Knowledge, Attitude, and Practices towards COVID-19 Infection and Prevention Measures among Medical Students (preprint)

The COVID-19 pandemic has rapidly led to an unprecedented health threat worldwide. During this time, disease prevention is considered to be the best way for general health protection. This is achieved through public health education by extending proper knowledge, promoting an optimistic attitude, and keeping the public compliant with preventive measures. As components of the healthcare system, medical students should also play a role in disease prevention more so in the Philippines where the Department of Health has called upon medical graduates to render services in response to the national emergency. In this study, the knowledge, attitude, and practices (KAP) of medical students from Cebu Institute of Medicine (CIM) towards COVID-19 infection and preventive measures were assessed. Demographic factors, their respective effect size on KAP, as well as the relationship between KAP variables were determined. The revised questionnaire, drafted based on qualitative and quantitative validity tests, was then used for the pilot study to generate the final questionnaire. Responses from participants underwent descriptive and correlational analysis. The results showed that the majority of the medical students of CIM have adequate knowledge (78.24%), positive attitude (80.68%), and good practices (94.38%) towards COVID-19 infection and prevention measures. Females have a significant association (p-value = 0.03) with better practices than male counterparts. Knowledge (p-value = 0.004) and attitude (p-value = 0.003) also showed significant correlation with practices, implying that knowledge and attitude play a role in shaping compliance to health practices. Therefore, health interventions should aim to disseminate accurate, evidence-based information and improve attitude towards the implemented precautionary measures in order to increase effectiveness of policies.

The Psychological Impacts of Taking Physiotherapy Teaching Online in 2020: What Did We Learn?

Introduction. The rapid shift to online learning due to the COVID-19 pandemic presented challenges for physical therapy (PT) education worldwide. This article aims to explore the factors influencing the well-being of the PT faculty and department chairs involved in delivering PT programs during the initial stages of the COVID-19 pandemic. Review of Literature. The literature has focused on the pedagogical impacts of the rapid shift to online learning. Little is known about the social and psychological impacts of this rapid transition on the well-being of the faculty involved in implementing PT programs. Subjects. Physical therapy faculty and department chairs at 3 universities in metropolitan Sydney, Australia who taught into or led PT programs in 2020. Methods. Focus group methodology was used to explore the experiences of PT faculty and department chairs during the initial stages of the COVID pandemic. The focus groups were digitally recorded and transcribed verbatim and the transcripts analyzed thematically. Results: The main finding of this study was the extent of stress experienced by PT program faculty and chairs during this period. Both work-related institutional and faculty factors and non-work-related personal factors contributed to perceived high levels of stress. Overall, there was a feeling that the stressors had not improved over the duration of the pandemic and that this had left the faculty and chairs feeling more fatigued, less collegiate, and may have ongoing impacts on their mental health. Discussion: The pandemic created stresses for faculty and program chairs over and above the usual stress of faculty and college work. The reality of taking steps to reduce the stressors in the current climate is very difficult. Conclusion. Moving forward, it is vital to secure increased institutional support, including the support for creating realistic boundaries without the risk of penalty, to address the psychological health and well-being of PT faculty and chairs to enable high-quality education in the future. Copyright © 2023 Academy of Physical Therapy Education, APTA.

