Autonoma del Estado de Mexico. All rights reserved.

Effects of socio-economic factors and health conditions on COVID-19 contagion in the states of Mexico

The aim of this paper is to analyze the effect of a large battery of demographic, social, health and economic factors on the magnitude and intensity of SARS-CoV-2 contagion in the Mexican states. To do so, an extreme-bounds analysis in cross-section econometric models, with possible spatial dependence, is carried out. Our findings suggest that a greater population density (that impedes social distancing), the suffering of obesity and/or chronic degenerative diseases (diabetes and hypertension) and the lack of respect for health regulations have favored the spread of COVID-19. Social conditions of population and economic characteristics seem to be not relevant. The public policy implications from our results are straightforward. © 2020 Universidad Nacional Autonoma de Mexico. All rights reserved.