Design and Development of IoT and Deep Ensemble Learning Based Model for Disease Monitoring and Prediction.

With the rapidly increasing reliance on advances in IoT, we persist towards pushing technology to new heights. From ordering food online to gene editing-based personalized healthcare, disruptive technologies like ML and AI continue to grow beyond our wildest dreams. Early detection and treatment through AI-assisted diagnostic models have outperformed human intelligence. In many cases, these tools can act upon the structured data containing probable symptoms, offer medication schedules based on the appropriate code related to diagnosis conventions, and predict adverse drug effects, if any, in accordance with medications. Utilizing AI and IoT in healthcare has facilitated innumerable benefits like minimizing cost, reducing hospital-obtained infections, decreasing mortality and morbidity etc. DL algorithms have opened up several frontiers by contributing towards healthcare opportunities through their ability to understand and learn from different levels of demonstration and generalization, which is significant in data analysis and interpretation. In contrast to ML which relies more on structured, labeled data and domain expertise to facilitate feature extractions, DL employs human-like cognitive abilities to extract hidden relationships and patterns from uncategorized data. Through the efficient application of DL techniques on the medical dataset, precise prediction, and classification of infectious/rare diseases, avoiding surgeries that can be preventable, minimization of over-dosage of harmful contrast agents for scans and biopsies can be reduced to a greater extent in future. Our study is focused on deploying ensemble deep learning algorithms and IoT devices to design and develop a diagnostic model that can effectively analyze medical Big Data and diagnose diseases by identifying abnormalities in early stages through medical images provided as input. This AI-assisted diagnostic model based on Ensemble Deep learning aims to be a valuable tool for healthcare systems and patients through its ability to diagnose diseases in the initial stages and present valuable insights to facilitate personalized treatment by aggregating the prediction of each base model and generating a final prediction.

SARS CoV-2 spike protein variants exploit DC-SIGN/DC-SIGNR receptor for evolution and severity: an in-silico insight.

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is related with the COVID-19 pandemic. Recent spike protein variations have had an effect on the transmission of the virus. In addition to ACE-2, spike proteins can employ DC-SIGN and its analogous receptor, DC-SIGNR, for host evasion. Spike variations in the DC-SIGN interaction region and role of DC-SIGN in immune evasion have not been well defined. To understand the spike protein variations and their binding mode, phylogenetic analysis of the complete GISAID (Global Initiative for Sharing Avian Influenza Data) data of the SARS-CoV-2 spike protein was considered. In addition, an in silico knockout network evaluation of the SARS-CoV-2 single-cell transcriptome was conducted to determine the key role of DC-SIGN/R in immunological dysregulation. Within the DC-SIGN-interacting region of the SARS-CoV spike protein, the spike protein of SARS-CoV-2 displayed remarkable similarity to the SARS-CoV spike protein. Surprisingly, the phylogenetic analysis revealed that the SARS-CoV-2's spike exhibited significantly diverse variants in the DC-SIGN interaction domain, which altered the frequency of these variants. The variation within the DC-SIGN-interacting domain of spike proteins affected the binding of a limited number of variants with DC-SIGN and DC-SIGNR and affected their evolution. MMGBSA binding free energies evaluation differed for variants from those of the wild type, suggesting the influence of substitution mutations on the interaction pattern. In silico knockout network analysis of the single-cell transcriptome of Bronchoalveolar Lavage and peripheral blood mononuclear cells revealed that SARS-CoV-2 altered DC-SIGN/R signaling. Early surveillance of diverse SARS-CoV-2 strains could preclude a worsening of the pandemic and facilitate the development of an optimum vaccine against variations. The spike Receptor Binding Domain genetic variants are thought to boost SARS CoV-2 immune evasion, resulting in its higher longevity. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-023-00820-3.

A robust NIfTI image authentication framework to ensure reliable and safe diagnosis.

