ABSTRACT
Introduction: While managing COVID-19 patients, the healthcare professionals are at higher risk for contracting the infection and also could be a potential source of transmitting the disease in the community unknowingly. Therefore awareness [knowledge, attitude, and practice (KAP)] among healthcare professionals becomes of utmost importance. Methods: We conducted this observational cross sectional study to evaluate the knowledge, attitude and perceived practices toward COVID-19 among HCWs using a self-administered questionnaire at tertiary level healthcare facility in western Rajasthan. The questionnaire was shared with all the healthcare professionals of the pre identified tertiary care facilities through electronic mail (e-mail) and the responses received were recorded and analyzed. Results: A total of 59 responses were recorded. Out of the total participants, 61% were aware of national COVID-19 helpline numbers, 54.2% answered correctly about Hydroxychloroquine prophylaxis, 13.6% answered appropriately on COVID-19 testing. Almost 96.6% acknowledged to wear a medical mask however only 55.9% participants answered correctly regarding using a face mask. 52.5% responded that ash collection as a ritual may be allowed after funeral (cremation) of the body of a COVID-19 patient. More than 90% of participants acknowledged to clean their hands > 6-10 times in a day. 72.9% of participants admitted to open the MoHFW website to keep themselves updated on COVID-19 in India and 66.1% have 'Aarogya Setu' application in their mobile phone. However only 23.7% have ever used central helpline number or email-ID to get information on COVID-19. Conlcusion: We concluded that healthcare professionals were aware of the management strategies and treatment protocol however there is significant differences in the KAP of HCW sub groups. It also becomes important to study the KAP in various other populations (general populations, close contacts of COVID-19 etc.) for planning effective intervention strategies for them.
ABSTRACT
In December 2019, a disease known as COVID-19 outbroke in some part of China which killed a bunch of people in that area. Till Mid-March, the disease spread all over the world killing more people. Due to this, World Health Organization (WHO) had to declare this decease as a pandemic. Therefore, scientists from all over the world were working very hard, giving their best everyday in order to make an anti-dote of this disease but it was expected to take alot of time and it even took. Now, government allowed the citizens to continue their normal way of living but still they made some protocols which was to be followed such as sanitization of hands on a regular interval, maintaining two-yard distance from each other, wearing masks, etc. Considering those protocols, we have evolved a Face-masks Detection System with a view to be useful in figuring out whether or not a person is wearing a mask or not inside the public locations which include Temples, Airports, and so on. The face masks detection database contains a mask and further to the facial snap shots, we've used OpenCV to carry out actual-time face detection from live streaming thru webcam. We have used the database to create a COVID-19 face mask detector from a computer view the use of Python, OpenCV, and Tensor Flow and Cameras. We present an in-intensity reading software that could come across conditions where a face mask isn't always used well. Our software incorporates a two-section configuration of the Convolutional Neural Network (CNN) that could hit upon hidden and unidentified faces and may point-out with pre-hooked up CCTV cameras. This allows in monitoring safety violations, promote using face mask, and ensures a safe running environment. © 2021 IEEE.
ABSTRACT
Understanding the pathophysiology of the coronavirus disease 2019 (COVID-19) infection remains a significant challenge of our times. The gingival crevicular fluid being representative of systemic status and having a proven track record of detecting viruses and biomarkers forms a logical basis for evaluating the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The study aimed to assess gingival crevicular fluid (GCF) for evidence of SARS-CoV-2 in 33 patients who were deemed to be COVID-19 positive upon nasopharyngeal sampling. An attempt was also made to comparatively evaluate it with saliva in terms of its sensitivity, as a diagnostic fluid for SARS-CoV-2. GCF and saliva samples were collected from 33 COVID-19-confirmed patients. Total RNA was extracted using NucliSENS easyMAG (bioMérieux) and eluted in the elution buffer. Envelope gene (E gene) of SARS-CoV-2 and human RNase P gene as internal control were detected in GCF samples by using the TRUPCR SARS-CoV-2 RT qPCR kit V-2.0 (I) in an Applied Biosystems 7500 real-time machine. A significant majority of both asymptomatic and mildly symptomatic patients exhibited the presence of the novel coronavirus in their GCF samples. Considering the presence of SARS-CoV-2 RNA in the nasopharyngeal swab sampling as gold standard, the sensitivity of GCF and saliva, respectively, was 63.64% (confidence interval [CI], 45.1% to 79.60%) and 64.52% (CI, 45.37% to 80.77%). GCF was found to be comparable to saliva in terms of its sensitivity to detect SARS-CoV-2. Saliva samples tested positive in 3 of the 12 patients whose GCF tested negative, and likewise GCF tested positive for 2 of the 11 patients whose saliva tested negative on real-time reverse transcription polymerase chain reaction. The results establish GCF as a possible mode of transmission of SARS-CoV-2, which is the first such report in the literature, and also provide the first quantifiable evidence pointing toward a link between the COVID-19 infection and oral health.