Frontiers: Unmasking Social Compliance Behavior During the Pandemic

In 2020, as the novel coronavirus spread globally, face masks were recommended in public settings to protect against and slow down viral transmission. People complied to varying extents, and their reactions may have been driven by a variety of psychological fac-tors. Based on the literature on social influence and on mask-wearing, we define three cus-tomer segments: Fully-Compliant customers wear masks, and they seem motivated primarily by concerns about their own health risk. Partially-Compliant customers also wear masks, but with improper and ineffective coverage;our empirical analysis suggests that they are moti-vated primarily by a desire to comply with social norms. Finally, Unmasked customers do not wear masks. We examine changes in shopping behaviors with the onset of the pandemic to corroborate the conjectured mask-wearing motives. We find that the three groups made significantly different behavior changes: Fully-Compliant customers shopped significantly faster and practiced stricter social distancing with the onset of the pandemic, whereas the other two groups did not adjust their shopping duration or social distancing.

Examining Disease Multimorbidity in U.S. Hospital Visits Before and During COVID-19 Pandemic: A Graph Analytics Approach

Enduring effects of the COVID-19 pandemic on healthcare systems can be preempted by identifying patterns in diseases recorded in hospital visits over time. Disease multimorbidity or simultaneous occurrence of multiple diseases is a growing global public health challenge as populations age and long-term conditions become more prevalent. We propose a graph analytics framework for analyzing disease multimorbidity in hospital visits. Within the framework, we propose a graph model to explain multimorbidity as a function of prevalence, category, and chronic nature of the underlying disease. We apply our model to examine and compare multimorbidity patterns in public hospitals in Arizona, U.S., during five six-month time periods before and during the pandemic. We observe that while multimorbidity increased by 34.26% and 41.04% during peak pandemic for mental disorders and respiratory disorders respectively, the gradients for endocrine diseases and circulatory disorders were not significant. Multimorbidity for acute conditions is observed to be decreasing during the pandemic while multimorbidity for chronic conditions remains unchanged. Our graph analytics framework provides guidelines for empirical analysis of disease multimorbidity using electronic health records. The patterns identified using our proposed graph model informs future research and healthcare policy makers for pre-emptive decision making. © 2023 Association for Computing Machinery.

Impact of the covid-19 pandemic on lung cancer referraland treatment

Background: UK restrictions during covid-19 impacted lung cancer care including referrals into secondary care. Aim(s): (1) document pattern of referrals to this semi-rural Trust, (2) evidence any later presentation of disease, and(3) report impact on treatment. Method(s): Data was collected retrospectively and analysed for pre-covid, lockdown/restriction period, and post-relaxation of rules. Non-parametric data were analysed by chi square (X2) analysis for trend. Result(s): Fall in referrals pivoted on the initial UK peak in 2020 with a slow recovery in two week wait referrals post-lockdown (43%, previously 60%). Table 1 shows distribution in disease stage negatively skewed (all >2.46) with themajority at stage 4. Trend showed no statistical difference in stage with X2 (df 6, n=792, = 3.831, p=.6995) andsimilarly when re-analysing earlier stages. Treatment outcome shows non-significant trends to increased palliativecare (28 to 35%) and radiotherapy (10 to 18%), with less chemotherapy (25 to 21%) or surgery (26 to 15%). Conclusion(s): Locally, lung cancer diagnosis numbers have been maintained, with a similar stage at presentation but a change in referral pattern favouring emergency/upgraded presentation may signal reduced access to primary care.

Profile of Patients Attending Telepsychiatry Unit and its Usability and Satisfaction during Pandemic in South India - A Retrospective Study