Advancements in digital medical imaging technologies have significantly impacted the healthcare system. It enables the diagnosis of various diseases through the interpretation of medical images. In addition, telemedicine, including teleradiology, has been a crucial impact on remote medical consultation, especially during the COVID-19 pandemic. However, with the increasing reliance on digital medical images comes the risk of digital media attacks that can compromise the authenticity and ownership of these images. Therefore, it is crucial to develop reliable and secure methods to authenticate these images that are in NIfTI image format. The proposed method in this research involves meticulously integrating a watermark into the slice of the NIfTI image. The Slantlet transform allows modification during insertion, while the Hessenberg matrix decomposition is applied to the LL subband, which retains the most energy of the image. The Affine transform scrambles the watermark before embedding it in the slice. The hybrid combination of these functions has outperformed previous methods, with good trade-offs between security, imperceptibility, and robustness. The performance measures used, such as NC, PSNR, SNR, and SSIM, indicate good results, with PSNR ranging from 60 to 61 dB, image quality index, and NC all close to one. Furthermore, the simulation results have been tested against image processing threats, demonstrating the effectiveness of this method in ensuring the authenticity and ownership of NIfTI images. Thus, the proposed method in this research provides a reliable and secure solution for the authentication of NIfTI images, which can have significant implications in the healthcare industry.

Biochemical Markers and Adverse Maternal Outcomes in COVID-19 Pregnant Women: A Prospective Study

Background-COVID-19 is a newly emerged virus that leads to severe consequences;hence a collaborative approach to COVID-19-positive pregnant women is required. Identifying clinical features of SARS-CoV-2 infection in pregnant women is important as early as possible to decrease it and lower mortality and morbidity associated with it. We have evaluated maternal parameters associated with COVID-19 pregnancy and their clinical outcomes. Obstetric outcomes were compared with the severity of the disease. Material and methods- The study was a single-centred analysis of 71 pregnant women prospectively from April 2021-July 2021. All pregnant patients admitted to our hospital as COVID suspects were recruited. Data collected includes age, parity, gestational age, mode of delivery, comorbidity, haematological parameters, and complications during antenatal periods. Results- Out of 71 cases, the majority, 59(83.1%) cases were symptomatic and 12(16.9%) cases were asymptomatic. According to SPO2 level out of 71 cases, 19(26.8%) cases had severe disease, 36(50.7%) had moderate, 10(14.1%) had mild disease and 6(8.5%) had normal. Maternal mortality was observed 29(40.8%). The mortality rate was higher among 14(48.3%) severe cases and 11(37.9) moderate cases. Serum ferritin was significantly associated with the maternal outcome severity. Conclusion- Mortality was higher in patients with lower levels of spo2, accounting for 48.3%. In these pregnant women, we found a more elevated serum ferritin level, denoting a positive correlation of these biochemical markers with the severity of COVID-19, resulting in adverse maternal outcomes. As limited studies were found on the correlation between biochemical markers and the negative effects in COVID-19 pregnant females, this study can help advance the research further. [ FROM AUTHOR] Copyright of Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research) is the property of Journal of Cardiovascular Disease Research 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 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 . (Copyright applies to all s.)

A Multi-Institutional Study of Barriers to Cervical Cancer Care in Sub-Saharan Africa.

