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Introduction: The Coronavirus disease-19 (COVID-19) pandemic mediated by Severe Acute Respiratory Syndrome-CoV2 (SARS-CoV2), made the use of face masks mandatory to check the spread of the disease. With the increased use of face masks, more people started presenting to the ophthalmologist with symptoms of dry eye. The proposed mechanism of dry eye was attributed to air blowing upwards from behind the mask into the eyes, especially in loose fitting masks. This air leads to rapid evaporation of tears and disturbance of homeostasis of the tear film.Aim: To measure self reported symptoms of dry eye and to establish mask use as a risk factor for the development of Dry Eye Disease (DED) in healthcare workers in a Tertiary Care Hospital.Materials and Methods: This cross-sectional, observational study was conducted at Nilratan Sircar (NRS) Medical College and Hospital for a duration of three months from December 2021 to February 2022. The study was conducted on 146 participants. An online survey was conducted using Google Forms, sent via email to hospital employees working in different departments of the hospital. All healthcare workers employed at NRS Medical College and Hospital who wore a face mask during duty hours and were willing to participate in the study were included. The Ocular Surface Disease Index (OSDI) questionnaire was used and modified by adding "while wearing a facemask" to the end of each question. To establish face mask use as a causative agent for development of DED, a few other questions related to face mask usage were included in the survey. The data was tabulated in Microsoft Excel and analysed with Statistical Package for Social Sciences (SPSS) version 24. Results: The mean age of the study population was 27.4+/-8.28 years. The mean hours of wearing a mask was 6.38+/-3.04 hours. N95 face mask was the most common type of mask used. The study population included 100 doctors, 14 nursing staff, 18 optometrists, eight group D staff (sweepers and ward attendants), and six dieticians. The mean OSDI score was 14.24. Increased usage of face masks, in particular surgical, more hours of reading significantly correlated with higher incidence of DED. Conclusion: This study showed that increased hours of face mask use in particular surgical was associated with development of DED. To encourage more people to wear face masks, all possible problems arising from face mask use should be promptly identified and dealt with.
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Vaccine hesitancy was found to be one of the top ten global health threats in 2019 by World Health Organization. Worldwide, more than 90% of countries have encountered vaccine hesitancy, which has notably jeopardized the implementation of vaccination campaigns. Some of the factors associated with COVID-19 vaccine hesitancy can be lack of confidence in information or lack of adequate information about the vaccine, misinformation from social media, and a fear of side effects. Widespread acceptance of COVID-19 vaccines is extremely crucial in order to achieve sufficient immunization coverage to end this global pandemic. It is evident that the number of studies that have investigated COVID-19 vaccination attitudes in lower-income countries like India is quite low. We analyze COVID-19 vaccine acceptance and hesitancy in Indian Scenario using the Twitter social media platform to ensure that these vaccines reach even the remotest of places, whether rural or urban, in India, while observing the results and outcomes of our research. We aim for accurate results and hope to help the Indian government in the process of making informed decisions for the vaccine-hesitant groups of India. © 2023 selection and editorial matter, Dr. R. Dhaya and Dr. R. Kanthavel;individual chapters, the contributors.
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As the rate of natural disasters and other devastating events caused by human activities increases, the burden on the health and well-being of those affected by kidney disease has been immeasurable. Health system preparedness, which involves creating a resilient system that is able to deal with the health needs of the entire community during times of unexpected disruptions to usual care, has become globally important. In the wake of the COVID-19 pandemic, there is a heightened awareness of the amplification of negative effects on the renal community. Paradoxically, the complex medical needs of those who have kidney diseases are not met by systems handling crises, often compounded by an acute increase in burden via new patients as a result of the crisis itself. Disruptions in kidney care as a result of unexpected events are becoming more prevalent and likely to increase in the years to come. It is therefore only appropriate that the theme for this year's World Kidney Day will focus on Kidney Health for All: preparedness for the unexpected in supporting the vulnerable. © 2023 JSC Vidal Rus. All rights reserved.
