Post-Covid Remote Patient Monitoring Using Medical Internet Of Things And Machine Learning Analytics

The Covid-19 pandemic disturbed the smooth functioning of healthcare services throughout the world. New practices such as masking, social distancing and so on were followed to prevent the spread. Further, the severity of the problem increases for the elderly people and people having co-morbidities as proper medical care was not possible and as a result many deaths were recorded. Even for those patients who recovered from Covid could not get proper health monitoring in the Post-Covid phase as a result many deaths and severity in health conditions were reported after the Covid recovery i.e., the Post-Covid era. Technical interventions like the Internet of Things (IoT) based remote patient monitoring using Medical Internet of Things (M-IoT) wearables is one of the solutions that could help in the Post-Covid scenarios. The paper discusses a proposed framework where in a variety of IoT sensing devices along with ML algorithms are used for patient monitoring by utilizing aggregated data acquired from the registered Post-Covid patients. Thus, by using M-IoT along with Machine Learning (ML) approaches could help us in monitoring Post-Covid patients with co-morbidities for and immediate medical help. © 2023 SCPE.

Medical Internet of Things and Data Analytics for Post-COVID Care: An Analysis

The healthcare services across the world have been badly affected by the pandemic since December 2019. People have suffered in terms of medical supplies and treatments because existing medical infrastructure has failed to accommodate huge number of COVID infected patients. Further, patients with existing morbidities have been the worst hit so far and need attention. Therefore, there is a need of post-COVID care for such patients which can be achieved by using technologies such as Internet of Things (IoT) and data analytics. This paper presents medical IoT-based data analysis for post-COVID care. This paper, further, presents post-COVID data analysis to get an insight into the various symptoms across the different perspectives. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Virtual Screening of Potential Therapeutic Inhibitors Against Spike, Heli-case, and Polymerase of SARS-CoV-2 (COVID-19)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected around 13 million people and has caused more than 5.7 lakh deaths worldwide since December 2019. In the absence of FDA approved drugs for its treatment, only symptomatic management is done. Method(s): We attempted to uncover potential therapeutic targets of spike, helicase, and RNA dependent RNA polymerase (RdRp) proteins of the SARS-CoV-2 employing a computational approach. The PDB structure of spike and RdRp and predicted structure of helicase proteins were docked with 100 approved anti-viral drugs, natural compounds, and some other chemical compounds. Result(s): The anti-SARS ligands EK1 and CID 23631927, and NCGC00029283 are potential entry in-hibitors as they showed affinity with immunogenic Receptor Binding Domain (RBD) of the spike pro-tein. This RBD interacts with Angiotensin Converting Enzyme (ACE2) receptor, facilitating the entry of virion in the host cells. The FDA approved drugs, including Nelfinavir, Saquinavir, Tipranavir, Setrobu-vir, Indinavir, and Atazanavir, showed potential inhibitory activity against targeted domains and thus, may act as entry or replication inhibitor or both. Furthermore, several anti-HCoV natural compounds, including Amentoflavone, Rutin, and Tannin, are also potential entry and replication inhibitors as they showed affinity with RBD, P-loop containing nucleoside triphosphate hydrolase, and the catalytic domain of the respective protein. Dithymoquinone showed significant inhibitory potential against the fusion peptide of S2 domain. Importantly, Tannin, Dithymoquinone, and Rutin can be extracted from Nig-ella sativa seeds and thus, may prove to be one of the most potential anti-SARS-CoV-2 inhibitors. Conclusion(s): Several potential ligands were identified with already known anti-HCoVs activities. Fur-thermore, as this study showed that some of the ligands acted as both entry and replication inhibitors against SARS-CoV-2, it is envisaged that a combination of either inhibitor with a dual mode of action would prove to be a much desired therapeutic option against this viral infection.Copyright © 2021 Bentham Science Publishers.

Point prevalence audit surveys of respiratory tract infection consultations and antibiotic prescribing in primary care before and during the COVID-19 pandemic in Ireland.