Frontal Electroencephalography Findings in Critically Ill COVID-19 Patients.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) negatively impacts the central nervous system, and studies using a full montage of electroencephalogram (EEG) electrodes have reported nonspecific EEG patterns associated with coronavirus disease 2019 (COVID-19) infection. The use of this technology is resource-intensive and limited in its implementation. In this descriptive pilot study, we report neurophysiological patterns and the potential prognostic capability of an abbreviated frontal EEG electrode montage in critically ill COVID-19 patients. MATERIALS AND METHODS: Patients receiving mechanical ventilation for SARS-CoV-2 respiratory failure were monitored with Sedline Root Devices using EEG electrodes were placed over the forehead. Qualitative EEG assessments were conducted daily. The primary outcome was mortality, and secondary outcomes were duration of endotracheal intubation and lengths of intensive care and hospitalization stay. RESULTS: Twenty-six patients were included in the study, and EEG discontinuity was identified in 22 (84.6%) patients. The limited sample size and patient heterogeneity precluded statistical analysis, but certain patterns were suggested by trends in the data. Survival was 100% (4/4) for those patients in which a discontinuous EEG pattern was not observed. The majority of patients (87.5%, 7/8) demonstrating activity in the low-moderate frequency range (7 to 17 Hz) survived compared with 61.1% (11/18) of those without this observation. CONCLUSIONS: The majority of COVID-19 patients showed signs of EEG discontinuity during monitoring with an abbreviated electrode montage. The trends towards worse survival among those with EEG discontinuity support the need for additional studies to investigate these associations in COVID-19 patients.

Can ship travel contain COVID-19 outbreak after re-opening: a Bayesian meta-analysis.

Large gatherings of people on cruise ships and warships are often at high risk of COVID-19 infections. To assess the transmissibility of SARS-CoV-2 on warships and cruise ships and to quantify the effectiveness of the containment measures, the transmission coefficient (ß), basic reproductive number (R0), and time to deploy containment measures were estimated by the Bayesian Susceptible-Exposed-Infected-Recovered model. A meta-analysis was conducted to predict vaccine protection with or without non-pharmaceutical interventions (NPIs). The analysis showed that implementing NPIs during voyages could reduce the transmission coefficients of SARS-CoV-2 by 50%. Two weeks into the voyage of a cruise that begins with 1 infected passenger out of a total of 3,711 passengers, we estimate there would be 45 (95% CI:25-71), 33 (95% CI:20-52), 18 (95% CI:11-26), 9 (95% CI:6-12), 4 (95% CI:3-5), and 2 (95% CI:2-2) final cases under 0%, 10%, 30%, 50%, 70%, and 90% vaccine protection, respectively, without NPIs. The timeliness of strict NPIs along with implementing strict quarantine and isolation measures is imperative to contain COVID-19 cases in cruise ships. The spread of COVID-19 on ships was predicted to be limited in scenarios corresponding to at least 70% protection from prior vaccination, across all passengers and crew.

Diagnostic Analysis of mZN Microscopy and PCR for Detection of Cryptosporidiosis in Goat Kids - A Molecular Epidemiological Study

The occurrence of Cryptosporidium species infection and its risk factors in neonatal goats is less explored. Also it is due to the fact that diseases like colibacillosis and neonatal viral enteritis complex caused by Group A rotaviruses and Bovine corona viruses can co-exist with Cryptosporidium and can lead to mixed infections and the latter is often overlooked. Therefore, in the current research we explored the cryptosporidial occurrence in neonatal goats of Mathura district of Uttar Pradesh, India. In this study, a total of 644 faecal samples were collected from neonatal goats at different villages and certain organized farms of Mathura district age-wise, season-wise and breed-wise, and were examined for Cryptosporidium based on modified Ziehl-Neelsen technique, conventional 18SSU rRNA nested PCR assay. The overall prevalence of Cryptosporidium infection in goats based on microscopy was 36.80% (237/644;p value <0.0001) and 18SSU rRNA nested PCR 52.95% (341/644;p value <0.0001) respectively. Cryptosporidium species typing was also done using 18SSU rRNA nested PCR-RFLP product using enzymes Mbo-II, Ssp-I and Vsp-I, which revealed species including C. parvum C. bovis, C. ryanae, C. hominis and C. andersoni. Also the infection was clinically associated based on age, gender and seasons to identify the causal relationships that precipitate the cryptosporidial infection in goat kids. Since mZN microscopy based screening requires expertise and may sometimes be confuse with other weak acid fast bodies and also due to low sensitivity, combination of diagnostic tests are used in this study to identify the best test combination that yields best statistical fit in terms of kappa-agreement and McNemar's test. Cryptosporidiosis is caused by an enteric protozoan parasite and the first report in sheep and goat was observed in early 1980s, with other important etiological agents for neonatal diarrhoea, mortality and morbidity in neonatal kids and lambs, responsible for economic losses.Copyright © 2023 Indian Veterinary Assocaition. All rights reserved.