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Background: Atrial fibrillation (AF) is the most common arrhythmia in the United States. Concomitant Covid-19 infection and the outcomes of AF are unknown. Objective(s): The study's goals were to analyze the outcomes of AF during the Covid-19 pandemic. Method(s): We conducted a retrospective cohort study based on the 2020 National Inpatient Sample (NIS) of Adults (>18 years) hospitalized for AF as the primary admitting diagnosis based on the ICD-10 codes and stratified these groups into concomitant covid-19 infection vs. non-covid-19 infection. All-cause mortality was our primary outcome, while the rate of ICU admission, length of stay, hospital charges were our secondary outcomes. Temporal trends were assessed using logistic regression. Result(s): In 2020, there were 1,994,985 admissions for atrial fibrillation, out of whom 104,495 (5.3%) had concomitant Covid-19. In the 104,495 AF admissions with covid-19, the mean age was 75y and 56.8% were males. Our results, image 1, showed AF with and without concomitant Covid-19 had similar rates of comorbid conditions including HTN, DM, OSA, CAD. HFrEF, and ESRD. AF patients with Covid-19 infection had a lower prevalence of smoking (31.83% vs. 39.4%, p<.001) and alcohol use (2% vs. 4.2%, p<.001). AF patients from both groups had similar rates of stroke (1.6% vs. 1.0%, p<.001). New AF patients with concomitant Covid-19 had worsening in-hospital outcomes such as shock (12.8% vs. 3.7%, p<.001), admission to the ICU (18.1% vs. 6.4%, p<0.001), higher all-cause mortality (21.8% vs. 3.9%, p<0.001), a longer length of stay (9.96 days vs 6.08 days, p<.001), and total hospital costs ($114,387 vs. $85,830, p<.0001). The incidence of AF catheter ablation on initial hospital admission for AF Covid-19 was lower compared to the AF non-covid-19 patients (.08% vs. 1.39%, p<.001). Conclusion(s): In 2020, Covid-19 infection was an independent predictor of higher all-cause mortality, length of stay, and costs in patients admitted for atrial fibrillation. In addition, these patients were less likely to get catheter ablation on hospital admission. [Formula presented]Copyright © 2023
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Problem: Despite being over 3 years into the pandemic, infants remain highly undervaccinated and at a high risk for hospitalization due to COVID-19. Further investigation as to how maternal health decisions for immunization can reduce morbidity from infant COVID-19 by providing passive immunity is necessary. The objective of this study was to describe the rates of SARS-CoV-2 variant antibody transfer from mother to infant cord blood by trimester ofmaternal vaccination. Methods of study: This is an observational cohort study including mother-infant dyads receiving primary or subsequent booster COVID- 19 vaccines during pregnancy.Unvaccinated, but SARS-CoV-2 infected dyads with were included as a comparison group. We quantified median titer and interquartile range (IQR) for SARS-CoV-2 receptor binding domain (RBD) IgG in infant cord blood samples at delivery using the mesoscale discovery platform (electrochemiluminescence). Primary outcome was infant cord IgG titer by trimester of vaccination for the WA1/2022 RBD IgG and current circulating, immune evasive XBB RBD IgG. Secondary outcome is the percent detectable IgG for each variant. Sensitivity analysis was performed based on known SARS-CoV-2 infection. Result(s): Eighty-three mother-infant dyads were included in this analysis. Seven were vaccinated in the first trimester, 37 in the second trimester, 33 in the third trimester, and 6 were unvaccinated and infected. Twenty-three (30%) of the vaccinated group had known SARS-CoV-2 infection. Most received monovalent mRNA COVID-19 vaccines during pregnancy, aside from two who received the viralvectored Ad26.COV2.S, and two received the bivalent mRNA vaccine during pregnancy. The median cord blood WA1/2020 RBD IgG titer was 5370 (412-7296) for first, 1225 (589-3289) for second, 2623 (664-5809) for third trimester in individuals who received aCOVID-19 vaccine dose during pregnancy, and 45 (10-187) in those unvaccinated and infected. After excluding thosewith infection, the cord blood IgG was 514 (106-4182), 1070 (518-2317), and 2477 (664-4470) for first, second, and third trimester, respectively. The rate of detectable WA1/2020 RBD IgG was 100% for all three trimesters, even when excluding infected individuals. For theXBBvariant, cord bloodRBDIgG titer was 284 (43-1296) for first, 66 (32-227) for second, 173 (45-389) for third trimester, and 10 (10-11) in the unvaccinated/infected group. Excluding infections, the cord blood XBB RBD IgG was 54 (10-128), 44 (25-181), and 152 (45-360) for first, second, and third trimester vaccination, respectively. The rate of detectable XBB IgG in those who received a vaccine during pregnancy were 83%, 91%, and 90% for first, second, and third trimester respectively, compared to 17% in the unvaccinated/infected group. Excluding infections, the rate of XBB RBD IgG detection was 66%, 89%, and 95% for first, second, and third trimester vaccination, respectively. Conclusion(s): Vaccination during pregnancy leads to high rates of detectable cord blood IgG specific to SARS-CoV-2 WA1/2020 variant and current circulating variants (XBB), regardless of trimester of vaccination. Infection history leads to higher cord blood IgG in vaccinated;however, infection alone without vaccination leads to lower titer and greater rates of undetectable cord IgG at delivery.
