COVID-19 during the Third Semester of Pregnancy: Maternal Characteristic, Possibility of Intrauterine Transmission and Neonatal Outcome in Aceh, Indonesia

BACKGROUND: Pregnant women are vulnerable against COVID-19 infection due to physiological and immunological changes. COVID-19 in pregnancy affects fetal well-being with a potential for vertical infection. AIM: This study aims to determine the incidence of vertical infection and anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in infants born to mothers with positive COVID-19 infection. MATERIALS AND METHODS: Amniotic fluid, swabs of the newborn's nasopharynx and oropharynx, and swabs of the placenta were examined using reverse transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2. Serological examination was performed by Electro-Chemiluminescence Immunoassay on infant's blood. RESULT(S): Four of 33 pregnant women gave birth to infants positive SARS-CoV-2 infection. RT-PCR examination of all amniotic fluid and placental swabs was negative for SARS-CoV-2. Four of 33 infants (12.1%) showed negative polymerase chain reaction (PCR) results but positive SARS-CoV-2 antibodies, another 4 newborns (12.1%) showed positive PCR results, but no SARS-CoV-2 antibodies detected. The remaining 25 babies (75.8%) showed both negative PCR and serologic results. CONCLUSION(S): No evidence of vertical transmission found in this study.Copyright © 2023 Cut Meurah Yeni, Zinatul Hayati, Sarjani M. Ali, Hasanuddin Hasanuddin, Rusnaidi Rusnaidi, Cut Rika Maharani.

Sustainable supply chain in emerging economies during and post COVID-19 pandemic: a systematic literature review and future research directions

Purpose: COVID-19 pandemic interrupted global supply chains (SCs) affecting both developed and developing countries. In context of the COVID-19 pandemic, numerous studies were conducted on sustainable supply chain (SSC) in emerging markets (EMs). However, the contributions of these studies require to be systematically reviewed to provide a platform of knowledge. The purpose of this review is to systematically explore the relevant literature on SSC management during the COVID-19 pandemic in EMs. Design/methodology/approach: The authors applied Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to perform a systematic literature review. Scopus database was used to extract the relevant literature, and 51 journal articles along with 5 conference proceedings were included in the study. Findings: This study identified the major contents along with four different themes, which are the impacts of COVID-19 on the SC, recovery strategies to alleviate the adverse impacts of COVID-19, sustainable practices to improve SC performance and resilience activities to assure firms' survivability. Furthermore, the research reveals that interview/survey/case study–based research and review articles focusing on various industries have dominated the field of SSC management in the context of EMs. Originality/value: This research enriches the literature by providing an overall scenario of SSC during the COVID-19 pandemic in the context of emerging economies. © 2022, Emerald Publishing Limited.

Serum Procalcitonin Level and Comorbidity in Covid-19 Patients in UAE

Background: Most COVID-19 patients experience a mild form of the disease, but there is a certain percentage of patients who progress to a very severe disease state that requires intensive care and invasive ventilation. In order to ensure better patient management and improved outcomes, early identification of patients who may be at a higher risk of severe infection can play an important role. The aim of this study was to assess the association between the mean procalcitonin (PCT) level and comorbidity in hospitalized patients with COVID-19. Methods and Results: A total of 231 COVID-19-positive patients aged between 20 and 82 years (170[73.6 %] males and 61[26.4%] females) were included in this study. Serum PCT was accessed by procalcitonin assay using the Beckman Coulter UniCel DxI 800 instrument. All patients were classified into 5 groups according to age: 20-29 years-20(8.7%), 30-39 years-47(20.3%), 40-49 years-72(31.2%), 50-59 years-48(20.8%) and >60years-44(19.0%). Eighty-seven (37.7%) patients had no chronic disease, while 144(62.3%) had comorbidities: hypertension (37[16.0%]), diabetes mellitus (44[19.0%]), a combination of diabetes mellitus with hypertension (32[13.9%]), asthma (6[2.6%]), hyperlipidemia (4[1.7%]), renal disease (1[0.4%]), and COPD (1[0.4%]). COVID-19 patients with diabetes in combination with hypertension had a statistically greater PCT level than COVID-19 patients without comorbidities (P=0.0273). However, there were no statistically significant differences in the mean PCT levels between other comorbidities. There were no statistically significant differences in the mean PCT level between different age categories (P=0.7390). The serum PCT measurement could evaluate the prognosis of the disease in some COVID-19 patients. © 2022, International Medical Research and Development Corporation. All rights reserved.