Barriers to achieving sustainability in pharmaceutical supply chains in the post-COVID-19 era

Purpose - The recent pandemic caused by coronavirus disease 2019 (COVID-19) has significantly impacted the operational performances of pharmaceutical supply chains (SCs), especially in emerging economies that are critically vulnerable due to their inadequate resources. Finding the possible barriers that continue to impede the sustainable performance of SCs in the post-COVID-19 era has become essential. This study aims to investigate and analyze the barriers to achieving sustainability in the pharmaceutical SC of an emerging economy in a bid to help decision-makers recognize the most influential barriers. Design/methodology/approach - To achieve the goals, two decision-making tools are integrated to analyze the most critical barriers: interpretive structural modeling (ISM) and the matrix of cross-impact multiplications applied to classification (MICMAC). In contrast to other multi-criteria decision-making (MCDM) approaches, ISM develops a hierarchical decision tool for decision-makers and cluster analysis of the barriers using the MICMAC method based on their driving and dependency powers. Findings - The findings reveal that the major barriers are in a four-level hierarchical relationship where "Insufficient SC strategic plans to ensure agility during crisis" acts as the most critical barrier, followed by "Poor information structure among SC contributors," and "Inadequate risk management policy under pandemic." Finally, the MICMAC analysis validates the findings from the ISM approach. Originality/value - This study provides meaningful insights into barriers to achieving sustainability in pharmaceutical SCs in the post-COVID-19 era. The study can help pharmaceutical SC practitioners to better understand what can go wrong in post-COVID-19, and develop actionable strategies to ensure sustainability and resilience in practitioners' SCs.

A comparative study to assess mental health literacy, impact of event, depression, anxiety, and stress levels of medical and other students during the second wave of the COVID-19 pandemic

Background: COVID-19 pandemic is negatively affecting the mental health of medical professionals as well as medical students, as they stand in the frontline. Medical education is recognized as stressful across the globe and in the hour of present crisis, students have to stay back home and continue their studies online. Aims: The aim of the study is to compare the emerging evidence of the effects of the COVID-19 outbreak on mental health and assess mental health awareness of medical students and other students studying in a Medical College of Eastern India. Materials and Methods: This cross-sectional observational study was conducted in a period of 3 months after taking Institutional ethical clearance and informed consent of the subjects. 212 medical students and 101 students of other courses studying in the college participated in the study. The present survey was conducted online using Google Forms. In the first section of the form, purpose of the study was explained and informed consent was taken from the participants. In the second part of the form, participants were asked to fill up demographic details and relevant history;in the third part, participants had to fill up three scales: Depression, Anxiety and Stress Scale-21, Impact of Event Scale-Revised (IRE-R), Mental Health Literacy Scale. Results: There was no significant difference in depression scores between the two groups. Anxiety scores and stress scores were significantly higher among medical students as compared to the other group with P = 0.0017 and 0.008, respectively. Group A: Anxiety scores 12.34 +/- 8.5;Stress scores -13.07 +/- 8.01. Group B: Anxiety scores 9.34 +/- 7.34;Stress scores -10.55 +/- 7.62. There was no significant difference in mental health literacy scores between the two groups. Mental Health literacy scores of Group A: 96.84 +/- 17.29;Mental health literacy score of Group B: 99.86 +/- 13.39;P = 0.09. No difference in IRE-R scores between the two groups was observed. Group A: Total score -21.81 +/- 14.34;Avoidance scale -9.43 +/- 6.1;intrusion scale 8.58 +/- 5.12;Hyperarousal scale -3.79 +/- 2.94. Group B: Total score -20.39 +/- 14.34;Avoidance scale -9.06 +/- 6.5;Intrusion scale -7.84 +/- 5.95;Hyperarousal scale -3.49 +/- 3.21. Conclusions: Mental health literacy scores and impact of event score were similar in medical and other students studying in the same medical institution. Medical students had significantly higher levels of anxiety and stress as compared to the other group, though depression scores of both groups were comparable. Hence, it may be concluded that medical students perceived higher levels of anxiety and stress during the second wave of the present COVID-19 pandemic.

UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

Biomedical image segmentation (BIS) task is challenging due to the variations in organ types, position, shape, size, scale, orientation, and image contrast. Conventional methods lack accurate and automated designs. Artificial intelligence (AI)-based UNet has recently dominated BIS. This is the first review of its kind that microscopically addressed UNet types by complexity, stratification of UNet by its components, addressing UNet in vascular vs. non-vascular framework, the key to segmentation challenge vs. UNet-based architecture, and finally interfacing the three facets of AI, the pruning, the explainable AI (XAI), and the AI-bias. PRISMA was used to select 267 UNet-based studies. Five classes were identified and labeled as conventional UNet, superior UNet, attention-channel UNet, hybrid UNet, and ensemble UNet. We discovered 81 variations of UNet by considering six kinds of components, namely encoder, decoder, skip connection, bridge network, loss function, and their combination. Vascular vs. non-vascular UNet architecture was compared. AP(ai)Bias 2.0-UNet was identified in these UNet classes based on (i) attributes of UNet architecture and its performance, (ii) explainable AI (XAI), and, (iii) pruning (compression). Five bias methods such as (i) ranking, (ii) radial, (iii) regional area, (iv) PROBAST, and (v) ROBINS-I were applied and compared using a Venn diagram. Vascular and non-vascular UNet systems dominated with sUNet classes with attention. Most of the studies suffered from a low interest in XAI and pruning strategies. None of the UNet models qualified to be bias-free. There is a need to move from paper-to-practice paradigms for clinical evaluation and settings.

Recent advancement in nanomaterial-encapsulated drug delivery vehicles for combating cancer, COVID-19, and HIV-like chronic diseases

Nanotechnology has gained immense attention owing to its multidimensional advantages in the scientific world. Recent progress has confirmed that nanostructured architectures possess promising medicinal applications and have triggered investigation as nanodrug delivery vehicles. These engineered vehicles offer an unprecedented platform for the controlled release of encapsulated drug to targeted site with higher effectuality and reduced toxicity by overcoming the loopholes allied with conventional drug delivery systems. This review provides a systematic overview of specific properties of nanostructured materials, viz., inorganic nanoparticles, polymeric micelles, chitosan, liposomes, dendrimers, carbon nanotubes, quantum dots, and niosomes, and consolidates their therapeutic approaches in the diagnosis and treatment of chronic diseases such as cancer, COVID-19, and HIV/AIDS. Factors including interactions of nanomaterials with physiological environment, mode of drug administration, stability of therapeutic agents, and mechanism of action have been summarized for attaining efficacious drug delivery. In addition to opportunities, the challenges of nanomedicines in drug delivery have also been discussed. In the futuristic perspective, further advancement is necessitated in the domain of nanotechnology mediated advanced drug delivery system by combining newer treatment approaches such as gene therapy and immunotherapy with the existing nanotechnology to improve the performance of drugs and maximize the efficiency of targeted drug distribution. © 2023 The Author(s).

Suramin binds and inhibits infection of SARS-CoV-2 through both spike protein-heparan sulfate and ACE2 receptor interactions.

SARS-CoV-2 receptor binding domains (RBDs) interact with both the ACE2 receptor and heparan sulfate on the surface of host cells to enhance SARS-CoV-2 infection. We show that suramin, a polysulfated synthetic drug, binds to the ACE2 receptor and heparan sulfate binding sites on the RBDs of wild-type, Delta, and Omicron variants. Specifically, heparan sulfate and suramin had enhanced preferential binding for Omicron RBD, and suramin is most potent against the live SARS-CoV-2 Omicron variant (B.1.1.529) when compared to wild type and Delta (B.1.617.2) variants in vitro. These results suggest that inhibition of live virus infection occurs through dual SARS-CoV-2 targets of S-protein binding and previously reported RNA-dependent RNA polymerase inhibition and offers the possibility for this and other polysulfated molecules to be used as potential therapeutic and prophylactic options against COVID-19.

