ABSTRACT
Background: During the COVID-19 pandemic, the pattern of medical services changed to minimize transmission to health care workers (HCWs) or hospitalized patients. Despite the care of COVID-19 patients in a special ward, new cases are accidentally discovered. This study aimed at determining the antibody seroprevalence among asymptomatic HCWs and the associated risks. Methods: The study involved 190 participants, including physicians, nurses, technicians, and administrative staff. All were inquired for sociodemographic, specialty, previous isolation, and previous infection, and their blood was tested for SARS-CoV2 antibody. Results: Of 190 HCWs;72,1% were females, the mean age was 32.6±7.9 years, 10.5% were smokers, and 15.8% reported co-morbid illness. SARS CoV2 antibodies were found in 68 (35.8%);being IgG, IgM and both IgM and IgG in 47 (69.1%), 10 (14.7%) and 11 (16.2%) participants respectively. The prevalence was higher (47.6%) among HCWs of the COVID unit, [OR=1.7 (95% CI: 0.69-4.3)] and HCWs with previous COVID-19, OR:1.61 (95% CI:0.88-2.94). The prevalence was significantly lower among smokers (p=0.049), OR:0.29 (95% CI:0.08-1.01), and significantly higher in HCWs who recalled cough (p=0.036) OR: 1.97 (95% CI: 1.05-3.69). The likelihood of antibody seropositivity increased in technicians [OR:2.02 (95% CI: 0.92-4.44)], followed by physicians [OR:1.7 (95% CI: 0.7-4.33)] while the odds ratio was low among nurses [OR:0.58 (95% CI: 0.32-1.07). Conclusion: A considerable proportion of antibody positive HCWs had evidence of past SARS CoV2. Provision of adequate personal protective equipment and periodic screening of HCWs are urgently needed to lessen the transmission within the health care settings. © 2020 The author (s).
ABSTRACT
From the outbreak of the COVID-19 pandemic in March 2020 until now, the Malaysian government has implemented various steps in curbing the spread of the virus in order to reduce the infection risk in all regions as well as among rural communities. The implementation of the Movement Control Order (MCO) by the government;designed to control intra- and inter-state and/or district movements and travels has been accepted and accustomed as the new norm in curbing the transmission of infection. This is especially among the vulnerable community groups i.e., elderly people and people with chronic diseases. Although MCO is crucial to curb the virus, this restriction of movement has also inhibited the activities of many important economic sectors especially on transportation of goods and other services. With a consideration that there is a dearth of studies, specifically about the impact of COVID-19 on the socioeconomic condition of the rural communities in specific context;a comprehensive study has been conducted involving 39 selected rural settlements for the whole Peninsular Malaysia. A total of 504 respondents/head of households had participated in the questionnaire survey. Research findings have shown the majority of respondents experienced socioeconomic impacts from MCO and the COVID-19 pandemic, particularly between 50% to 75% income reductions. This is contributed by two main factors: the MCO which hindered them to go out for work and carry out business activities as well as declining sales of produce or livestock. The research findings also reveal that 15% to 25% of the rural communities experienced food supply disruption. This is categorised as low to moderate level. It is important to note that since majority of the respondents are having low income, they are highly vulnerable to this volatile situation. Outcomes of this research could offer meaningful information regarding the current socioeconomic condition of rural communities in relation to the MCO and prolongation of the COVID-19 pandemic. As the way forward, there should be a more inclusive Build Back Better (BBB) strategies for creating a future more resilient rural community to pandemic.
ABSTRACT
The prolongation of the Pandemic COVID-19 has undermined the healthcare system and negatively impacted the economy and social development on a global and regional scale. At the human settlement level, responding to the pandemic situation has altered the broad spectrum of our daily routine down to the family and individual levels. Prior to the lockdown popularly known as the Movement Control Order (MCO), which the government introduced, the public was urged to limit outdoor movements and stay at home hence, encouraging the adoption of Work From Home (WFH) for employees and Home-based Teaching and Learning (PdPR) for the academic community and school students. Other than technological readiness for online working and teaching, the new normal also prompted new challenges for households in utilizing indoor spaces at home, especially for quarantine as well as for WFH and PdPR activities. In this light, a series of household surveys using questionnaires to determine the preference and usage of indoor space among households have been conducted in 39 locations/settlements across peninsular Malaysia. A total of 504 respondents participated and fieldwork and interview processes. Findings of the study indicated a majority of respondents have to designate indoor spaces/rooms for home quarantine (58%), and the three indoor spaces, in particular, have been monitored regularly by respondents during the pandemic, namely living areas (39%), kitchen (25%) and bedroom (21%). During MCO, most of them spent 1 to 4 hours per day for PdPR (43%), and 47% of respondents have a designated learning space at home for PdPR. In summary, pandemic COVID-19 has raised awareness among households regarding the selection and usage of indoor space to conduct various activities while they have to stay at home.
ABSTRACT
The transition from face-to-face classes to fully online learning (OL) during the spring semester of 2020 occurred almost globally because of the imposed COVID-19 lockdown. The present study investigated the perception and experiences of undergraduate students and faculty members of the Civil Engineering program at the United Arab Emirates University concerning switching to OL during COVID-19. Quantitative questionnaires were distributed to faculty members and students following the end of the spring semester of 2020. Students and faculty members identified student engagement and online exams as major areas that require improvement. Online exams were challenging for students and difficult to prepare, control, and administer for faculty. Providing technical support is critical for the successful streaming of online courses. Initially, half of the surveyed students began the transition with a positive attitude toward OL, and this percentage increased during the transition. The capacity to continue learning during the COVID-19 crisis and the availability of recorded materials were perceived by the students as the main advantages of OL while challenging online examinations and the lack of social interaction were the main disadvantages. © 2022, The Online Learning Consortium. All rights reserved.