Purpose: The global rise in cancer incidence has been accompanied by disproportionately high morbidity and mortality rates in low- and middle-income countries. Many patients who are offered potentially curative treatment for cervical cancer in low- and middle-income countries never return to start treatment for reasons that are poorly documented and little understood. We investigated the interplay of sociodemographic, financial, and geographic factors as barriers to care among such patients in Botswana and Zimbabwe. Methods and Materials: Patients seen in consultation between 2019 and 2021 who were >3 months late for an appointment to initiate definitive treatment were contacted via telephone and invited to complete a survey. Afterward, an intervention connected patients with resources and counseling to return for treatment. Follow-up data were collected 3 months later to ascertain the outcomes of the intervention. Fisher exact tests analyzed the relationship between the putative number and types of barriers and demographics. Results: We recruited 40 women who initially presented for oncology care but did not return for treatment at [Princess Marina Hospital] in Botswana (n = 20) and [Parirenyatwa General Hospital] in Zimbabwe (n = 20) to complete the survey. Overall, married women experienced more barriers than unmarried women (P < .001), and unemployed women were 10 times more likely to report a financial barrier than employed women (P = .02). In Zimbabwe, financial barriers and belief-associated barriers (eg, fear of treatment) were reported. In Botswana, many patients noted scheduling obstacles associated with administrative delays and COVID-19. At follow-up, 16 Botswana patients and 4 Zimbabwe patients had returned for treatment. Conclusions: Financial and belief barriers identified in Zimbabwe showcase the importance of targeting cost and health literacy to reduce apprehensions. In Botswana, administrative challenges could be addressed with patient navigation. Improving our understanding of the specific barriers to cancer care could enable us to help patients who might otherwise default.

Severity and mortality associated with COVID-19 among children hospitalised in tertiary care centres in India: a cohort study

Background It is critical to identify high-risk groups among children with COVID-19 from low-income and middle-income countries (LMICs) to facilitate the optimum use of health system resources. The study aims to describe the severity and mortality of different clinical phenotypes of COVID-19 in a large cohort of children admitted to tertiary care hospitals in India, Methods Children aged 0-19 years with evidence of SARS-CoV-2 infection (real time polymerase chain reaction or rapid antigen test positive) or exposure (anti-SARS-CoV-2 antibody, or history of contact with SARS-CoV-2) were enrolled in the study, between January 2021 and March 2022 across five tertiary hospitals in India.. All study participants enrolled prospectively and retrospectively were followed up for three months after discharge. COVID-19 was classified into severe (Multisystem Inflammatory Syndrome in Children (MIS-C), severe acute COVID-19, ‘unclassified') or non-severe disease. The mortality rates were estimated in different phenotypes. Findings Among 2468 eligible children enrolled, 2148 were hospitalised Signs of illness were present in 1688 (79%) children with 1090 (65%) having severe disease. High mortality was reported in MIS-C (18·6%), severe acute COVID-19 (13·3%) and the unclassified severe COVID-19 disease (12·3%). Mortality remained high (17·5%) when modified MIS-C criteria was used. Non-severe COVID-19 disease had 14·1% mortality when associated with comorbidity. Interpretation Our findings have important public health implications for low resource settings. The high mortality underscores the need for better preparedness for timely diagnosis and management of COVID-19. Children with associated comorbidity or coinfections are a vulnerable group and need special attention. MIS-C requires context specific diagnostic criteria for low resource settings. It is important to evaluate the clinical, epidemiological and health system-related risk factors associated with severe COVID-19 and mortality in children from LMICs. Funding Department of Biotechnology, Govt of India and Department of Maternal, Child and Adolescent Health and Aging, WHO, Geneva.

Engaging Faith-Based Organizations for Promoting the Uptake of COVID-19 Vaccine in India: A Case Study of a Multi-Faith Society.

Mass vaccination, currently the most promising solution to contain communicable diseases, including COVID-19 requires collaboration between a variety of partners to improve the supply and demand and alleviate vaccine inequity. Vaccine hesitancy features in WHO's list of top 10 threats to global health, and there is plethora of disinformation instigating conflict between COVID-19 vaccination drive and religious sentiments. Negotiating public health partnerships with FBOs (Faith Based Organizations) has always been challenging. A handful of faith leaders have always shown resistance to ideas such as child immunization, and family planning. Many others have been supportive on other fronts like helping people with food, shelter, and medical aid in the times of public health crisis. Religion is an important part of life for the majority of the Indian population. People confide in faith-based leaders in the times of difficulty. This article presents experiences from the strategic engagement with FBOs (entities dedicated to specific religious identities, often including a social or moral component) to promote uptake of COVID-19 vaccination, especially among the vulnerable and marginalized communities. The project team collaborated with 18 FBOs and more than 400 religious institutions to promote COVID-19 vaccination and build confidence for the vaccination program. As a result, a sustainable network of sensitized FBOs from diverse faiths was created. The FBOs mobilized and facilitated vaccination of 0.41 million beneficiaries under the project.

