Stability and Hopf bifurcation analysis of a delayed SIRC epidemic model for Covid-19

This paper examines the spread of COVID-19 during the pandemic using the SIRC model and transmission delay. We investigated both the infection-free (E-0) and the infected (E-1) steady states are locally stable. We evaluated the duration of the delay for which the steadiness pursues to be maintained, by the Nyquist criterion. The Hopf bifurcation is used to explain the nature of the disease at the start of a 2nd cycle and the kinds of interventions needed to end it. Theoretical results are supported through numerical simulations.

Prediction of Covid-19 symptoms with chest x-ray to optimize the solution through the MCOA Algorithm for feature extraction and measurement

Due to poor understanding and inconsistent knowledge about covid-19 symptoms, the survival rate will decrease anywhere in the world. Every person who lives in the world should aware of COVID-19 symptoms to protect their life and hence increase the mortality rate of humans. The Indian government took precautions to lower the fatality rate, which includes hand sanitizer, wearing NS2 masks and keeping social distance to live a long life. The proposed method uses the MCOA-modified cat optimization algorithm to extract the image features and predict them in earlier stages and diagnosis. Furthermore, the proposed method clusters the chest image concerning size, shape and intensity concerning the irregular edges present in the chest imaging. The proposed MCAO algorithm cluster the chest image with an accuracy of about 95% and fit into the solution space with the state of art. The problem of the concave region present in the image is clustered in the solution space to delineate the parameters of pneumonia, fever, mucus fluid and respiration rate. The method gives the solution to the radiologist to detect earlier covid 19 symptoms for feature extraction and measurement

The Risk of COVID-19 in Patients of Chronic Kidney Disease with Cognitive Dysfunction Like Alzheimer Disease: A Perspective on Erythropoietin as a Potential Adjuvant Therapy

Background: The universal risk to mankind, coronavirus disease 2019 (COVID-19), shares etiological cofactors with a variety of diseases, including anemic chronic kidney disease patients (CKD) with cognitive dysfunction like Alzheimer disease (AD). Understanding the shared links between COVID-19 and CKD, as well as cognitive impairment such as AD, might aid in designing therapeutic ways to combat both. Given the need of developing COVID-19 medicine, the connection and symptoms of CKD with cognitive impairment have been reviewed here, with a focus on memory and learning disturbance. Objective(s): COVID-19 and CKD with cognitive dysfunction share angiotensin-converting enzyme 2 receptors, and AD indicators include amyloid, tau protein, and glycogen synthase kinase-3beta. Anemia in patients with CKD and pulmonary fibrosis is frequently treated with recombinant human erythropoietin (rHuEPO). Through nitric oxide stimulation, neuroprotection, and various organ hypoxias, rHuEPO promotes red blood cells (RBC) growth while also assisting oxygen delivery. Results and Conclusion(s): In COVID-19, rHuEPO may be advantageous. The common etiological variables and manifestations outlined in this review could aid in the development of therapeutic options for COVID-19 and CKD with cognitive impairment, such as AD, and so help to eliminate the ongoing universal risk. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Impact of coronavirus disease 2019 on head and neck urgent suspected cancer referral pathways in rural Wales.

OBJECTIVE: To assess the impact of the coronavirus disease 2019 pandemic on head and neck urgent suspected cancer referral pathways in rural areas of Wales. METHOD: A retrospective audit was conducted of 2234 head and neck urgent suspected cancer referrals received from January 2019 to November 2020. RESULTS: The referrals dropped by 35 per cent in 2020 compared to the same period in 2019. The time from general practitioner referral to the first ENT appointment improved during the pandemic (8.0 vs 10.0 days; p < 0.001). Of referrals, 92.1 per cent were seen within a 14-day period in 2020, compared with 79.6 per cent in 2019 (p < 0.001). There were no differences between 2020 and 2019 in terms of: the (confirmed cancer) conversion rate (10.6 per cent vs 9.7 per cent; p = 0.60), general practitioner referral to multidisciplinary team discussion time (35.5 vs 41.5 days; p = 0.40) or general practitioner referral to initiation of treatment time (68.0 vs 78.0 days; p = 0.16). CONCLUSION: Whilst coronavirus disease 2019 reduced the number of overall head and neck urgent suspected cancer referrals, the pathways were generally unchanged, if not slightly improved, in rural Wales.

Predictive Analysis of COVID-19 Symptoms with CXR Imaging and Optimize the X-Ray Imaging Using Segmentation Thresholding Algorithm-An Evolutionary Approach for Bio-Medical Diagnosis