Background: The COVID-19 pandemic is an unexpected event that has led to a drastic shift in the practice of medicine around the world. Currently, not many studies are available in India regarding the role of telepsychiatry and no study has been done to assess the usability and satisfaction scores of patients who undergo a telepsychiatric consultation. Aim: The aim of the study is to find the profile of patients attending the telepsychiatry Unit and its usability and satisfaction during the pandemic in South India. Setting and Design: The study was conducted on patients attending telepsychiatric consultation from a period of March 25, 2020, to September 2020. Materials and Methods: A retrospective chart analysis of patients attending telepsychiatry consultation from March 25, 2020, to September 2020 was made. Patients who underwent video consultation were asked to fill out the telehealth usability questionnaire scale through Google Forms. The usability of the telehealth system was assessed using a Likert Scale and scoring was done. Statistical Analysis: Descriptive statistics were used to characterize the study population. Statistical significance was set at P < 0.05. The design and findings of this study were written in accordance with SQUIRE 2.0 guidelines. Results: Twenty-two percent of the study population had consultation for more than fourtimes. Around 78% of the study population had online consultation for less than four times. More than 74% of the study population had video consultation and 26% of the study population had audio consultation. The total average Telehealth Usability Questionaire score was 5.3. The usefulness score summary was found to have a low score of 5.2 +/- 0.6, whereas the satisfaction scale summary was found to have the highest score of 5.3 + 0.9. Conclusion: Profile of patients who attend a telepsychiatry unit during the crisis and their satisfaction helped us to know the pros and cons of online consultation and the ways to improve telemedicine in regard to psychiatric patient care. Our study shows that majority are satisfied with telepsychiatric consultation.

Design of IMC Based PI Controllers for Three Tank Interacting Level Control Process

India is a country that consists of most process industries, where most of the end products are related to water or other liquid state materials. In recent days pharmaceutical industries have grown on a larger scale due to the COVID'19 situation. One of the major processes is to maintain the level of the liquid for having a continuous process. In this proposed process, Proportional Integral (PI), Internal Model Controller (IMC) based PI is implemented on a three-tank integrating system with two input and two output (TITO). IMC-PI gain values are acquired and decoupled using the decoupler matrix by determining RHP poles and zeros for the TITO system. Since two input tanks are involved, therefore two different gain values are calculated keep the liquid at the given level. The proposed system has given has resulted with 180 seconds and 190 seconds for Settling time and 5% and 0% of Overshoot for two tanks. © 2022 IEEE.

Applications of IoT and Cloud Computing: A COVID-19 Disaster Perspective

The utility of Internet of Things (IoT) and cloud computing has become indispensable in various industrial sectors. This chapter provides a brief insight into the application of IoT and cloud computing in education, entertainment, transportation, manufacturing, healthcare and agriculture. Besides, it also discusses the future opportunities for such emerging technologies in these sectors. Further, there have been massive developments in the field of cloud computing which has played a crucial role in ensuring a proper learning environment and resources. The entertainment industry has also seen changes similar to the ones in the education industry. The transportation and logistics industry was impacted heavily during the COVID-19 pandemic. With technologies breaking benchmarks time and again, technology will soon make a huge difference with respect to transportation. The need and ability to control various aspects of a manufacturing pipeline remotely and wirelessly has been a domain of interest for many researchers and scholars and the need is increasing day by day. The healthcare industry envisions transforming a hospital-centric approach into a complete healthcare experience at the comfort of your home using the latest technologies including IoT and cloud computing. This crisis due to the pandemic has forced farmers to look towards technology;therefore, IoT-based agricultural solutions have become popular all across the world. Finally, this chapter also discusses the future opportunities provided by these technologies in handling the day-to-day livelihood during such pandemic disasters. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Preserving Location Privacy in the IoT against Advanced Attacks using Deep Learning

Location-based services (LBSs) have received a significant amount of recent attention from the research community due to their valuable benefits in various aspects of society. In addition, the dependency on LBS in the performance of daily tasks has increased dramatically, especially after the spread of the COVID-19 pandemic. LBS users use their real location to build LBS queries to take benefits. This makes location privacy vulnerable to attacks. The privacy issue is accentuated if the attacker is an LBS provider since all information about users is accessible. Moreover, the attacker can apply advanced attacks, such as map matching and semantic location attacks. In response to these issues, this work employs artificial intelligence to build a robust defense against advanced location privacy attacks. The key idea behind protecting the location privacy of LBS users is to generate smart dummy locations. Smart dummy locations are false locations with the same query probability as the real location, but they are far from both the real location and each other. Relying on the previous two conditions, the deep-learning-based intelligent finder ensures a high level of location privacy protection against advanced attacks. The attacker cannot recognize the dummies from the real location and cannot isolate the real location by a filtering process. In terms of entropy (the privacy protection metric), accuracy (the deep learning metric), and total execution time (the performance metric) and compared to the well-known DDA and BDA systems, the proposed system shows better results, where entropy = 15.9, accuracy = 9.9, and total execution time = 17 sec. © 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved.

