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INTRODUCTION: Puerto Rico has endured three major environmental and public health crises (Hurricane Irma, Hurricane Maria, the unprecedented seismic activity of January 2020) and the coronavirus disease 2019 (COVID-19) pandemic during the past 5 years. All these events might lead to an unquestionable deleterious impact in the prevention of cancer and across the cancer continuum, exacerbating cancer health disparities in the future. Cancer screening plays a critical role in early cancer detection. COVID-19 has significantly hampered screening programs in many countries' cancer screening infrastructure and services, affecting adherence. Cancer is the leading cause of morbidity and mortality in Puerto Rico. Limited information is available about the impact the current pandemic on colorectal cancer screening. In this study, we aim to describe the impact of the COVID-19 pandemic on colorectal cancer screening in 2020 and assess if this impact varied by health regions. METHOD(S): This study analyzed administrative data claims from the Public Health System of Puerto Rico which is managed by the Government of Puerto Rico through the Health Insurance Administration. The Current Procedural Terminology (CPT) codes included for this study were (81528, 82270, G0104, G0105, G0121, G0328, G0464). To assess changes in the numbers of colorectal cancer screening claims between the incurred year (2016 and 2020), Poisson regression was used. Initially, we fitted this model with only the incurred year as the predictor and offsetting the model with the annual average of total insured (univariate model). Based on this model, we estimate the magnitude of association between the number of claims and incurred year using the Prevalence Ratio (PR) of claims. Lastly, Poisson univariate regression model were used for each of the seven health regions (Ponce, Bayamon, Caguas, Mayaguez, Metro, Arecibo and Fajardo) to assess potential geographic disparities. RESULT(S): The numbers of colorectal cancer screening claims significantly decreased by 40% (PRcrude: 0.60, 95%CI: 0.59, 0.62) in 2020 when compared to 2016. However, when adjusting for claim incurred month, sex, health region and offsetting the model with the annual average of total insured, the numbers of colorectal cancer screening claims significantly decreased by 34%, (PRadj: 0.66, 95%CI: 0.64, 0.67). The numbers of colorectal cancer screening claims significantly decreased in all health regions in 2020 when compared to 2016 (p<0.05). However, the most impacted region was the Eastern region, Fajardo, with a 64% (PRFajardocrude: 0.36, 95%CI: 0.30, 0.42) significant decrease in numbers of colorectal cancer screening claims. CONCLUSION(S): COVID-19 had a profound negative effect on colorectal screening in Puerto Rico. Moreover, despite the beneficiaries of this governmental health plan sharing similar sociodemographic and socioeconomic background, regional differences were observed.
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Introduction: The COVID-19 pandemic has caused major changes to healthcare services, especially those related to early detection and screening practices like breast cancer. In Puerto Rico, breast cancer is the main cause of death, representing 18.9% of cancer deaths in women, making early detection even more important to prevent morbidity and mortality. This study aims to describe the impact of COVID-19 on breast cancer screening and assess differences in health utilization by age group and health regions in Puerto Rico. Method(s): This study used data on breast cancer screening medical claims from Puerto Rico Track, a project in collaboration with the Puerto Rico Public Health System and the Puerto Rico Institute of Statistics that aims to assess health access and utilization patterns in Puerto Rico. Claims including unilateral and bilateral mammography, sonommamography, and MRI were analyzed. Descriptive statistics and percentual changes between the COVID-19 baseline year (2016) compared with 2020 and 2021 were performed (overall, by age-group and health region). Result(s): A total of 193,793 screening tests were performed in 2016, compared to 66,463 in 2020, and 89,322 in 2021. Overall, a third of the medical claims for breast cancer screening (33.2%) were in the age group of 51-60 years. An overall decreasing percentual change was observed comparing 2016 vs. 2020 (65.7%), where the age group with the broadest gap reduction were among women 41-50 years old (68.2%). When comparing medical claims of 2016 (193,750) versus 2021 (89,320) (pre and post pandemic), an important decreasing change (53.9%) was observed. The age group with the highest decrease comparing 2016 to 2021 was the 41-50 years one (68.2%). The Western region of Mayaguez/Aguadilla had the highest decreasing percentual change, with a reduction of 73.6% in 2020 compared to 2016, and 62.6% when compared 2021 with 2016. Conclusion(s): Breast cancer screening was notably affected by the COVID-19 pandemic in Puerto Rico. A pattern of decreasing breast cancer screening was observed by health regions and by age. These efforts provide evidence of the need of tailored evidence-based interventions to increase breast cancer screening in the island.