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Aims: This questionnaire-based survey was designed to assess the acquaintance, apprehension, and perceptions of parents toward the COVID-19 pandemic and toward seeking dental care for their children in Visnagar, Gujarat, India. Settings and Design: This was a questionnaire-based cross-sectional study. Subjects and Methods: The online Google survey form included 6 units with 27 close-ended questions in twin languages (regional and English). Inquiries covered demographics, changes in daily acts, dietary traditions, and preparedness to seek child oral care during November 2020 to January 2021. Results: Out of 400 parents, 172 responded to the electronic survey form. Over half of the guardians affirmed that alveolar treatment could fan out COVID-19. Around 90% resorted to medication (self-medication - 39%, home remedies - 32.6%, and teledentistry - 17.4%) to evade personal dental visits for their children. Conclusions: The awareness about COVID-19 and precautions was significantly high. Though parents were unaware about safeguards practiced by dentists during Covid19. Measures were taken to correct misconceptions among parents about safe dental procedures.
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This work is devoted to studying the transmission dynamics of CoV-2 under the effect of vaccination. The aforesaid model is considered under fractional derivative with variable order of nonsingular kernel type known as Atangan-Baleanue-Caputo (ABC). Fundamental properties of the proposed model including equilibrium points and R0 are obtained by using nonlinear analysis. The existence and uniqueness of solution to the considered model are investigated via fixed point theorems due to Banach and Krasnoselskii. Also, the Ulam-Hyers (UH) approach of stability is used for the said model. Further numerical analysis is investigated by using fundamental theorems of AB fractional calculus and the iterative numerical techniques due to Adams-Bashforth. Numerical simulations are performed by using different values of fractional-variable order ?(??) for the model. The respective results are demonstrated by using real data from Saudi Arabia for graphical presentation.
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The COVID-19 pandemic has dramatically altered the workplace. It drove a mass social experiment in working from home. To mitigate the spread of the virus and protect employees, many companies shifted to remote work with video calls and instant messaging replacing in-person meetings. Several studies have shown that working from home boosted worker productivity, with the reduction in commuting time being the greatest contributing factor;thus, it will stick in the post-pandemic economy. In addition, studies have also shown that there is an increase in the number of people wanting to work remotely. However, choosing to work remotely can affect people's budgets. For instance, working from home reduces transportation costs but many remote workers have seen an increase in their energy bills. In addition, many remote workers paid for home office setup on their own. This study analyzes the overall benefit and disbenefit of working from home and performs an economic analysis of working from home for an individual. Copyright, American Society for Engineering Management, 2022.
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In this work, we present a model that uses the fractional order Caputo derivative for the novel Coronavirus disease 2019 (COVID-19) with different hospitalization strategies for severe and mild cases and incorporate an awareness program. We generalize the SEIR model of the spread of COVID-19 with a private focus on the transmissibility of people who are aware of the disease and follow preventative health measures and people who are ignorant of the disease and do not follow preventive health measures. Moreover, individuals with severe, mild symptoms and asymptomatically infected are also considered. The basic reproduction number (R0) and local stability of the disease-free equilibrium (DFE) in terms of R0 are investigated. Also, the uniqueness and existence of the solution are studied. Numerical simulations are performed by using some real values of parameters. Furthermore, the immunization of a sample of aware susceptible individuals in the proposed model to forecast the effect of the vaccination is also considered. Also, an investigation of the effect of public awareness on transmission dynamics is one of our aim in this work. Finally, a prediction about the evolution of COVID-19 in 1000 days is given. For the qualitative theory of the existence of a solution, we use some tools of nonlinear analysis, including Lipschitz criteria. Also, for the numerical interpretation, we use the Adams-Moulton-Bashforth procedure. All the numerical results are presented graphically. © 2023 Tech Science Press. All rights reserved.