BACKGROUND: Respiratory tract infections (RTIs) are the most common reason for prescribing antibiotics in general practice. The COVID-19 pandemic has impacted on antibiotic prescribing and delivery of primary care in Ireland. OBJECTIVES: To assess the quality of antibiotic prescribing, the impact of the COVID-19 pandemic and identify opportunities for antimicrobial stewardship (AMS) in Ireland. METHODS: Point prevalence audit surveys for RTI consultations were conducted as part of a European study at three time periods: January-February 2020, March-May 2020 and March-May 2021. Antibiotic prescribing was assessed and comparisons made between the three time periods. RESULTS: In total, 765 consultations were recorded, which were mainly face to face before the pandemic, but changed to predominantly remote consultations during the pandemic surveys in 2020 and 2021 (82% and 75%). Antibiotics were prescribed in 54% of RTI consultations before the pandemic. During pandemic surveys, this dropped to 23% in 2020 and 21% in 2021. There was a decrease in prescribing of Red (reserve) agents in 2021. Assessment against indication-specific quality indicators showed a high proportion of consultations for bronchitis and tonsillitis resulting in an antibiotic prescription (67% and 85%). Point-of-care testing (POCT) to aid diagnosis of RTIs were utilized in less than 1% of consultations. CONCLUSIONS: During the COVID-19 pandemic, there was a reduction in antibiotic prescribing. Opportunities identified to support AMS in primary care in Ireland are targeted initiatives to reduce antibiotic prescribing for bronchitis and tonsillitis and introducing POCT to support appropriate antibiotic prescribing.

Effect of disease activity on the clinical outcome of SARS CoV 2 in patients with underlying rheumatic diseases

Objective: To determine the effect of disease activity on the clinical outcome of SARS CoV 2 in patients with underlying rheumatic diseases. Method(s): This multicentric cross sectional study was performed under grant received from GRA/ILAR from 1st June 2021 till 31st December 2021. Online survey form was disseminated through platform of PSR to collect the data. Data included demographic details as well as underlying rheumatic and medications. Course of SARS CoV2 was noted for the patients as either (1) need for hospitalization, intensive care unit (ICU) admission;(2) need for respiratory support or (3) recovery or death. Data was analysed using SPSSv23. Result(s): A total of 100 patients fulfilling the inclusion criteria were enrolled. 78 (78%) were females with a mean age of 45.60 +/- 13.7 years. The clinical and demographic characteristics at baseline are as shown in Table 1. The most common rheumatic disorders were RA, SLE and AS seen in 52 (52%) 20 (20%) and 8 (8%) respectively. The mean duration of rheumatic disorders was 7.54 +/- 7.66 years. Common medications were NSAIDS and glucocorticoids (GC) each in 55 (55%) patients, HCQ in 42 (42%) and MTX in 48 (48%).Mean duration of COVID-19 symptoms was 16 +/- 12.7 days. Overall, 33 (33%) patients needed hospitalization;out of whom only 21 (21%) needed ICU care. Mean duration of hospital stay was 10.69 +/- 11.6 days. Complaint of dyspnea predicted the hospitalization. There was no association between ongoing rheumatic disease treatment and need for hospitalization. Similarly, disease activity status of RA, SLE and AS had no association with hospitalization, need for invasive ventilation or mortality. Conclusion(s): In patients with underlying rheumatic disorders, more than two thirds survived the SARs-CoV 2 infection. Rheumatic disease activity and medications had no impact on patient outcomes. (Table Presented).

Reduction in environmental pollution due to lockdown in the COVID-19 pandemic: A case study of Delhi-NCR

The Indian government imposed a countrywide lockdown on 25 March 2020 to contain the COVID-19 virus. The lockdown has led to a tremendous economic loss because of the closing of all industries and other activities. However, it has brought a brighter side to environmental quality improvement. This study assesses the influence of lockdown on Delhi-NCR's air and water quality. The earth system rejuvenated during the lockdown. An effort is made to understand the water quality of the Yamuna River in Delhi and the air quality of the Delhi-National Capital Region (Delhi NCR) during the lockdown. In the Yamuna River surrounding Delhi, a reduction of 1-10%, 33-66%, 51%, 45-90%, and 33-82%, respectively, in pH, EC, DO, BOD, and COD has been observed compared to the pre-lockdown. Similarly, the particulate matter concentration reduced by 31-53% in PM10 and 22-48% in PM2.5 during the lockdown of2020 in comparison to the earlier years (2018 and 2019). Hence, the periodic lockdown has positively impacted the air and water quality in Delhi NCR. © 2021, IGI Global.