Optimal Anticoagulant Dosing in Patients with COVID-19, a Retrospective Review

Background Hospitalized patients with coronavirus disease 2019 (COVID-19) infection have higher rates of venous thromboembolism (VTE).Higher mortality rates have been reported in severe cases of COVID-19 including those who have elevated D-dimer levels and have thromboembolic phenomena. Objective The objective of this retrospective and observational study was to ascertain which type and dosages of anticoagulation provide a mortality benefit and decrease the risk of developing VTE. Methods We evaluated the risk factors for VTEs in patients with a confirmed polymerase chain reaction test positive for COVID-19 who were admitted to our facility from April 1 to July 1, 2020. In addition, we performed a logistic regression to examine the relationship between mortality and intensive care unit (ICU) admission, specific risk factors outlined in the study, D-dimer, ferritin, prothrombin time (PT) and international normalized ratio (INR). Patients with a history of VTE, those already on anticoagulation (AC) prior to hospitalization, and patients on comfort care were excluded from study. Results There were originally 331 patients in the data set. Of those, 111 patients were excluded based on exclusion criteria and 4 additional patients were removed as they were the only individual patients in their specific AC covariant group. The analysis was performed on the remaining 216 patients. We divided the AC medications administered to the patients into five separate covariates: 1. enoxaparin 40 mg subcutaneous (sq) daily, 2. enoxaparin 40 mg sq every 12 hours (q12h), 3. heparin 5000 mg sq q12h, 4. heparin 5000 mg sq every 8 hours (q8h), 5. Patients taking multiple AC or deep venous thrombosis (DVT) prophylaxis medications. 6. No AC and examined them via logistic regression for mortality at 28 days and 60 days (Table 1). Patients in enoxaparin 40 mg daily group had statistically significant lower 28 day mortality. There was no statistically significant relationship between the use of enoxaparin 40 mg q12h and 28 day mortality rate. Patients in both heparin groups did not have significantly lower 28 day mortality rates. Patients in groups 5 & 6 had significantly higher 28 day mortality rates (Table 1). It is important to note that 33 patients underwent a pulmonary computed tomography angiography due to concern for pulmonary embolism and 38 patients underwent an ultrasound of their lower extremities to rule out the development of DVT. For patients with additional risk factors defined as chronic kidney disease, chronic obstructive pulmonary disease, organ transplant recipient, obesity (BMI > 30), cardiac disease (heart failure, coronary artery disease or cardiomyopathy), sickle cell disease, diabetes mellitus and smoking history, the odds of death at 28 days increased by a factor of 1.71, at 60 days by a factor of 1.63 and being admitted to the ICU by a factor of 1.41. Patients with 3-5 risk factors are 2.48 times more likely to be admitted to the ICU than patients with 0-2 risk factors. Patients with 4 or 5 risk factors are 3.56 times more likely to be admitted to the ICU than patients with 0-3 risk factors (Table 2). Predictably, patients that were admitted to the ICU had a significantly increased rate of mortality compared to those who were not (Table 3). Per our analysis, there was no relationship between PT or INR and mortality. At 28 days and 2 months, the D-dimer > 4000 was indicative of a higher odds of death versus patients with a D-dimer < 4000. An increased ferritin was also indicative of a higher mortality rate (Table 4). Conclusion Patients receiving enoxaparin 40 mg daily benefited more than any other AC regimen with respect to the development of VTE at both 28 days and 2 months. Increasing the dosing to twice daily did not decrease mortality. Additionally, patients receiving heparin did not have a decreased mortality. It is important to note that there was no standard protocol used to determine which patients received daily or twice daily dosing. The type and dose of AC was determined based on the clinical judgment of int nsivists in each case. It is also possible that patients with severe COVID-19 infection were more likely to be given twice daily dosing which could account for the lack of mortality benefit with more frequent dosing. We did not report bleeding rates in AC groups in our study and this can be a possible reason for no mortality benefit among higher dose AC groups. [Formula presented] Disclosures: No relevant conflicts of interest to declare.