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As we see coronavirus is the very dangerous diseases and to identify this diseases in one's body is also not as easy. So during identification of diseases there are many false positive cases we see that person does not have corona and still the prediction comes true and also in some cases, it happens that person has corona but it does not get detected (false negative case). So due to this problem, we here come up with the two approaches and make comparison between these two approaches and decide which one is better to analyze the diseases in the body. We are using CNN to scan chest X-ray dataset and ML algorithms for tabular dataset as it contains many text information too. So in this project, we explain in detail, what is CNN, what is ML, how to implement CNN and ML algorithms on particular dataset, what output we will get as a comparison. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Background: Evaluation of the impact of stress on glycaemic control in hospitalized type-2 diabetes (T2DM) patients with coronavirus disease (COVID-19). Methods: In this retrospective study conducted at a single centre in Maharashtra from May to July 2020 on hospitalized COVID-19 patients with T2DM who reported having stress of pandemic;they were selected using purposive sampling. DASS-12 stress sub-scale was used to estimate the severity of their stress. Fasting blood glucose (FBG) and post-prandial blood glucose (PPBG) before admission and at the time of discharge were compared. Results: One hundred and ninety-nine patients (mean age 54 years;61.30% females) were included. Mean±SD FBG before admission was 168.4±30.6 mg/dl which increased to 195.9±28.8 mg/dl at the time of discharge (P<0.001). Also, Mean±SD PPBG before admission was 312±62.3 mg/dl which increased to 351.6±61.9 mg/dl (P<0.001). A total of 73 (36.7%) participants had perceived stress. Moderate and severe/extremely severe stress was found in 44 (27.1%) and 19 (9.6%) patients, respectively. A significant difference was observed in the mean FBG before and during discharge in patients who had no stress and those with moderate stress (P<0.001). There was no difference in FBG in patients with severe/extremely severe stress (P=0.43). Similar observations were seen for PPBG (no stress P<0.001;moderate stress P<0.001;severe/extremely severe stress P=0.06). Conclusion: There was a rise in the glucose level in T2DM patients discharged after COVID-19 treatment. The increase was significant in T2DM without stress and those with moderate stress. In addition to traditional treatment, measures for psychological stress control should also be taken for such patients. © 2022 The authors.
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The Global Automotive Aftermarket sector was valued at USD 392.5 billion in 2020 and is predicted to surpass USD 525 billion by 2028. The automotive aftermarket of the United Arab Emirates, led by Dubai, is the fastest-growing market, which is expected to reach USD 634.4 million. However, the Covid-19 pandemic diminished the growth rate and profitability of the sector, pressing small and medium enterprises to reduce their costs, including employees' remuneration. This empirical paper aims to analyse the impact of changes in salesforce remuneration on sales turnover and the role of Covid-19 in influencing this causal relationship. The data, before Covid (2019) and during Covid (2020-21), were collected from 80 automotive aftermarket enterprises in Dubai using a single-stage convenience sampling method. The correlation analysis and ANOVA test highlight the significant difference in sales commission within the group and between the groups caused by Covid-19. The results indicate how the reduction in remuneration, especially sales commission, during the crisis significantly declined the sales turnover in automotive aftermarket enterprises. The study proposes guidelines and tips that business leaders, the human resources professionals can implement to revive their sales turnover post-Covid-19 and manage such crises in future. © 2022, Czestochowa University of Technology. All rights reserved.