Association of Papilledema with Headache Visualizing Via Smartphone Fundoscopy

Objective: To determine association of papilledema with headache using 20D lens and a smartphone for fundoscopy. Study Design: Prospective Cross-sectional Study Place and Duration of Study: This study was conducted at the Ophthalmology OPD at Liaqat National Hospital, Karachi from, 25th May 2022 till 25th July 2022. Materials and Methods: Patients, presenting to ophthalmology OPD at Liaqat National Hospital, patient complaining of blurring of vision and difficulty focusing on distant object were included in our study. We used a 20D lens for indirect ophthalmoscopy and smartphone camera for recording and taking pictures. Participant's pupils were dilated using 1% tropicamide drops and waited for 15-20 mins for pupil dilation. Video recording was done with flashlight switched on and recording was reviewed for fundus pictures and snap shots were taken from it. Results: 384 patients were included in the study. There were 65.6% male and 34.4% female patients in our study with mean age 41.93±13.50 years while majority (62.8%) were from age group >35 years. we found 3.6% of patients with obesity, 12.2% with diabetes mellitus, 14.3% with hypertension and 45.1% with headache and 7.3% of patients were found with papilledema. Strong association was found with papilledema and headache with p-value of <0.001. Conclusion: Strong association of papilledema with headache was found in patients who came with symptoms of blurry vision and We can reliably do fundus visualization with Smartphone based indirect ophthalmoscopy to view optic disc for presence of papilledema, can be cheap alternative to conventional ophthalmoscopy devices even in neurosurgical examinations, in covid-19 era where social distancing is a norm and proximity to the patients with direct ophthalmoscopy can be discomforting in these circumstances. © 2022 Medical Forum Monthly. All rights reserved.

Improving the benefits and cost of using emerging technologies for sustainable recovery from COVID-19 in manufacturing industries

The ongoing COVID-19 pandemic has manifold disastrous effect on different service and production sectors, and manufacturing industries are no exception. Emerging technologies (ETs) can play a pivotal role in reviving these ailing manufacturing industries. However, the cost of implementing and operating ETs is a prime concern. Nonetheless, the important attributes that will minimize the cost and harness the advantages of the technology are still to be explored. To address this gap, this research seeks to examine the critical attributes required for the effective and efficient deployment of ETs. At first, a detailed literature review was conducted to identify and sort the attributes influencing the effective use of ETs in manufacturing industries. After that, Fuzzy-TODIM (Portuguese abbreviation of "Interactive and Multi-Criteria Decision Making ") method was used to rate the importance of the attributes. The result reveals that, "Inventory and Resource Management " tops the attribute list responsible for exploiting the optimal usage ETs, followed by "Development of Skilled Workforce " and "Supplier and Service Management Capability, " respectively. This paper will assist industry professionals not only in using ETs but also getting the best yield from them strategically and practically.