Background and Objective: The concept of Too Close and Too Short spreads the virus simultaneously from one person to another person. The radiologist investigates to prevent the spreading of the virus in the earlier stage of diagnosis and predict the symptoms in the beginning stage. The objective of the study is to predict the virus in the earlier stage and diagnose it so that the mortality rate is reduced. Hence, the virus-infected person lives a healthier life. Materials and Methods: The Chest X-ray imaging segments the image concerning edge detection (with and without contour detection) for earlier identification and prediction of COVID-19 symptoms. The segmentation thresholding algorithm accurately detects the parameters of fever, pneumonia and mucus fluid in earlier predictions. Moreover, the segmentation thresholding algorithm automatically classifies with the prediction of COVID-19 symptoms in pixel shape, size and intensity. Extraction of image features for pixel size, shape and intensity for feature enhancement and measurement. Results: Validation of segmentation thresholding algorithm improves with high accuracy in Chest X-ray imaging. The predictive analysis of CXR imaging to Accuracy, Precision, F-measure and Recall accurately enhanced with symptoms of COVID-19 in an earlier stage. The future study of the proposed method detection of COVID-19 symptoms is predicted in the earlier stage can be diagnosed automatically. Conclusion: Detection of COVID-19 symptoms in earlier stage processed through CXR imaging via Automatic Segmentation Threshold Algorithm clusters the pixel concerning contour and non-contour edge detection. The accuracy detection of contour and non-contour edge detection extract the image feature 90% of the original enhanced image.

TEAM BASED, RISK ADJUSTED STAFFING DURING A PANDEMIC: AN AGENT BASED APPROACH

Since the World Health Organization declared the novel coronavirus disease a pandemic, more than 2 million cases of infections and 140,000 deaths have been reported across the world. Specialty physicians are now working as frontline workers due to hospital overcrowding and a lack of providers, and this places them as a high-risk target of the epidemic. Within these specialties, anesthesiologists are one of the most vulnerable groups as they come in close contact with the patient's airway. An agent-based simulation model was developed to test various staffing policies within the anesthesiology department of the largest healthcare provider in Upstate South Carolina. We demonstrate the benefits of a restricted, no mixing shift policy, which segregates the anesthesiologists as groups and assigns them to a shift within a single hospital. Results consistently show a reduction in the number of deaths, anesthesiologists not available to work, and the number of infected anesthesiologists.

Drivers and barriers to information seeking: Qualitative research with advanced cervical cancer patients in the United States

Background: Patients diagnosed with persistent, recurrent, or metastatic cervical cancer (CC) may face uncertainty about treatment options, impact of treatment on health & quality of life (QoL), & available resources. This study provides insight into patient concerns & information seeking (IS) behaviors. Methods: In January 2021, semistructured telephone interviews were conducted in the US with CC patients (diagnosed within 2 years) recruited through panels, social media & advocacy groups. The interview focused on rational & emotional drivers and barriers for IS. Transcripts were coded using NVivo qualitative analysis software to identify key themes. Results: 14 women of varied education status were interviewed (mean age 51 years (range: 37-70);8 White, 4 Black, & 2 Latina). Patients emphasized trust in their oncologist to provide sufficient information. IS was driven by the desires to confirm their oncologist's recommendation & find reassurance through the experience of other patients, and encouragement from family. Barriers to IS included: 1) hesitancy to undermine their oncologist's recommendations, 2) pessimism about ability to find individualized answers about prognosis or QoL, 3) feeling overwhelmed & fearing misinformation, 4) personal urgency to decide on a treatment plan, 5) already having sufficient information, 6) potential exposure to 'negative energy' from online patient communities, & 7) COVID-19 hindering opportunity for personal connections. Conclusions: While patients' oncologist, family, & common patient experience provide comfort, reluctance towards IS exists. As trusted gatekeepers, oncologists should recognize patients' desire for accessible, reliable, & personalized information. Better understanding this perspective and gaps in the availability of validated & relevant resources can enable clinicians/policy makers to develop strategies & tools for better communication. In turn, this will help CC patients feel more empowered & informed throughout their cancer care journey.

Chronic periodontal disease and COVID - 19 complications: Mechanistic links through increase of CD14+ CD16+ monocytes blood count

Introduction: It is well known that the SARS-CoV-2 virus that causes COVID-19 could enter the human host through the oral cavity. In patients with periodontal disease, there is an increase of Furin, Cathepsin, and CD14+ CD16+ monocytes. The hypothesis stated here sheds light on the regular need of periodontal management to reduce inflammation and the levels of deleterious host enzymes and cytokines, which could pave the way for deadly viral diseases such as COVID-19. The Hypothesis: Patients with periodontal disease are at increased risk of SARS-CoV-2 infection due to elevated levels of Furin and Cathepsin in oral cavity and COVID-19 complications like cytokine storm could occur with increased frequency in patients with periodontal disease due to the significant increase of CD14+ CD16+ monocytes in blood. Evaluation of the Hypothesis: Oral and periodontal examination of patients with mild, moderate, and severe SARS-CoV-2 infection could shed light on the significant role played by periodontal disease in making an individual more prone to get SARS-CoV-2 infection by elevation of Furin and Cathepsin and the elevation of CD14+CD16+ monocytes and proinflammatory cytokines in the blood that could consequently worsen COVID-19 complications like cytokine storm. The blood counts of CD14+CD16+ monocytes need to be assayed in SARS-CoV-2 patients with and without periodontal disease to observe if periodontal disease as a coexisting condition elevates the proportion of CD14 CD16 + monocytes in SARS-CoV-2 patients. In fact, assessment of monocyte subsets in peripheral blood could be used as an immunosurveillance marker in SARS-CoV-2 patients. Hence, SARS-CoV-2 positive patients with chronic periodontal disease should be closely monitored for potential signs of a cytokine storm and its related complications. © 2021 Dental Hypotheses ;Published by Wolters Kluwer - Medknow