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BACKGROUND: Payer characteristics is rapidly changing for dialysis in India. Public partnership is a an evolving model with its set unique challenges for patients and providers. An understanding of variance will help address the gaps in the health system AIM OF THE STUDY: 1. To compare difference in patient center and dialysis characteristics between PPP and non-PPP centers 2. To assess gaps in health system for planning and improvement METHODS: 797 Non-COVID deaths that occurred in large dialysis network between Jan and Mar 2021 were compared to age matched controls to study factors influencing mortality: gender educational status BMI duration of HD center size for staff and patient numbers payer type HD frequency access Hb S. Albumin diabetic status Htn h/o heart failure and h/o hospitalization. A multivariate analysis identified factors influencing mortality. In a sub-analysis of this study, we compared characteristics across centers under public-private partnership (PPP) and non-PPP of above characteristics and learn salient differences. RESULT(S): a. Comparison of patient, center, HD characteristics (mean + sd) PPP (n = 715). Non-PPP (n = 869). p value Age (yrs) 52 + 12.7 56.9 + 13.8 < .001 Height (cm) 160 + 9.5 161.7 + 9 < . 001 Weight (Kg) 57.7 + 11.7 59 + 12.4 .02 BMI 22.5 + 4.3 22.6 + 4.8 .63 Distance (km) 30. 8 + 34.8 30.7 + 10 <.001 No of staff 22.1 + 23.4 18.3 + 15.5 <.001 No of patients 22.1 + 21.3 15.7 + 11.3 <.001 HD (Months) 16.8 + 16.8 18.2 + 18.2 .08 HB (g%) 8.5 + 1.5 9.1 + 1.6 <.001 Adequacy 1.2 + .1 1.3 + .2 .003 Alb (g%) 3.5 + .7 3.5 + .5 . 17 b. Comparison of proportions of patient characteristics (as %) PPP Non-PPP p value Non-survivor: Survivor 59.6/40.4 41.4/58.5 <.001 Perm/Tem 75.9/24.1 75/25 .67 Gender M 74.7/25.3 68.1/31.9 .04 Educ: < College/College 89.4/10.6 69.7/30.3 <.001 HD frequency < /> 2x 51.8/49.8 66.3/31.1 <.001 Diab: Non-diabetic 24.9/75.1 44.8/552 <.001 Heart failure: Y/N 6.7/93.3 10.9/89.1 .004 Hospitalization: Y/N 16.1/83.9 31.1/68.9 <.001 CONCLUSION(S): Patients in PPP centers are younger and more likely to be men and shorter in height, less educated. They are more anemic, dialyzed thrice with lesser proportion who have diabetes and heart failure. Centers are less accessible and larger in size. Understanding these differences will help health systems direct more customized patient-centric interventions to improve outcome.
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INTRODUCTION: COVID-19-related organ dysfunction is increasingly recognized as sepsis of viral origin and is a common complication among those requiring hospitalization, with estimated prevalence of over 50% among the latter. However, the population-level association of COVID-19 with short-term mortality among septic patients is unknown. METHOD(S): We used a statewide dataset to identify hospitalizations aged >=18 years with sepsis in Texas during April 1-December 31, 2020. Sepsis was defined by "explicit" and ICD-10 codes for severe sepsis (R65.20) and septic shock (R65.21) and COVID-19 by ICD-10 code U07.1. A hierarchical, mixed-effects model was fit to estimate the association of COVID-19 with short-term mortality (defined as in-hospital death or discharge to hospice) among sepsis hospitalizations. Sensitivity analyses of the sepsis hospitalization subsets with septic shock and ICU admission were performed using a similar modeling approach. RESULT(S): Among 55,145 sepsis hospitalizations, 13,149 (23.8%) had COVID-19. Compared to those without COVID-19, sepsis hospitalizations with COVID-19 were younger (aged >=65 years 53.6% vs 55.0%), more commonly male (59.5% vs 50.4%) and racial/ethnic minority (66.1% vs. 46.2%), with lower burden of chronic illness (mean [SD] Charlson comorbidity index 1.8 [1.9] vs 2.8 [2.6]), but with higher mean [SD] number of organ dysfunctions (3.1 [1.4] vs 2.7 [1.6]) [p < 0.0001 for all comparisons]. Short-term mortality among sepsis hospitalizations with and without COVID-19 was 52.7% vs 30.2%, respectively. On adjusted analysis, COVID-19 remained associated with higher risk of short-term mortality (adjusted odds ratio [aOR] 2.54 [95% 2.39-2.70]), with findings on sensitivity analyses consistent with the primary model among sepsis hospitalization subsets with septic shock ([aOR] 2.70 [95% 2.51-2.91]) and ICU admission ([aOR] 2.67 [95% 2.30-3.10]). CONCLUSION(S): COVID-19 infection was associated with over 250% higher odds of short-term mortality among septic patients. Additional studies are needed to determine the mechanisms underlying these observations in order to inform future efforts to reduce the observed outcome disparities.