Risk factors and vectors for SARS-CoV-2 household transmission: a prospective, longitudinal cohort study.

BACKGROUND: Despite circumstantial evidence for aerosol and fomite spread of SARS-CoV-2, empirical data linking either pathway with transmission are scarce. Here we aimed to assess whether the presence of SARS-CoV-2 on frequently-touched surfaces and residents' hands was a predictor of SARS-CoV-2 household transmission. METHODS: In this longitudinal cohort study, during the pre-alpha (September to December, 2020) and alpha (B.1.1.7; December, 2020, to April, 2021) SARS-CoV-2 variant waves, we prospectively recruited contacts from households exposed to newly diagnosed COVID-19 primary cases, in London, UK. To maximally capture transmission events, contacts were recruited regardless of symptom status and serially tested for SARS-CoV-2 infection by RT-PCR on upper respiratory tract (URT) samples and, in a subcohort, by serial serology. Contacts' hands, primary cases' hands, and frequently-touched surface-samples from communal areas were tested for SARS-CoV-2 RNA. SARS-CoV-2 URT isolates from 25 primary case-contact pairs underwent whole-genome sequencing (WGS). FINDINGS: From Aug 1, 2020, until March 31, 2021, 620 contacts of PCR-confirmed SARS-CoV-2-infected primary cases were recruited. 414 household contacts (from 279 households) with available serial URT PCR results were analysed in the full household contacts' cohort, and of those, 134 contacts with available longitudinal serology data and not vaccinated pre-enrolment were analysed in the serology subcohort. Household infection rate was 28·4% (95% CI 20·8-37·5) for pre-alpha-exposed contacts and 51·8% (42·5-61·0) for alpha-exposed contacts (p=0·0047). Primary cases' URT RNA viral load did not correlate with transmission, but was associated with detection of SARS-CoV-2 RNA on their hands (p=0·031). SARS-CoV-2 detected on primary cases' hands, in turn, predicted contacts' risk of infection (adjusted relative risk [aRR]=1·70 [95% CI 1·24-2·31]), as did SARS-CoV-2 RNA presence on household surfaces (aRR=1·66 [1·09-2·55]) and contacts' hands (aRR=2·06 [1·57-2·69]). In six contacts with an initial negative URT PCR result, hand-swab (n=3) and household surface-swab (n=3) PCR positivity preceded URT PCR positivity. WGS corroborated household transmission. INTERPRETATION: Presence of SARS-CoV-2 RNA on primary cases' and contacts' hands and on frequently-touched household surfaces associates with transmission, identifying these as potential vectors for spread in households. FUNDING: National Institute for Health Research Health Protection Research Unit in Respiratory Infections, Medical Research Council.

A Multiplexed Cas13-Based Assay with Point-of-Care Attributes for Simultaneous COVID-19 Diagnosis and Variant Surveillance.

Point-of-care (POC) nucleic acid detection technologies are poised to aid gold-standard technologies in controlling the COVID-19 pandemic, yet shortcomings in the capability to perform critically needed complex detection-such as multiplexed detection for viral variant surveillance-may limit their widespread adoption. Herein, we developed a robust multiplexed clustered regularly interspaced short palindromic repeats (CRISPR)-based detection using LwaCas13a and PsmCas13b to simultaneously diagnose severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and pinpoint the causative SARS-CoV-2 variant of concern (VOC)-including globally dominant VOCs Delta (B.1.617.2) and Omicron (B.1.1.529)-all the while maintaining high levels of accuracy upon the detection of multiple SARS-CoV-2 gene targets. The platform has several attributes suitable for POC use: premixed, freeze-dried reagents for easy use and storage; convenient direct-to-eye or smartphone-based readouts; and a one-pot variant of the multiplexed detection. To reduce reliance on proprietary reagents and enable sustainable use of such a technology in low- and middle-income countries, we locally produced and formulated our own recombinase polymerase amplification reaction and demonstrated its equivalent efficiency to commercial counterparts. Our tool-CRISPR-based detection for simultaneous COVID-19 diagnosis and variant surveillance that can be locally manufactured-may enable sustainable use of CRISPR diagnostics technologies for COVID-19 and other diseases in POC settings.