Medical IoT Data Analytics for Post-COVID Patient Monitoring

The COVID-19 has changed the scenario of patient care in most of the hospitals and healthcare centers throughout the world. Since pandemic is spread through contact with the COVID infected person, the most vulnerable community is doctors and healthcare workers. To avoid the mixing of COVID patients from other diseases, there is a need to be a separation, which will contain the spread of virus. As such, remote patient monitoring becomes very essential to take care of the patients under such situations. Because of this medical data is growing exponentially and needs to be analyzed continuously to improve the health care. Data analytics improved the performance of health care organization by proper decision making, accurate and timely information. Medical data can be explored from the sensors or medical equipments installed in the hospitals or can be collected from the fast-growing Internet of Things (IoT) devices. Visualizing the data and correlating the same with the patient monitoring for better treatment and health care is an essential part of it. This paper discusses various Machine Learning (ML) approaches for remote patient monitoring using medical IoT data for the Post-COVID patient care. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Baseline Parameters in Untreated Ovarian and Breast (Symptomatic and Asymptomatic Covid-19) Cancer Patients

Objective: To evaluate the effect of covid-19 on CBC, LFT's, RFT's and TMR's in cancer patients. Study Design: A prospective study Place and Duration of Study: This study was conducted at Multan Institute of Nuclear Medicine and Radiotherapy (MINAR) from April 2019 to December 2020. Materials and Methods: This study was performed on 3772 untreated cancer patients (includes bladder, bone, brain, breast, colon, larynx, leukemia, liver, lung, ovary and other cancer types with age ranging from 8-87 years (49.59±15.27) of 2019 and 2020 (50% of COVID attack) at MINAR hospital, Multan. Chi-square Mann Whitney, Independent T- test and Spearman correlation analysis were performed to calculate results. Results: The incidence of bone cancer (p value-0.02), brain cancer (p value-0.03), breast cancer (p value-0.00001) liver cancer (p value-0.006), and ovarian cancer (p value-0.0001) was higher in 2020 patients. All cancers, data indicated that Creatinine (p=0.004) and CA 125(p=0.04) were in higher ranges in COVID 19 cancer patients. There observed significant change in creatinine levels of breast (p=0.02) and ovarian cancer patients (p=0.04) and also higher level of CA-125(p=0.04) was indicated in ovarian cancer patients along with covid-19. There observed strongly significant positive association of CA- 125 with creatinine (r=0.34, p=0.02), and CEA with Bilirubin Total(r=0.57, p=0.04) in ovarian cancer. MCV (p=0.00), HGB (p=0.01), HCT (p=0.04), MCH (p=0.001), and MCHC (p=0.02) were decreased in breast cancer patients. CA-125 showed a strongly significant negative association with LY %(r= -0.305, p=0.03) and MO %(r= -0.299, p=0.049) in ovarian cancer. Conclusion: Our findings suggest that incidence of ovarian cancer and breast cancer was very high during COVID pandemic attack. Association of CA 125 with creatinine in breast cancer and with LY% and MO% in ovarian cancer serve as the prognostic factor during viral attack. MCV and Creatinine are diagnostic factors in both cancers. © 2022 Medical Forum Monthly. All rights reserved.

Perceptions and Preparedness for Covid-19 Pandemic among Students of a Medical University

Background: The accomplishment of control of Covid-19 pandemic depends upon people’s readiness & preparedness of the medical professionals. The current study is expected to benefit the communities by assessing the knowledge of medical students regarding containment of this pandemic. Objectives: 1. To assess the perceptions and readiness of the medical students regarding COVID-19. 2. To determine association between various socio- demographic profile of study participants and their perceptions regarding Covid-19. Methodology: Three hundred & eighty four medical & dental students were selected by convenience sampling. Besides socio-demographic variables of medical students, students level of knowledge & perceptions regarding Covid-19 were recorded on a pre-designed & pre-validated questionnaire. Besides computing frequencies & percentages, the association among variables was performed by applying Chi-square test by taking p-value <0.05 as level of significance. Results: The response rate was 92.53%. The study participants had a high level of information (93.75%) regarding COVID19 outbreak. We did not find a single insignificant association between age of students & their perceptions regarding Covid-19 pandemic (p ≤ 0.01). Similar associations were observed between gender & level of education to the knowledge & perceptions regarding Covid-19 pandemic (p ≤ 0.01). Conclusions: The medical & dental students are very well aware about the Covid-19 pandemic & its control measures undertaken by government.