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INTRODUCTION: The adverse impact of comorbid conditions on the development of severe illness and risk of death among hospitalized patients with COVID-19 has been well-documented. However, the population-level epidemiology and outcomes of previously healthy [PH] adults compared to those with prior comorbidities [PC] among COVID-19 patients requiring ICU admission are unknown. METHOD(S): We used a statewide dataset to identify hospitalizations aged >=18 years with ICU admission and a diagnosis of COVID-19 in Texas during April 1-December 31, 2020. COVID-19 was defined by ICD-10 code U07.1. PH was defined as absence of the comorbidities included in the Charlson Comorbidity Index, and of obesity, malnutrition, mental disorders, and substance and alcohol use disorders. A hierarchical, mixed-effects model was fit to estimate the association of PH with short-term mortality (defined as in-hospital death or discharge to hospice) among ICU admissions. A similar approach was used to identify predictors of short-term mortality among the PH group. RESULT(S): Among 58,845 ICU admissions with COVID-19, 6,760 (11.6%) were PH. Compared to those with PC, those with PH were younger (aged >=65 years 36.1% vs 49.4%), more commonly racial/ethnic minority (63.8% vs 61.5%), and with lower mean [SD] number of organ dysfunctions (1.2 [1.1] vs 1.8 [1.4]) [p< 0.001 for all comparisons]. Short-term mortality was lower among PH than among PC (16.4% vs 25.0%). However, following adjustment for confounders, the risk of short-term mortality was higher among PH (adjusted odds ratio [aOR] 1.37 [95% CI 1.25-1.51]). Among PH ICU admissions, short-term mortality increased with age ([aOR] 35.20 [95% CI 22.09-56.09];>=65 vs 18-44 years) and management at facilities with >=50 ICU beds ([aOR] 4.43 [95% CI 1.07-18.32] vs < 10 ICU beds). CONCLUSION(S): PH was uncommon among critically ill adults with COVID-19 and PH patients had substantially lower short-term mortality than those with PC. However, once risk-adjusted, the odds of short-term mortality were, unexpectedly, 37% higher among PH, with the latter facing higher risk of death when managed at hospitals with higher number of ICU beds. Additional studies are needed to identify the patient-, care process-, and health system-related contributors to these findings.
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Objectives: Adolescents are vulnerable populations at risk for mental health disorders due to physical, social, and educational transitions and need to be assessed seriously, especially after the recent COVID-19 pandemic. We aim to understand and identify irritability at a preschool age as a predictor of developing psychopathology later in adolescence. Method(s): A literature search was conducted using relevant Medical Subject Headings (MeSH) keywords in PubMed, MEDLINE, and PubMed Central databases. We identified all relevant published articles from inception until March 31, 2021. Out of 99 studies applied, 19 studies were chosen for full-text review when inclusion and exclusion criteria were applied. After a full-text review, we included 6 relevant studies in our final qualitative synthesis review. Result(s): The results of the studies showed an association between preschool irritability and mental health outcomes later in life. A 2019 study showed that irritability in preschoolers predicted later diagnosis of mood and externalizing disorders when controlled for social adversity, maternal history of mood disorders, and externalizing diagnoses at baseline. Irritability early in childhood predicted mania later in life (OR = 1.99;95% CI, 1.19-3.37;p =.009), and the OR of later being diagnosed with depression was 3.11 (95% CI, 1.32-3.27;p =.002) for each point increase in irritability factor score. Results further indicated that high stable irritability in early childhood is a predictor of irritability at age 12 (r =.35;p <.001). A 2021 study reproduced the results showing that preschool irritability predicted internalizing and externalizing comorbidity (OR = 1.67;95% CI, 1.22-2.28;p =.001). Conclusion(s): The findings show that irritability in preschool children is a predictor of internalizing, externalizing, and other behaviors later in life. It indicates an association between preschool irritability and psychopathology later in adolescence. A large-scale well-structured randomized controlled trial is recommended to unearth the potential benefit of identifying irritability in early life. ADOL, IMD, PSC Copyright © 2022