The shock of the SARS-CoV-2 pandemic on health professionals’ education: A pilot qualitative study in Malaysia

Various measures were introduced globally to prevent the spread of COVID-19, including travel restrictions, social distancing, and closure of educational establishments. Implementing these measures resulted in appreciable changes to health professions’ education (HPE) with concerns regarding the level of preparedness among faculty members and students towards e-learning, including laboratory, clinical, and other forms of hands-on training. In addition, the affordability of devices and Internet bundles arose, especially among students in low and middle-income countries. A pilot qualitative study was conducted in Malaysia to ascertain critical challenges and how higher learning establishments addressed them. The study was undertaken among 10 purposely selected educators in both public and private universities in Malaysia using an established questionnaire to ascertain critical challenges and responses. The main issues included unfamiliarity with e-learning approaches and inadequate availability of devices and Internet bundles among students. Furthermore, the study revealed a lack of interaction between faculty members and students, concerns with conducting practicals and clinical examinations, and mental distress among faculty members. Measures introduced to address concerns included supporting digital needs through the provision of software, devices, and Internet bundles, enhanced training of educators in e-learning approaches, providing clinical case banks and curated patient data, and establishing clear policies and procedures for classroom and clinical teaching. Psychological support, including stress management, was also provided. The challenges and lessons learned in Malaysia regarding HPE during the pandemic were similar to other countries with hybrid learning here to stay. © 2022 Ambigga Krishnapillai et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Healthcare assessment for beauty centers using hybrid sentiment analysis

Because of COVID-19, healthcare became the first interesting domain at the world. Here, comes the role of researchers to do what they can to guide people. Nowadays, the most wanted field is beauty industry. It achieved large market. And the estimation is toward the growing. Researchers can give advice to prevent unhealthy causes in this field. They can apply sentiment analysis methods to make decision whether a Beauty center is healthy or unhealthy. This work develops an improved method of sentiment analysis to classify the beauty centers in Iraq into healthy and unhealthy classes. Researchers used comments of beauty centers’ Facebooks to perform the assessment. The methodologies encompass the two approaches lexicon-based and machine-learning-based. Three machine learning mechanisms had been applied;rough set theory, naïve bayes, and k-nearest neighbors. It will be shown that rough set theory is the best compared with the others two. Rough set theory achieved 95.2%, while Naïve Bayes achieved 87.5% and k-nearest neighbors achieved 78%. © 2022 Institute of Advanced Engineering and Science. All rights reserved.

Healthcare Monitoring Based on Cloud Computing: Case Study (Corona Virus)

COVID-19 (Corona Virus) is a very transmissible infection that has the world’s attention lastly. This virus can be transmitted from any patient to other people by direct contact,it could be spread if the person sneezes or coughs. It is also spread by touching a surface that contains a virus.In this paper, the intelligent healthcare system is proposed, that integrates cloud computing technologies. Its architecture utilizes smart sensors, microcontrollers, C ++ and the Php programming languages to program the Arduino and cluad. The temperature sensor, with an accuracy of 0.5 degrees, and the sound sensor are used in this paper. These sensors will send the data of the patient to the SQL database and cloud after encryption it by RSA algorithm. Finally the data transport to the monitor and the doctor or nurse can monitor the patients from web browser from any device such as smart phones, ipads, or PC computers from any place remotely without touching the patients. This architecture can reduce the transmission of infections by touch, in addition to monitoring all cases in a hospital without potential. The system tracks the state of patients and delivers timely, reliable, and high quality healthcare with minimum cost. The presented architecture will be useful in diagnosis research and healthcare systems.The computing cloud is necessary for highly challenging architectures like intelligent healthcare. The concept of intelligent architecture healthcare systems was to provide patient surveillance at all times, in addition to real time connectivity. In addition, the sensors are required for this architecture to be applied to any patient afflicted with any disease. Therefore, by adding the sensors are required.