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Coronavirus disease (Covid-19) is an infectious respiratory disease caused by SARS-CoV-2. Among the symptoms, the respiratory system of the sufferer is affected. This respiratory condition suggests that the chest imaging plays a key role in the diagnosis of the disease. Several pre-trained deep learning models have been developed to detect Covid-19 through chest radiographs. These models provide high precision for binary detection, however, when combined with other diseases such as pneumonia that also affect the respiratory system and lungs, they offer poorer quality performance and reduce screening performance. In this study, we analyze some neural networks models for binary and multiclass classification of X-ray images in order to find out the best accuracy of classification. The models are based on deep learning methodology to learn and classify images. They are extracted from well-known repositories such as Kaggle. The conducted experiments compare their performance in several scenarios: a multiclass classification model versus the combination of several binary classification models. Two methods for combining the output of the binary models are proposed to achieve the best performance. The results show that the best results are obtained with a well-trained multiclass model. However, a preliminary screening can be obtained from the binary models without creating and training a more complex model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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CASE: A 40-year-old man with no significant past medical history presented with acute hypoxemic, hypercarbic respiratory failure and was diagnosed with COVID-19 pneumonia. He reported that he was unvaccinated against SARSCoV-2. Over the course of two months, he required high-flow nasal cannula, continuous then nocturnal BIPAP for respiratory support and completed appropriate courses of dexamethasone, remdesivir, and baricitinib. He also completed a course of levofloxacin due to concern for superimposed bacterial pneumonia. After finishing the course of dexamethasone, the patient was initiated on a prolonged prednisone taper. His course was complicated by the development of fibroproliferative acute respiratory distress syndrome two months after his initial diagnosis of COVID- 19 requiring continuous followed by nocturnal BIPAP to maintain adequate oxygenation. Subsequently, he developed recurrent bilateral, spontaneous pneumothoraces, which required the insertion of multiple chest tubes due to ongoing air leaks and continued recurrence on removal. IMPACT/DISCUSSION: Acute respiratory distress syndrome (ARDS) leads to diffuse alveolar damage in the lung and is increasingly being seen as a complication of COVID-19. These patients frequently require steroids along with positive pressure ventilation to maintain adequate oxygenation. Pneumothorax is a common and sometimes fatal complication of positive pressure ventilation in patients with acute respiratory distress syndrome, with some studies quoting an incidence as high as 48%. On the other hand, development of spontaneous pneumothorax in patients with COVID-19 pneumonia is much more rare, with studies showing an incidence of approximately 1% and usually upon the initiation of invasive mechanical ventilation, with collapse due to barotrauma in the setting of cystic and fibrotic changes in the lung parenchyma. However, there are no current case reports citing pneumothoraces as late complications of COVID-19 ARDS, as occurred in our patient two months into his hospitalization, and related solely to BiPAP use in a patient who never previously underwent endotracheal intubation or ventilation. Additionally, since corticosteroids delay wound healing, it is critical to recognize the possibility of developing spontaneous, recurrent pneumothoraces in patients with COVID-19 on prolonged steroid tapers who are initiating any form of positive pressure ventilation, including non-invasive ventilation such as BIPAP. CONCLUSION: Pneumothoraces are rare complications of COVID-19 pneumonia, and are most commonly seen in males who undergo endotracheal intubation. Corticosteroids delay wound healing, and prolonged steroid tapers increase the risk of recurrent pneumothoraces once one develops. Clinicians must be wary of this rare, late complication of patients with COVID-19 ARDS and prolonged steroid exposure and should be extra judicious with the use of positive pressure ventilation.