Clinical characteristics & severity profile of children with COVID-19 during the second wave pandemic: An experience from tertiary care hospital in Mumbai.

This retrospective observational study was aimed at defining the demographic and clinical characteristics as well as severity profile of COVID-19 disease in children admitted to dedicated COVID-19 tertiary care hospital in Mumbai, India, during the second wave. COVID-19 infection detected in children (1 month-12 years) by the rapid antigen test or reverse transcriptase polymerase chain reaction or TRUENAT from March 1 to July 31, 2021 on throat/nasopharyngeal samples were enrolled and their clinical features and outcomes were studied. During the study period, 77 children with COVID-19 infection were admitted, of whom two-third (59.7%) were <5 yr old. The common presenting symptom was fever (77%), followed by respiratory distress. Comorbidities were noted in 34 (44.2%) children. Most of the patients belonged to the mild severity category (41.55%). While 25.97 per cent of patients presented in severe category and 19.48 per cent were asymptomatic. Admission to intensive care was needed in 20 (25.9%) patients, with 13 patients needing invasive ventilation. Nine patients succumbed while 68 were discharged. The results might help understand the course, severity profile and outcomes of the second wave of the COVID-19 pandemic in the paediatric population.

An assessment of the strategy and status of COVID-19 vaccination in India.

The COVID-19 disease continues to cause devastation for almost 3 years of its identification. India is one of the leading countries to set clinical trials, production, and administration of COVID-19 vaccination. Recent COVID-19 vaccine tracker record suggests that 12 vaccines are approved in India, including protein subunit, RNA/DNA, non-replicating viral vector, and inactivated vaccine. Along with that 16 more vaccines are undergoing clinical trials to counter COVID-19. The availability of different vaccines gives alternate and broad perspectives to fight against viral immune resistance and, thus, viruses escaping the immune system by mutations. Using the recently published literature on the Indian vaccine and clinical trial sites, we have reviewed the development, clinical evaluation, and registration of vaccines trial used in India against COVID-19. Moreover, we have also summarized the status of all approved vaccines in India, their associated registered clinical trials, manufacturing, efficacy, and their related safety and immunogenicity profile.

Risk hedging properties of infrastructure: a quantile regression approach

PurposeThis paper aims to examine the hedge, diversifier and safe haven properties of the global listed infrastructure sector and subsector indices against two traditional asset classes, stocks and bonds, and four alternative asset classes, including commodities, real estate, private equity and hedge funds during extreme negative stock market movements.Design/methodology/approachUsing dynamic conditional correlation and quantile regression, the authors analyze a data set of 12 indices comprising listed infrastructure and traditional asset classes from 2010 to 2019.FindingsOverall, the findings indicate that listed infrastructure acts as an effective diversifier but not as a strong safe haven or hedge when considered in a multiasset context. With minor exceptions, listed infrastructure cannot be concluded as a safe haven against other asset classes under investigation.Practical implicationsThe present study has implications for institutional investors looking to incorporate infrastructure in their multiasset portfolios for increased portfolio diversification benefits.Originality/valueDespite the increased influence of infrastructure as an asset class, to the best of the authors' knowledge, this is the first study to investigate the hedge, safe haven and diversifying properties of infrastructure in a multi-asset context.

A narrative inquiry into the meaning of career identity of Indian emerging adults amid Covid-19

This paper studied the career experiences of emerging adults amid the pandemic and how they make sense of their career identities during this time. Twenty Indian Emerging adults (18–25 years) wrote narratives about their career stories during the pandemic. Using thematic analysis, three key themes of (1) Perceived Impact of Pandemic Crisis on Career Identity, (2) Positive Meaning-Making of Career Identity amid the Crises, and (3) Negative Meaning-Making of Career Identity amid the Crises were identified. The study concluded that despite the negative impact of Covid-19 on career experiences, most emerging adults cognitively reframed negative experiences as positive.