Spatial Exploration of Social Vulnerability and COVID-19-Related Health Outcomes in Mississippi

The COVID-19 pandemic has caused more than 48 million cases and 800,000 deaths in the United States. Mississippi (MS) is one of the hardest-hit states with a high incidence and mortality compared to the US national average. This paper explores the relationship of MS county-level COVID-19-related incidence and mortality (through December 2, 2021) with the Center for Disease Control's Social Vulnerability Index (CDC SVI). The CDC SVI consists of four major subthemes: [1] socio-economic status, [2] household composition and disability, [3] minority status and language, and finally, [4] housing type and transportation. We found that the overall SVI ranking has a statistically significant association with reported COVID-19 cumulative mortality at the county level. Among the SVI subthemes, subtheme 1 (socio-economic status) and subtheme 2 (household composition and disability) showed a significant relationship with incidence and mortality (p < 0.05). The results of our analysis will assist in understanding the spatial relationship between CDC SVI themes and the health effects of COVID-19 in MS and the surrounding areas.

Applications of geospatial analyses in health research among homeless people: A systematic scoping review of available evidence

Background: Unequal housing access resulted in more than 150 million homeless people worldwide, with mil-lions more expected to be added every year due to the ongoing climate-related crises. Homeless population has a counterproductive effect on the social, psychological integration efforts by the community and exposure to other severe health-related issues. Geographic Information Systems (GIS) have long been applied in urban planning and policy, housing and homelessness, and health-related research. Methods: We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to systematically review 24 articles collected from multiple databases (n = 10) that focused on health-related issues among homeless people and used geospatial analysis techniques in their research. Results: Our findings indicated a geographic clustering of case study locations- 26 out of the 31 case study sites are from the USA and Canada. Studies used spatial analysis techniques to identify hotspots, clusters and patterns of patient location and population distribution. Studies also reported relationships among the location of homeless shelters and substance use, discarded needles, different infectious and non-infectious disease clusters. Conclusion: Most studies were restricted in analyzing and visualizing the patterns and disease clusters;however, geospatial analyses techniques are useful and offer diverse techniques for a more sophisticated understanding of the spatial characteristics of the health issues among homeless people. Better integration of GIS in health research among the homeless would help formulate sensible policies to counter health inequities among this vulnerable population group.

Prediction Of Covid-19 Infection Based on Lifestyle Habits Employing Random Forest Algorithm

A data of four factors contributing to covid-19 infection and whether the person has been infected or not is taken as input to train a Random Forest Algorithm. Factors like wearing mask, regularity of exercise, consumption of pepper and area population density are taken as input factors and the status of covid-19 infection is taken as output parameter. A random forest model trained with at least 50 data instances will become a powerful predictive model for assessing the risk of covid19 infection.

A Design of Self-Assisted Patient Control Technique for Early Rehabilitation Interventions to Prevent the Reduced elbow Joint ROM of COVID-19 Patients

The novel coronavirus, SARS-CoV-2 pandemic has posed new challenges for physiotherapist due to unprecedented acute care patients' surge. It contributed to minimize physical activity, especially reducing the elbow range of motion (ROM). Early rehabilitation and physiotherapy are recommended to combat the adverse effects of extended immobility. However, the increased patient-physiotherapist interaction increased risks of disease transmission. There emerges a need to minimize this interaction and disease transmission probability. This study aims to speed-up the return to regular ROM of COVID-19 patients by developing a self-assisted device for successful elbow therapy. The proposed device referred as 'self-assisted', reflects the idea of active and passive patient intervention and early rehabilitation. The device is designed and programmed to characterize the patients into three levels, depending on their ROM vulnerability: level 1 below 50 degrees, level 2 50 degrees-100 degrees and level 3 above 100 degrees. To examine the efficacy and accuracy of SAPT-COVID-19, eight volunteers with varying ages were selected, who were home-bound due to prolong COVID-19 pandemic and compromised their functional ROM. SAPT-COVID-19 substantially strengthened the elbow ROM for the volunteers and hit the maximum functional ROM over 14 -days exercise session, resulting in approximately 10 improvement in elbow ROM The degree of efficiency of active and passive exercise has also been widely examined. SAPT-COVID-19 is supposed to prevent elbow ROM deterioration and reduce hospitalization, with therapeutic and economic gain and minimized the physiotherapist-patient interactions.