Advances and Application of Artificial Intelligence and Machine Learning in the Field of Cardiovascular Diseases and Its Role During the Pandemic Condition

Artificial intelligence (AI) has shown an immense potential to affect diverse domains of healthcare during the COVID-19 pandemic. The applications of AI in the field of cardiovascular disorders during the COVID-19 pandemic were an added advantage to the cardiologists, as it helped in certain aspects of treatments digitally. This technology is constructive for providing sophisticated treatment in the area of cardiovascular medicine based on technology, because it may assist in assessing and measuring the human heart function. Artificial intelligence employs simulated neuronal program for predicting the survival of a COVID-19 patient affected with heart dysfunction. AI entails intricate algorithms for predicting successful evaluation and therefore the treatment protocol. AI utilizes various methods like cognitive computing, deep learning, and machine learning. It is integrated to make an assessment and determine multifaceted challenges. In humans, cardiovascular disease is still one of the major causes of death, and it is escalating for years together and is also very expensive. AI is employed to recognize new drug treatment and advance the efficacy of a clinician. AI is turning into a well-approved attribute of a variety of engineering and healthcare segments and is being expected to provide a feasible treatment stage. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

An integrated framework for digitalization of humanitarian supply chains in post COVID-19 era

Digital Supply Chains (DSCs) are transforming industries across various domains. Digitalization can improve coordination, increase data collection and retention capacities, enhance funding mechanisms, and improve operational performance and resource utilization. However, DSC adoption is constrained by lack of funding, operational complexities, infrastructure issues, etc. Thus, the need emerges to explore the digitalization of the Humanitarian Supply Chain (HSC) and provide solutions that can ease the adoption of DSC. In this study, a framework is created to facilitate the digitalization process of HSC in post COVID-19 era. Nineteen related drivers are identified with the potential to digitalize the HSC. The drivers are identified from the previous literature and finalized with the assistance of HSC stakeholders. A Principal Component Analysis is carried out to discover the most pertinent drivers from the identified list of drivers. A Kappa analysis is adopted to perfect the priority map of the digitalization drivers. Further, the neutrosophic DEMATEL methodology is adopted to prioritize the potential drivers and find their dependency on each other. The results from the study indicate that the most influential drivers fall under the operational and technological categories. However, the social drivers have the potential to play a significant contribution in an effort to HSC digitalization. In addition, the study presents strategies for enhancing funds collection and data management using emerging technologies. These strategies can assist HSC decision-makers in formulating relevant policies and strategic interventions. © 2023 Elsevier Ltd

Lung-on-chip: Its current and future perspective on pharmaceutical and biomedical applications

Organ-on-a-chip is a three-dimensional microfluidic system that simulates the cellular structure and biological milieu of an organ, that seemed to be constructed and studied substantially in the last decade. Microchips can be configured to suit disease states in a variety of organs, including the lung. When contrasted to traditional in vitro models like monolayer cell lineages, lung-on-a-chip models lays out a pragmatic portrayal of disease pathophysiology and pharmaceuticals' mode of action, and this is especially more prevailing in connection with the COVID-19 pandemic. Animal models have typically been used in pharmaceutical drug screening to assess pharmacological and toxicological reactions to a new entity. These adaptations, on the other hand, do not precisely represent biological reactions in humans. Present and prospective uses of the lung-on-a-chip model in the pulmonary system are highlighted in this overview. In addition, the constraints of existing in vitro systems for respiratory disease simulation and therapeutic discovery would be emphasized. Attributes of lung-on-a-chip transformative features in biomedical applications will be addressed to illustrate the relevance of this lung-on-chip model for medical science.Copyright © 2022