Risk factors of mucormycosis in post-COVID-19 patients- a retrospective study

Background: Rhino-orbito-cerebral mucormycosis was seen in increasing severity in the recent second wave of COVID-19 in India. The incidence of mucormycosis is increased significantly in patients with diabetes. The most common cause attributed to the rise of mucormycosis in COVID-19 patients are uncontrolled diabetes. Lymphopenia and increased levels of certain cytokines, such as IL-6, have been closely associated with the disease severity. Aims and Objectives: The aims of this study were to analyze risk factors involved in Mucormycosis in 2nd wave of COVID-19. Materials and Methods: The study was done in the Mucormycosis ward, Department of ENT, Patna Medical College and Hospital, Patna, between May 2021 and July 2021. A total of 100 patients of both gender and all age groups were taken into the study. Results: Out of 100 patients included in the study, 57% (n=57) of patients had history of steroid intake, while 43% (n=43) had no history. About 41% (n=41) of patients needed oxygen support during treatment, while 59% (n=59) had no history of oxygen inhalation. About 88% (n=88) of patients had prior history of diabetes or detected during treatment, while 12% (n=12) had no prior history of diabetes or detected during treatment. About 91% (n=91)of patients had uncontrolled hyperglycemia, while 9% (n=9) had controlled blood sugar level. Conclusion: Uncontrolled hyperglycemia and delta strain are mainly associated major risk factors that lead to such high number of mucormycosis cases in India (post 2nd wave of COVID-19). Steroid role is not that much significant in our study and oxygen inhalation is not associated with mucormycosis.

Liquidity, Risk and Performance Measurement: An Analytical Study in Steel Industry

The paper showcases the analysis of the financial statements on Jindal Steel & Power Ltd which gives the inputs about the performance of the company. To support the study, Ratio analysis is used to focus on the financials of the company. As the financial analysis of any firm helps to understand the health of the company for this accounting ratios are studied to demonstrate the changes in the financials of the company because it is the useful tool for management, shareholders, financiers etc. Data was collected and used from Annual Reports of Jindal Steel & Power Ltd from the period of 2016-17 to 2020-21. The findings of the paper's financial study of Jindal Steel & Power Ltd. show that the company's financial performance increased after 2016-17 without taking the COVID-19 pandemic condition into account.

Infection Prevention Considerations for a Multi-Mission Convention Center Field Hospital in Baltimore, Maryland, During the COVID-19 Pandemic.

The state of Maryland identified its first case of coronavirus disease 2019 (COVID-19) on March 5, 2020. The Baltimore Convention Center (BCCFH) quickly became a selected location to set up a 250-bed inpatient field hospital and alternate care site. In contrast to other field hospitals throughout the United States, the BCCFH remained open throughout the pandemic and took on additional COVID-19 missions, including community severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic testing, monoclonal antibody infusions for COVID-19 outpatients, and community COVID-19 vaccinations.To prevent the spread of pathogens during operations, infection prevention and control guidelines were essential to ensure the safety of staff and patients. Through multi-agency collaboration, use of infection prevention best practices, and answering what we describe as PPE-ESP, an operational framework was established to reduce infection risks for those providing or receiving care at the BCCFH during the COVID-19 pandemic.

Early Warning Scores at Time of ICU Admission to Predict Mortality in Critically Ill COVID-19 Patients.