Sentiment Analysis for COVID-19 Tweets Using Recurrent Neural Network (RNN) and Bidirectional Encoder Representations (BERT) Models

In the last few decades, social media usage has exponentially increased, and people often share information covering various topics of interest. The social media platforms such as Twitter allow users to share images, audio, videos, and text. The textual content can be used as a powerful tool for sentiment analysis. The main goal of this work is to investigate the deep learning models for sentiment analysis of tweets related to COVID-19. The dataset was obtained using tweeter web API between December 20, 2019, to December 15, 2020, and labels were assigned manually as positive, negative, or neutral. Two deep learning models were selected for sentiment analysis: Recurrent Neural Networks (RNN) and the Bidirectional Encoder Representations (BERT) model. The experimental results showed that both RNN and BERT models were effective for sentiment analysis, resulting in 86.4% and 83.14% accuracy, respectively. © 2021 IEEE.

Non-Verbal Communication in the Context of Social Presence in Virtual Space

Studies related to non-verbal communication in virtual space need to be explored as a result of changes in communication processes that largely rely on online interaction due to the COVID-19 pandemic. Undoubtedly, it has extended the scope of understanding an individual's virtual presence and the effectiveness of non-verbal communication practices. In this study, non-verbal communication is explored in the process of online teaching and learning. Social Presence Theory has been used in understanding the practice of lecturers to establish relationships through their virtual presence and build closeness with students during online teaching and learning. In-depth interviews were conducted with a total of ten students of Universiti Utara Malaysia (UUM). This study has found that lecturers can establish relationships and closeness with students through non-verbal communication cues such as kinesic, proxemic, chronemic, and paralinguistic. Lecturers who practice effective non-verbal communication enable a positive effect on students in terms of motivation to learn, focus in learning sessions, create interest in understanding topics, and feel at ease in learning. However, the lecturers' non-verbal communication has had a negative effect if the lecturer is unable to build a good relationship especially in terms of chronemic and facial expressions cues. It will cause students to be unmotivated and experience emotional stress. In conclusion, non-verbal communication is still vital in the process of establishing a social presence and building relationships even online. The practice of non-verbal communication during the individual social presence in virtual space needs to be explored in other contexts such as in organisations.

Case-Control Study to Evaluate Zinc Deficiency as a Risk Factor for Oxygen Requirement in Patients with COVID-19

Zinc is one of the important trace elements of blood. It helps in maturation of immune system in our body. In the past studies originate the relationship between viral disease and serum zinc deficiency. This was a multicenter case-control study to measure the serum zinc level of COVID-19 patients with different respiratory supports and to evaluate the Odds Ratio (OR) and Relative risk (RR) of zinc deficiency for oxygen requirement for COVID-19 patients. Study places were COVID-19 unit of three tertiary hospitals of Sylhet, a Northern district of Bangladesh. There were 30 controls and 90 cases in this study. The mean zinc level of cases (53-38mcg/dl) was significantly (p=0.000072) lower than the level of controls (73-23mcg/dl). The mean zinc level of the COVID-19 patients required oxygen (49-33mcg/dl) was significantly (p=0.0054) lower than the patients were not treated by oxygen therapy (64-51mcg/dl). The RR of getting affected by COVID-19 was 1-91 for the low zinc level people. Among the COVID-19 affected participants the lower zinc level people had a RR of 1-93 to receive oxygen supplementation. Lower zinc level people are more likely to be affected by COVID-19 in comparison to the normal zinc level people. Among the COVID-19 patients the lower zinc level people had nearly double (RR 1-93) risk of becoming hypoxic and eventually prone for oxygen support.

Henoch-Schönlein purpura: Another COVID-19 complication.