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The new current pandemic situation has meant that some previously unknown concepts have become part of our everyday language, as is the case with health areas. These are the demarcations for the distribution of health services, and their boundaries depend on broad criteria such as demographic, geographic, labor, epidemiological, road provisioning, or health facilities within them. But, from a planning perspective, what could be the minimum unit of confinement? What would be their characteristics and minimum services? What would be the appropriate criteria to define these units? The very experience lived during this pandemic, makes us reflect and put on the table the debate on the policies and action plans determined by the different governments from the perspective of the praxis of urbanism. From this experience, this study aims to reflect, from the perspective of urban planning, on the potential criteria best suited to the definition of minimum units of social confinement that can be included in the processes of urban planning and management. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The COVID 19 virus outbreak was the opportunity to assume new academic practices or adjust existing ones to the reality of the pandemic. This new reality led to change the learning strategies to assure the interest of the students in the virtual learning. The TPI (interdisciplinary project course) is subject based on the PBL (Problem-Based Learning) methodologic. In the Dynamic of the course take part 320 students, 20 teachers and 10 people in charge of the course administration. At the end of the course an event was made, it showed the result of about seventy projects. In this, the students recognized the importance of learning from interaction, improve their communication skills and interact with principal stakeholders who give feedback on the progress presented during the development of the course. The pandemic allowed the event was virtualized using a platform in which the students built their page and presented their ideas. The focus of this work is comparing the academic results and perception of the course by the students in terms of experience, the development of skills, and the achievement of the goals. The comparison was made by making a parallel between the face-to-face version and the virtual version giving importance to the use of Information and Communication Technologies (ICT) as an important part of the change. This analysis shows the differences and / or similarities based on the results of the last four semesters (years 2019 and 2020), This allowed to develop strategies for continuous improvement from teaching practice. © The authors, 2021.
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Purpose: The purpose of this paper is to present a discrete compartmental susceptible-asymptomatic-infected-dead (SAID) model to address the expansion of plant pests. The authors examined the case of Xylella fastidiosa in almond trees in the province of Alicante (Spain) to define the best eradication/contention protocol depending on the environmental parameters such as climatic factors, distance between trees, isolation of the plots, etc. Design/methodology/approach: This approach considers the expansion of the disease among the almond trees orchards by means of a grid model. The cells of the grid represent a tree (or even a group of trees) that can be susceptible (healthy), asymptomatic (infected by the bacterium but without symptoms), infected or dead. When time passes, the status of the cells is determined by binary rules that update following both a neighborhood and a delay pattern. The model assumes that the environmental parameters have a crucial impact on the expansion of the disease, so a grid is assigned to each parameter to model the single effect caused by this parameter. The expansion is then the weighted sum of all the grids. Findings: This proposal shows how the grid architecture, along with an update rule and a neighborhood pattern, is a valuable tool to model the pest expansion. This model has already been analyzed in previous works and has been compared with the corresponding continuous models solved by ordinary differential equations, coming to find the homologous parameters between both approaches. Thus, it has been possible to prove that the combination neighborhood-update rule is responsible for the rate of expansion and recovering/death of the illness. The delays (between susceptible and asymptomatic, asymptomatic and infected, infected and recovered/dead) may have a crucial impact on both the peak of infected and the recovery/death rate. This theoretical model has been successfully tested in the case of the dissemination of information through mobile social networks and is also currently under study in the case of expansion of COVID-19. Originality/value: This work develops a new approach for the analysis of expansion of plant pests. This approach provides both behavioral variability at the cell level (by its capability to modify the neighborhood and/or the update rule and/or the delays) and modularity (by easy scaling the number of grids). This provides a wide range of possibilities to deal with realistic scenarios. © 2020, Emerald Publishing Limited.