ABSTRACT
The unprecedented outbreak of the 2019 novel coronavirus, termed as COVID-19 has brought new techniques/technologies which are emerging a lot in today’s research industry including 5G, Internet-of-Things (IoT), Edge Computing, Blockchain, etc., to more light. This is attracting more researchers across the Globe to enhance the existing models shared through different platforms. In addition to that, many have come across having humanoids/robots deployed into streets for serving and public announcements, delivering medications or emergency support onto doorsteps. These technologies are also helping many organizations across planet to explore COVID-19 related useful solutions which can help to manipulate and process data in real time. In this paper, authors are concentrating on integrating the algorithmic approach of Edge Computing & Drone Technology which can enlighten the challenges of parameters namely latency, connectivity, data processing, onsite computation. etc. In addition to that, proposing an architecture for the design of Edge-based integrated Drone use case for the containment zones detection with offline data processing & computation and deployment of algorithm for thermal sensing. This approach of making UAV bandwidth-independent architecture will create new opportunities for exploring COVID Pandemic smoothness for every aspect of social duties. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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.