BLOOD CULTURES IN PATIENTS WITH ACUTE COVID-19 PNEUMONITIS: CONTAMINATION OR BACTERIAL CO-INFECTION?

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: INTRODUCTION: Research shows that 90% of blood cultures show no growth and a third of the remainder who test positive are identified as false positives [Garcia RA et al. Am J Infect Control 2015]. Although blood culture contamination rates of <1% are achievable, historical rates at <3% are industry accepted standards[Wayne PA. Clinical and laboratory Standards Institute (CLSI) document M47-A;2007];contaminants from skin flora are the most common, but 20% are from microbes deep in the dermis layer which may be drawn into blood specimens. Evidence for early use of antibiotics managing patients with COVID-19 pneumonitis is lacking but there are anecdotal concerns that more blood cultures than usual have identified organisms usually considered contaminants in sampling. Objectives were to quantify our local findings and relate these to outcome at discharge and during follow up. METHODS: Computer based retrospective review of 228 patients, mean age 71.8 (SD 8.7, range 29-87) years admitted at this hospital between March-May 2020 during the UK COVID-19 (SARS-Cov-2 RNA) peak and surge. Blood cultures reported here correspond to initial presentation with COVID-19 following a sepsis protocol. Comparative analysis by chi square (X2). RESULTS: 137/228 (60%) of patients had blood cultures at admission. 21/137 (15.3%) identified organisms from either one (n=13) or both (n=8) aerobic and anaerobic blood culture bottles. 12/21 (57.1%) (8 died) were identified as coagulase negative staphylococci (CoNS), traditionally considered contaminants at sampling;others included coagulase positive staph aureus (2), Klebsiella (2), E coli (2), and one each for Diptheroids, Proteus Miribalis and Aerococcus Viridans. The remaining 116 reported no growth from initial samples but 3 had positive results later in the admission (2 with CoNS, 1 with E Coli). 7/21 (33.3%) of those with any growth had died during the admission and this was proportionately similar to the 38/116 (32.8%) with no growth on blood cultures [X20.0027, p=.9588, not significant]. At 6 month follow up however, 15/21 (71.4%) of those who had positive findings on original cultures had died compared with 48/116 (41.4%) that had shown no growth [X26.4639, p=.0110, statistically significant]. CONCLUSIONS: Although death rates during admission did not differ, comparing those with and without positive findings on initial blood cultures, a large percentage with positive initial findings then died during follow up. Despite several organisms traditionally considered contaminants, the higher (15.3%) reporting and potential false positive rates requires further study;this should address sampling errors but also revisit bacterial co-infection in COVID-19. CLINICAL IMPLICATIONS: Improving sampling for blood cultures, but research is also needed to make sure this is not a signal for underlying bacterial co-infection. DISCLOSURES: No relevant relationships by Nawaid Ahmad, source=Web Response No relevant relationships by Emma-Jane Crawford, source=Web Response No relevant relationships by Annabel Makan, source=Web Response No relevant relationships by Nikhita Moudgil, source=Web Response No relevant relationships by Harmesh Moudgil, source=Web Response No relevant relationships by Afrah Riaz, source=Web Response No relevant relationships by Koottalai Srinivasan, source=Web Response