OBJECTIVE: To assess ability of National Early Warning Score 2 (NEWS2), systemic inflammatory response syndrome (SIRS), quick Sequential Organ Failure Assessment (qSOFA), and CRB-65 calculated at the time of intensive care unit (ICU) admission for predicting ICU mortality in patients of laboratory confirmed coronavirus disease 2019 (COVID-19) infection. METHODS: This prospective data analysis was based on chart reviews for laboratory confirmed COVID-19 patients admitted to ICUs over a 1-mo period. The NEWS2, CRB-65, qSOFA, and SIRS were calculated from the first recorded vital signs upon admission to ICU and assessed for predicting mortality. RESULTS: Total of 140 patients aged between 18 and 95 y were included in the analysis of whom majority were >60 y (47.8%), with evidence of pre-existing comorbidities (67.1%). The most common symptom at presentation was dyspnea (86.4%). Based upon the receiver operating characteristics area under the curve (AUC), the best discriminatory power to predict ICU mortality was for the CRB-65 (AUC: 0.720 [95% confidence interval [CI]: 0.630-0.811]) followed closely by NEWS2 (AUC: 0.712 [95% CI: 0.622-0.803]). Additionally, a multivariate Cox regression model showed Glasgow Coma Scale score at time of admission (P < 0.001; adjusted hazard ratio = 0.808 [95% CI: 0.715-0.911]) to be the only significant predictor of ICU mortality. CONCLUSIONS: CRB-65 and NEWS2 scores assessed at the time of ICU admission offer only a fair discriminatory value for predicting mortality. Further evaluation after adding laboratory markers such as C-reactive protein and D-dimer may yield a more useful prediction model. Much of the earlier data is from developed countries and uses scoring at time of hospital admission. This study was from a developing country, with the scores assessed at time of ICU admission, rather than the emergency department as with existing data from developed countries, for patients with moderate/severe COVID-19 disease. Because the scores showed some utility for predicting ICU mortality even when measured at time of ICU admission, their use in allocation of limited ICU resources in a developing country merits further research.

Anticoagulation practice patterns in COVID-19: A global survey.

Background: Best practice for prevention, diagnosis, and management of venous thromboembolism (VTE) in patients with coronavirus disease 2019 (COVID-19) is unknown due to limited published data in this population. Objectives: We aimed to assess current global practice and experience in management of COVID-19-associated coagulopathy to identify information to guide prospective and randomized studies. Methods: Physicians were queried about their current approach to prophylaxis, diagnosis, and treatment of VTE in patients with COVID-19 using an online survey tool distributed through multiple international organizations between April 10 and 14, 2020. Results: Five hundred fifteen physicians from 41 countries responded. The majority of respondents (78%) recommended prophylactic anticoagulation for all hospitalized patients with COVID-19, with most recommending use of low-molecular-weight heparin or unfractionated heparin. Significant practice variation was found regarding the need for dose escalation of anticoagulation outside the setting of confirmed or suspected VTE. Respondents reported the use of bedside testing when unable to perform standard diagnostic imaging for diagnosis of VTE. Two hundred ninety-one respondents reported observing thrombotic complications in their patients, with 64% noting that the complication was pulmonary embolism. Of the 44% of respondents who estimated incidence of thrombosis in patients with COVID-19 in their hospital, estimates ranged widely from 1% to 50%. One hundred seventy-four respondents noted bleeding complications (34% minor bleeding, 14% clinically relevant nonmajor bleeding, and 12% major bleeding). Conclusion: Well-designed epidemiologic studies are urgently needed to understand the incidence and risk factors of VTE and bleeding complications in patients with COVID-19. Randomized clinical trials addressing use of anticoagulation are also needed.

Online education and its effect on teachers during COVID-19-A case study from India.

BACKGROUND: COVID pandemic resulted in an initially temporary and then long term closure of educational institutions, creating a need for adapting to online and remote learning. The transition to online education platforms presented unprecedented challenges for the teachers. The aim of this research was to investigate the effects of the transition to online education on teachers' wellbeing in India. METHODS: The research was conducted on 1812 teachers working in schools, colleges, and coaching institutions from six different Indian states. Quantitative and qualitative data was collected via online survey and telephone interviews. RESULTS: The results show that COVID pandemic exacerbated the existing widespread inequality in access to internet connectivity, smart devices, and teacher training required for an effective transition to an online mode of education. Teachers nonetheless adapted quickly to online teaching with the help of institutional training as well as self-learning tools. However, respondents expressed dissatisfaction with the effectiveness of online teaching and assessment methods, and exhibited a strong desire to return to traditional modes of learning. 82% respondents reported physical issues like neck pain, back pain, headache, and eyestrain. Additionally, 92% respondents faced mental issues like stress, anxiety, and loneliness due to online teaching. CONCLUSION: As the effectiveness of online learning perforce taps on the existing infrastructure, not only has it widened the learning gap between the rich and the poor, it has also compromised the quality of education being imparted in general. Teachers faced increased physical and mental health issues due to long working hours and uncertainty associated with COVID lockdowns. There is a need to develop a sound strategy to address the gaps in access to digital learning and teachers' training to improve both the quality of education and the mental health of teachers.