Sentiment Analysis of COVID-19 Vaccine Rollout in India

This paper deals with opinions expressed in social media, namely Twitter, with respect to the ongoing vaccination program for the novel coronavirus COVID-19. This pandemic has affected almost the entire world because of lockdown and its related impact on personal, economical and emotional levels. During the lockdown, people suffered loneliness and lack of interpersonal interaction therefore resort to taking social media to voice their concerns and emotions. The need for vaccination, its delivery and trust are some of the topics on which sentiments are expressed on Twitter based on which this research is conducted. This study analyses the sentiments of the people in India towards the emergency use authorization of COVID vaccine rollout. The tweets are collected, pre-processed to exclude noise and irrelevant data and then used for sentiment analysis using the Lexicon-based approach and machine learning method. The relative outcome of tweets analysed via all these methods is consistent in each type of sentiment. It is observed that sentiments of most of the tweets came out to be either affirmative or neutral. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Data Analytics and Visualization to Aid Mental Health Care

Mental state of a person is an indication of emotive, psychological and social welfare. Various parameters like pressure, strain, social fretfulness, dejection, obsessive compulsive disorder, drug obsession and personality disorders leads to mental illness. The purpose of the research was to analyse, predict and make better mental health solutions for the individuals using data visualization tool on selected datasets in metropolitan and semi-urban population. The study was undertaken among wide age range group from less than 18 to 50 plus of all around India. A 747 samples were collected using Google Form, out of which 425 were male (56.09%) and female were 319 (42.07%). The figure of 307 people of total population showed prevalence of diagnosable mental disorders. Hence, there is a great need to upsurge the prevention policies both at initial and tributary levels to overcome the mental distress and economic loss to society due to mental disorders. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Brief survey on phytochemicals to prevent COVID-19

Background: The recent pandemic by COVID-19 is a global threat to human health. The disease is caused by SARS-CoV-2 and the infection rate is increased more quickly than MERS and SARS as their rapid adaptation to varied climatic conditions through rapid mutations. It becomes more severe due to the lack of proper therapeutic drugs, insufficient diagnostic tool, scarcity of appropriate drug, life supporting medical facility and mostly lack of awareness. Therefore, preventive measure is one of the important strategies to control. In this context, herbal medicinal plants received a noticeable attention to treat COVID-19 in Indian subcontinent. Here, 44 Indian traditional plants have been discussed with their novel phytochemicals that prevent the novel corona virus. The basic of SARS-CoV-2, their common way of transmission including their effect on immune and nervous system have been discussed. We have analysed their mechanism of action against COVID-19 following in-silico analysis. Their probable mechanism and therapeutic approaches behind the activity of phytochemicals to stimulate immune response as well as inhibition of viral multiplication discussed rationally. Thus, mixtures of active secondary metabolites/phytochemicals are the only choice to prevent the disease in countries where vaccination will take long time due to overcrowded population density. © 2021 Indian Chemical Society

COVID-19 and An IoT Based Protection System for Working Environment

As the spread of COVID-19 has widely affected the large area of the world population, this led many countries to impose complete lock-down all across the globe which is still going on and on. In such situation all the business, education, industries and organizational activities were completely stopped. In this scenario, the organizations give a policy to employees to the concept of "working from home (WFH)". However, this policy does not work for every organization. Therefore, after starting physical presence of workers and employees in organization there should be proper safety measures for identifying the symptoms and causes of the deadly virus among workers. In order to do so, in this research paper, an internet of things (IoT) based solution to protect the working environment from further spread of the disease is proposed. Suspects of COVID-19 the virus are identified through various parameters using IoT framework. The general idea is to maintain a safe and sound working environment to prevent and control the further spread of the virus. It would be more useful not only preventing and controlling the spread of COVID-19 virus but also maintaining the Standard operating procedures (SoPs) in the organizations.