Whether affecting children or adults, SARS-CoV-2 infection (COVID-19) can have multi-organ involvement mediated by an inflammatory cascade. Immunoglobulin A (IgA) is one of the key components of the inflammatory cascade that can lead to endothelial injury and inflammation. IgA vasculitis or Henoch-Schönlein purpura (HSP) has been rarely reported in the context of COVID-19. In this report, we highlight a case of HSP occurring 2 days after diagnosis of COVID-19 in a 16-year-old boy, who presented with palpable purpura of the lower extremities and buttocks, diffuse abdominal pain, hemoptysis, and hematochezia. He was treated with oral prednisolone with rapid clinical improvement.

Evaluating the Respiratory Support Pattern and Relationship with Initial Oxygen Saturation of the COVID Isolation Unit Patients in Sylhet

COVID-19 is the devastating pandemic of the century predominantly fatal due to its respiratory failure nature. Severe and critical patients need oxygen supplementation in different forms. This cross-sectional study was conducted in four tertiary hospitals of Sylhet, Bangladesh from November 2020 to March 2021. All the patients admitted in the COVID-19 isolation units and fulfill the selection criterion were enrolled in this study. The primary objective of this study was to evaluate different types of respiratory supports and its relationship with initial oxygen saturation (SpO2). Total 481 patients were enrolled. There was a male predominance (65.00%) in the participants. Highest number of participants was from 61-70 years age group. Number of ventilated patients were significantly high (p<0.001) in the COVID-19 patient group. The initial SpO2 and hospital staying period of COVID-19 positive and negative group did not show any significant difference but these two parameters showed significant difference among died and survived group (p<0.001). Nearly one fourth patients (24.94%) of total patients were treated in ICU with high flow nasal cannula (HFNC), non-invasive ventilation (NIV) and mechanical ventilation. Among the ICU admitted patients nearly one-fourth (24.16%) patients were treated with mechanical ventilation. Mortality rate was 62.00% for ventilated patients, 70.60% for NIV patients and 15.80% for the HFNC patients.

Supply chain viability in the context of COVID-19 pandemic in small and medium-sized enterprises: implications for sustainable development goals

Purpose The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic has severely disrupted the operations of global supply chains (SCs) providing an opportunity for decision-makers to rethink and tune their existing strategies. To tackle the impacts caused by such a pandemic, this study aims to examine the contextual relations among the factors influencing supply chain viability (SCV) for achieving long-term Sustainable Development Goals (SDGs). Design/methodology/approach A decision-aid approach by integrating Pareto analysis, grey theory and total interpretive structural modeling (TISM) has been propounded. The proposed approach examines contextual relations among the factors for SCV for small and medium-sized enterprises (SMEs) in an emerging economy. This study contributes to theory, methodology and practice by exploring a new research problem in the context of the SCV and COVID-19 pandemic and by developing a new decision-aid approach. Findings The findings reveal that the creation of SC digital twin and transformation of SCs to supply networks would help the policymakers to deal with the "new normal." Also, SC crowdfunding and policy development for health protocols are critical driving factors influencing SCV. Originality/value This research work is perhaps one of few initial attempts to advance the theoretical and practical understanding of SCV and to achieve SDGs in industries following a pandemic risk.

Early Detection of Malpositioned Catheters and Lines on Chest X-Rays using Deep Learning

Hospital patients can have catheters and lines inserted during the course of their admission and serious complications can arise if they are positioned incorrectly. Early recognition of malpositioned tubes is the key to preventing risky complications (even death), even more so now that millions of COVID-19 patients are in the need of these tubes and lines. Earlier detection of malpositioned catheters and lines is even more important as COVID-19 cases continue to surge, these steps can be time consuming and are still prone to human error, especially in stressful situations when hospitals are at capacity This paper presents an analysis of the solution to the challenge "RANZCR CLiP-Catheter and Line Position Challenge"on Kaggle hosted by Royal Australian and NZ College of Radiologists which scores 0.972 (AUC). It is a Transfer Learning-based CNN heavily inspired by UNet and EfficientNet. This architecture stands out from the rest due to the compound scaling methods applied to achieve its smaller size and higher speed than the rest. © 2021 IEEE.