Racial and Socioeconomic Characteristics Associated with the use of Telehealth Services Among Adults With Ambulatory Sensitive Conditions.

Introduction: The COVID-19 pandemic led to a major transition for patients from routine ambulatory-care-based in-person primary care visits to telehealth visits to manage chronic diseases. However, it remains unclear the extent to which individuals access telehealth services and whether such utilization varies along neighborhood characteristics, especially among racial minorities. This study aims to examine the association of outpatient telehealth utilization with sociodemographic, clinical, and neighborhood characteristics among adults with ambulatory care sensitive conditions (ACSCs) during the COVID-19 pandemic. Methods: We included adults treated for an ACSC between March 5, 2020, and December 31, 2020, at a single ambulatory-care-based healthcare system, which serves a large population of low-income patients in the South region of the United States (i.e., Memphis, TN, Metropolitan Statistical Area). Telehealth utilization was defined by outpatient procedural codes and providers' notes on the type of visits. Generalized linear mixed models were used to examine the association of sociodemographic, clinical, and neighborhood factors with telehealth utilization in the overall cohort and the racial subpopulations. Results: Among the 13,962 adults with ACSCs, 8583 (62.5%) used outpatient telehealth services. Patients who were older, female, with mental disorders, and who had more comorbidities had higher rates of telehealth services (p < .05). Controlling for covariates, we observed 75.2% and 23.1% increased use of telehealth services among Hispanics and other race groups, respectively, compared to Whites. Patients who commuted more than 30 minutes to health facilities were slightly less likely to use telehealth services [OR: 0.994 (0.991,0.998)]. Racial minorities (Blacks and Hispanics) with mental disorders were more likely to use telehealth service when compared to Whites. Discussion: We found that among patients being treated for ACSCs, the use of telehealth services was highly prevalent in Hispanic patients in general and were more pronounced among both Hispanics and Black patients who have mental disorders.

Computational framework to understand the clinical stages of COVID-19 and visualization of time course for various treatment strategies.

Coronavirus disease 2019 is known to be regulated by multiple factors such as delayed immune response, impaired T cell activation, and elevated levels of proinflammatory cytokines. Clinical management of the disease remains challenging due to interplay of various factors as drug candidates may elicit different responses depending on the staging of the disease. In this context, we propose a computational framework which provides insights into the interaction between viral infection and immune response in lung epithelial cells, with an aim of predicting optimal treatment strategies based on infection severity. First, we formulate the model for visualizing the nonlinear dynamics during the disease progression considering the role of T cells, macrophages and proinflammatory cytokines. Here, we show that the model is capable of emulating the dynamic and static data trends of viral load, T cell, macrophage levels, interleukin (IL)-6 and TNF-α levels. Second, we demonstrate the ability of the framework to capture the dynamics corresponding to mild, moderate, severe, and critical condition. Our result shows that, at late phase (>15 days), severity of disease is directly proportional to pro-inflammatory cytokine IL6 and tumor necrosis factor (TNF)-α levels and inversely proportional to the number of T cells. Finally, the simulation framework was used to assess the effect of drug administration time as well as efficacy of single or multiple drugs on patients. The major contribution of the proposed framework is to utilize the infection progression model for clinical management and administration of drugs inhibiting virus replication and cytokine levels as well as immunosuppressant drugs at various stages of the disease.