Vaccine perception: Acceptance, hesitancy, beliefs and barriers associated with Covid-19 vaccination among medical students

Introduction: COVID-19 vaccines have emerged as a key strategy, being the most effective public health intervention in preventing the massive humanitarian crisis. Thus, as a part of preventive measure, government of India had launched COVID-19vaccines on 16 January 2021.Indeed vaccine hesitancy is one of the most significant barriers for success of any immunization drive. Hence, in view of the recent surge in Covid19 cases in our country, this study was planned to assess the awareness, hesitancy and acceptance attitudes ofCOVID-19vaccine among Medical Students (MS) of Maharashtra. Methodology: This was a cross sectional study. Data was collected using self-reported, structured questionnaire from 356 MS through online Google form. Data were extracted, transferred and analysed using appropriate statistical tool. Results: The study reported 83.43%vaccine acceptance and 16.57% of hesitancy among MS. Furthermore, the main source of COVID-19 vaccine information was social media followed by government web sites. Majority 91.57% of the students were aware of different types of COVID-19vaccines available in our country. However 62.62% MS among acceptance group were willing to get vaccinated through college or university health centre. Beside the main reason for hesitancy was fear of adverse reactions. Moreover the hesitant group was uncertain about safety and efficacy of available vaccines. Conclusion: High acceptance was shown among MS regarding COVID-19 vaccine;however, it is critical to alleviate uncertainties among hesitant MS by continuous education, encouragement and motivation. Consequently, planning and implementation of strategies to further amplify the vaccination rate among medical student is vital to augment the COVID-19 vaccination drive in our country.

Examining investors' sentiments, behavioral biases and investment decisions during COVID-19 in the emerging stock market: a case of Pakistan stock market

Purpose - This study investigates the impact of the COVID-19 pandemic on investors' sentiments, behavioral biases and investment decisions in the Pakistan Stock Exchange (PSX). Design/methodology/approach - The authors have assessed investors' behaviors and sentiments and the stock market overreaction during COVID-19 using a questionnaire and collected data from 401 investors trading in the PSX. Findings - Results of structural equation modeling revealed that the COVID-19 pandemic affected investors' behaviors, investment decisions and trade volume. It created feelings of fear and uncertainty among market participants. Evidence suggests that behavioral heuristics and biases, including representative heuristic, anchoring heuristic, overconfidence bias and disposition effect, negatively influenced investors' decisions at the PSX. Research limitations/implications - This study will contribute to behavioral finance literature in the context of developing countries as it has revealed the impact of COVID-19 on the emerging stock market, and its results are generalizable to other emerging stock markets. Practical implications - The findings of this study will help academicians, researchers and policymakers of developing countries. Academicians can formulate new behavioral models that can depict the solutions of dealing with an uncertain situation like COVID-19. Policymakers like the Securities Exchange Commission and the PSX can formulate crisis management strategies based on behavioral finance concepts to cope with situations like COVID-19 in the future and help lessen investors' losses in the stock markets. The role of the Securities Exchange Commission is crucial as it regulates the financial markets. It can arrange workshops to educate investors to manage their decisions during crisis time and focus on the best use of irrational and rational decision-making at the same time using Lo (2004) adaptive market hypothesis. Originality/value - The novelty of the paper is that the authors have introduced overconfidence and disposition effect as mediators that create a connection between representative and anchoring heuristics and investment decisions using primary data collected from investors (institutional and retail) to demonstrate the presence of psychological biases during COVID-19, and it has been done for the first time according to authors' knowledge. It is a contribution and addition to the behavioral finance literature in the context of developing countries' stock markets and their efficiency.

Potential exploration of recent FDA-approved anticancer drugs against models of SARS-CoV-2’s main protease and spike glycoprotein: A computational study

COVID-19 has become a worldwide risk to the healthcare system of practically every nation of the world, which originated from Wuhan, China. To date, no specific drugs are available to treat this disease. The exact source of the SARS-CoV-2 is yet unknown, although the early cases are associated with the Seafood market in Huanan, South China. This manuscript reports the in silico molecular modeling of recent FDA-approved anticancer drugs (Capmatinib, Pemigatinib, Selpercatinib, and Tucatinib) for their inhibitory action against COVID-19 targets. The selected anticancer drugs are docked on SARS-CoV-2 main protease (PDB ID: 6LU7) and SARS-CoV-2 spike glycoprotein (PDB ID: 6M0J) to ascertain the binding ability of these drugs. ADMET parameters of the drugs are assessed, and in addition, DFT calculations are done to investigate the pharmacokinetics, thermal parameters, dipole moments, and chemical reactivity descriptors. The docking energies (ΔG) and the interacting amino acid residues are discussed. Promising molecular docking conclusions have been accomplished, which demonstrated the potential of selected anticancer drugs for plausible drug development to fight COVID-19. Further optimizations with the drug may support the much-needed rapid response to mitigate the pandemic. © 2020 by the authors.