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This article is devoted to investigate a mathematical model consisting on susceptible, exposed, infected, quarantined, vaccinated, and recovered compartments of COVID-19. The concerned model describes the transmission mechanism of the disease dynamics with therapeutic measures of vaccination of susceptible people along with the cure of the infected population. In the said study, we use the fractal-fractional order derivative to understand the dynamics of all compartments of the proposed model in more detail. Therefore, the first model is formulated. Then, two equilibrium points disease-free (DF) and endemic are computed. Furthermore, the basic threshold number is also derived. Some sufficient conditions for global asymptotical stability are also established. By using the next-generation matrix method, local stability analysis is developed. We also attempt the sensitivity analysis of the parameters of the proposed model. Finally, for the numerical simulations, the Adams-Bashforth method is used. Using some available data, the results are displayed graphically using various fractal-fractional orders to understand the mechanism of the dynamics. In addition, we compare our numerical simulation with real data in the case of reported infected cases. © 2022 Kamal Shah et al.
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As we see coronavirus is the very dangerous diseases and to identify this diseases in one’s body is also not as easy. So during identification of diseases there are many false positive cases we see that person does not have corona and still the prediction comes true and also in some cases, it happens that person has corona but it does not get detected (false negative case). So due to this problem, we here come up with the two approaches and make comparison between these two approaches and decide which one is better to analyze the diseases in the body. We are using CNN to scan chest X-ray dataset and ML algorithms for tabular dataset as it contains many text information too. So in this project, we explain in detail, what is CNN, what is ML, how to implement CNN and ML algorithms on particular dataset, what output we will get as a comparison. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Introduction: Adults living with disability comprise over 25% of the U.S. adult population and suffer from an increased risk of developing associated conditions, frequently in the form of mental illness and substance use. Adults in this subgroup report depression and anxiety, decreased access to healthcare, and increased health-risk behaviors compared to the general population, making them a high-risk population for substance addiction, mental health deterioration, and overall susceptibility to infection during COVID-19. In order to better elucidate upon associations of comorbidities for disabled American adults, the COVID-19 Outbreak Public Evaluation (COPE) Initiative performed a self-reported cross-sectional survey study to screen for substance use, mental health, and healthcare access in this population since the COVID-19 pandemic began. Method(s): In the period between February 16, 2021 to March 8, 2021, the 8,475 eligible adults sampled to match the 2019 US Census were invited to respond to an electronic survey to screen for disability, symptoms of anxiety and depression, suicidal ideation, pre-pandemic and past month substance use, and access to healthcare during the pandemic. Informed consent was provided electronically by respondents. Result(s): Out of 5119 respondents, or 62.1% of the adults surveyed, 32.2% reported living with at least one disability. Of these individuals, 38.8% reported new or increased substance use, 56.6% reported symptoms of depression/anxiety, and 30.6% reported severe suicidal ideation. Of the respondents who did not report a disability, 17.5% reported new or increased substance use, 28.7% reported symptoms of depression/anxiety, and 8.3% reported severe suicidal ideation. Further analysis of data revealed that adults with disabilities reported increased alcohol use compared to non-disabled respondents and nearly twice the past-month usage of substances like methamphetamines, non-opioid prescription drugs, and marijuana. Past month usage of substances like cocaine and illicit opioid use was found to have an even more significant difference, being nearly three times greater compared to adults who didn't report a disability. Discussion(s): This study establishes new screening data from disabled and non-disabled US adults during the COVID-19 pandemic. It shows a clear disparity in nearly all categories of substance use and mental health outcomes, highlighting the vulnerability of this patient population amid the ongoing global pandemic. Increasing clinician access to prescription drug surveillance programs, patient counseling, and accessibility of substance use care and mental health resources for disabled Americans will serve crucial in mitigating this trend of negative public health outcomes.