Reduced vitamin d levels associated with increased COVID-19 related deaths

RATIONALE: Vitamin D supports immunity and inflammation by inhibiting proinflammatory cytokine release from macrophages and up-regulating the expression of anti-microbial peptides exhibiting anti-viral activity. Respiratory epithelial cells also convert inactive 25(OH)D (main circulating vitamin D) to 1,25(OH)2D3 enabling high local concentrations of this biologically active form to increase the expression of vitamin D-regulated genes. Studies continue to investigate the therapeutic effects and establish the optimal serum levels of 25(OH)D required to reduce the impact of respiratory tract infections whilst avoiding toxic hypercalcaemic high-dose 'blind' supplementation. Analysing patients admitted to hospital with COVID-19 (SARS-CoV-2 RNA) during the first phase of the pandemic, objectives and focus on reporting were to (1) document the population where measured vitamin D levels are readily available whilst quantifying those on supplements and (2) compare outcome at discharge depending on most recent available vitamin D status. METHODS: Computer data including clinical outcomes were examined for the 516 patients (55% male) with mean age 67.4 (SD 18.3, range 0 to 100) years admitted from our semi-rural predominantly white European population to our District General Hospitals (Teaching) during the 4 months (March to June 2020) in the first phase of the COVID-19 illness in the UK. Outcomes (death during admission versus discharged alive) were analysed with SPSS comparing those with reduced versus adequate vitamin D levels. RESULTS: Collectively (n=516), vitamin D levels (historical or updated) were available on 163 (31.5%) of patients;17 (3.3%) undertaken during the admission. Data were skewed with median level 47 (interquartile range 24.1 to 66.9) nmol/L. 74 (14.3%) were already on vitamin D supplements and for an additional 10 (1.9%) this was initiated during the admission. Among the 163 patients, 86 (52.7%) had reduced vitamin D levels (deficient or insufficient) and these had worse outcomes with 29/86 (33.7%) having died during the admission compared with 13/74 (17.6%) of those with adequate levels: X2 (df 1, n=163) 6.02, p=.014. Table 1 categorises distribution of values. CONCLUSIONS: Data highlight (1) less than a third of admitted COVID-19 patients have recorded vitamin D levels and of these more than half have reduced levels, (2) 14.3% are already taking vitamin D, (3) very few get tested during the acute admission or get started on supplements, and (4) there is a statistical difference highlighting adverse outcome (death versus discharged alive) for those with reduced vitamin D levels.

Fuzzy Logic-Based Health Monitoring System for COVID'19 Patients

In several countries, the ageing population contour focuses on high healthcare costs and overloaded health care environments. Pervasive health care monitoring system can be a potential alternative, especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care, mobile care and home care. In this aspect, we propose a pervasive system to monitor the COVID'19 patient's conditions within the hospital and outside by monitoring their medical and psychological situation. It facilitates better healthcare assistance, especially for COVID'19 patients and quarantined people. It identifies the patient's medical and psychological condition based on the current context and activities using a fuzzy context-aware reasoning engine based model. Fuzzy reasoning engine makes decisions using linguistic rules based on inference mechanisms that support the patient condition identification. Linguistics rules are framed based on the fuzzy set attributes belong to different context types. The fuzzy semantic rules are used to identify the relationship among the attributes, and the reasoning engine is used to ensure precise real-time context interpretation and current evaluation of the situation. Outcomes are measured using a fuzzy logic-based context reasoning system under simulation. The results indicate the usefulness of monitoring the COVID'19 patients based on the current context.

Contemporary Analysis of Olfactory Dysfunction in Mild to Moderate Covid 19 Patients in A Tertiary Health Care Centre.

INTRODUCTION: The World Health Organization declared COVID-19 a pandemic on March 11, 2020. The virus that causes COVID-19 was designated as severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). Several studies have reported chemosensory dysfunction, such as anosmia and ageusia, as common findings in COVID-19 positive patients. To date, qualitative olfactory testing has been performed only in a very few cohort studies on COVID-19 patients. However, objective testing is necessary to verify or determine the true magnitude of their deficits. Moreover, the proportion of COVID-19 patients exhibiting true olfactory disturbances is unknown. AIM OF THE STUDY: To determine the true prevalence of olfactory dysfunction in COVID-19 patients by objective assessment in mild to moderate symptomatic patients. MATERIALS & METHODOLOGY: This was a prospective cross-sectional analytical study. All patients who were COVID-19 positive and having mild to moderate symptoms and not admitted in ICU formed part of the study group. Objective evaluation of smell function was done. RESULTS: Self-reported smell dysfunction was present in 26.9% patients (n=62) and taste dysfunction was seen in 10.9% (n=25) of patients. On quantitative assessment of smell dysfunction, it was noted that 41.3% (n=95) of patients had some form of smell dysfunction out of which 70.5% patients (n=67) had hyposmia and 29.5% patients (n=28) had anosmia. CONCLUSION: Incidence was found to be more by objective assessment when compared to self-reported symptoms.