ABSTRACT
COVID-19, one of the most dangerous pandemics, is currently affecting humanity. COVID-19 is spreading rapidly due to its high reliability transmissibility. Patients who test positive more often have mild to severe symptoms such as a cough, fever, raw throat, and muscle aches. Diseased people experience severe symptoms in more severe cases. such as shortness of breath, which can lead to respiratory failure and death. Machine learning techniques for detection and classification are commonly used in current medical diagnoses. However, for treatment using neural networks based on improved Particle Swarm Optimization (PSO), known as PSONN, the accuracy and performance of current models must be improved. This hybridization implements Particle Swarm Optimization and a neural network to improve results while slowing convergence and improving efficiency. The purpose of this study is to contribute to resolving this issue by presenting the implementation and assessment of Machine Learning models. Using Neural Networks and Particle Swarm Optimization to help in the detection of COVID-19 in its early stages. To begin, we preprocessed data from a Brazilian dataset consisted primarily of early-stage symptoms. Following that, we implemented Neural Network and Particle Swarm Optimization algorithms. We used precision, accuracy score, recall, and F-Measure tests to evaluate the Neural Network with Particle Swarm Optimization algorithms. Based on the comparison, this paper grouped the top seven ML models such as Neural Networks, Logistic Regression, Nave Bayes Classifier, Multilayer Perceptron, Support Vector Machine, BF Tree, Bayesian Networks algorithms and measured feature importance, and other, to justify the differences between classification models. Particle Swarm Optimization with Neura Network is being deployed to improve the efficiency of the detection method by more accurately predicting COVID-19 detection. Preprocessed datasets with important features are then fed into the testing and training phases as inputs. Particle Swarm Optimization was used for the training phase of a neural net to identify the best weights and biases. On training data, the highest rate of accuracy gained is 0.98.738 and on testing data, it is 98.689.
ABSTRACT
By the end of 2021, it is expected that the coronavirus (COVID-19) will shift from pandemic to endemic phase as the number of vaccinated people is increasing over time. It gives us hope as the endemic phase will allow us to live together with the virus. During the Covid-19 situation, people have become more creative and innovative for familiarising themselves with the New Normal. The next question is how is the existing housing for the low-income group ready to be suited with this situation? Therefore, this study will examine the concept of space design in housing units for the lower income group. The study adopted a case study approach based on housing layout from Kuala Lumpur, Bandung and Buckinghamshire. These housing layouts were analysed using the Space Syntax method for describing the meaning of space layout from a low-income perspective. This study found two consideration points, (1) the willingness of space to accommodate small business activities and to avoid the spread of epidemics in the domestic space, and (2) the willingness of the government to educate the public to cultivate small home entrepreneurship with the existing low-income routine and limited domestic spaces.
ABSTRACT
Transitioning to online learning (OL) is more challenging for engineering education because hands-on course delivery requirements are compromised. Like most universities around the globe, the institution to which the authors are affiliated shifted to emergency remote teaching in spring 2020 because of the coronavirus disease 2019 (COVID-19) pandemic. The researchers queried undergraduate students enrolled in the Civil and Environmental Engineering Department about their perceptions of OL during the pandemic and asked whether the students would attend online classes in the future. The students did not evince a clear inclination for either face-to-face (F2F) classes or OL (52%-48%) regardless of the proximity between their residence and the campus. The participating students were also almost equally divided irrespective of their gender when asked if OL was better than F2F learning. Moreover, the students registered a 50% positive response when asked whether they would enroll in optional online classes in the future. Most students who did not desire OL nevertheless enrolled in online classes in the summer session of 2020. However, student preference for OL tended to decline with the increase in the number of registered courses. Furthermore, overachieving and underachieving students favored F2F classes, and male students were more inclined to OL than female students. Other factors that may have influenced student predilections for OL during the COVID-19 lockdown include access to emotional support, information technology support, and reliable internet connection;the availability of an undisturbed space at home;and the nature and methodology of online examinations. © 2021 IEEE.
ABSTRACT
Ever since the uncovering of the severe discrepancy of COVID-19 manifestations, irrespective of viral load, scientists have raced to locate and manage factors contributing to the genesis of a critical state. Recent evidence delineates the role of oral dysbiosis in the development of low-grade inflammation, characterized by the increase of inflammatory cytokines common to those fundamental to the development of severe COVID. Furthermore, high periodontopathic bacteria were recorded in severe acute respiratory syndrome in COVID patients, as well as its common provoking comorbidities such as diabetes and hypertension. This can be explained by the immigration and elimination of oral bacteria into the airways, which, in the context of an injured lung, allows for their preferential overgrowth familiar to that, causing the progression to advanced lung diseases. This is why we indicate the promising usage of oral microbiome transplantation as a treatment of oral microbial dysbiosis, not only associated with the worst outcomes of COVID-19 but also in other disorders of low-grade inflammation.
ABSTRACT
Due to COVID-19 pandemic, society need to embrace and adopt new norm that includes practising social distance to break the transmission. The smart social distance application or tracker can help people to be constantly monitored and reminded to adhere to this practice. Direct impact that can be seen from this application will be lower or minimum number of COVID-19 cases due to high level of social distance compliance. This paper will present an innovative solution called MySD which stand for 'My Safe Distance' that help users or public to observe social distance advice closely. It leverages smart phone hardware features that typically has Bluetooth transceiver as well GPS to determine safe distance and required level compliance. © 2020 IEEE.