Project description:Infrared temperature measurement is a common form of mass screening for febrile illnesses such as COVID-19 infection. Efficacy of infrared monitoring is debated, and external factors can affect accuracy. We determine that outside temperature, wind, and humidity can affect infrared temperature measurements and partially account for inaccurate results.
Project description:Background: The COVID-19 pandemic forced health-related organizations to rapidly launch country-wide procedures that were easy to use and inexpensive. Body temperature measurement with non-contact infrared thermometers (NCITs) is among the most common procedures, both in hospital settings and in many other entities. However, practical hospital experiences have raised great doubts about the procedure's validity. Aim: This study aimed to evaluate the validity of the body temperature measured using NCITs among oncological and transplant patients who took the polymerase chain reaction test for SARS-Cov-2 PCR+ and PCR- in a Romanian Hospital. Methods: Body temperature was measured for 5,231 inpatients using NCITs. The cutoff point for fever was equal to or above 37.3°C. Patients then completed a questionnaire about their symptoms, contact, and travel history. Findings: Fever was detected in five of 53 persons with PCR+, resulting in a sensitivity of 9.43% (95% CI, 3.13-20.66%). No fever was verified in 5,131 of 5,171 persons with PCR-, resulting in a specificity of 99.15% (95% CI, 98.86-99.38%). A defensive vision of NCIT procedure (maximum standard error only in favor) had a sensitivity of 15.09% (95% CI, 6.75-27.59%). Conclusions: The use of NCITs in a triage provides little value for detection of COVID-19. Moreover, it provides a false sense of protection against the disease while possibly discriminating individuals that could present fever due to other reasons, such as oncologic treatments, where fever is a common therapeutical consequence. The consumption of qualified human resources should be considered, especially in the context of the shortage of healthcare professionals worldwide.
Project description:An optimal clinical specimen for accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by minimizing the usage of consumables and reduce hazard exposure to healthcare workers is an urgent priority. The diagnostic performance of SARS-CoV-2 detection between healthcare worker-collected nasopharyngeal and oropharyngeal (NP + OP) swabs and patient performed self-collected random saliva was assessed. Paired NP + OP swabs and random saliva were collected and processed within 48 h of specimen collection from two cohort studies which recruited 562 asymptomatic adult candidates. Real-time reverse-transcription polymerase chain reaction targeting Open reading frame 1a (ORF1a) and nucleocapsid (N) genes was performed and the results were compared. Overall, 65 of 562 (28.1%) candidates tested positive for COVID-19 based on random saliva, NP + OP swabs, or both testing techniques. The detection rate of SARS-CoV-2 was higher in random saliva compared to NP + OP testing (92.3%; 60/65 vs. 73.8%; 48/65; p < .05). The estimated sensitivity and specificity of random saliva were higher than NP + OP swabs (95.0; 99.9 vs. 72.2; 99.4). The Ct values of ORF1a and N genes were significantly lower in random saliva compared to NP + OP swabs specimens. Our findings demonstrate that random saliva is an alternative diagnostic specimen for the detection of SARS-CoV-2. Self-collected random oropharyngeal saliva is a valuable specimen that provides accurate SARS-CoV-2 surveillance testing of a community.
Project description:To confine the spread of an infectious disease, setting a sensible quarantine time is crucial. To this end, it is imperative to well understand the distribution of incubation times of the disease. Regarding the ongoing COVID-19 pandemic, 14-days is commonly taken as a quarantine time to curb the virus spread in balancing the impacts of COVID-19 on diverse aspects of the society, including public health, economy, and humanity perspectives, etc. However, setting a sensible quarantine time is not trivial and it depends on various underlying factors. In this article, we take an angle of examining the distribution of the COVID-19 incubation time using likelihood-based methods. Our study is carried out on a dataset of 178 COVID-19 cases dated from January 20, 2020 to February 29, 2020, with the information of exposure periods and dates of symptom onset collected. To gain a good understanding of possible scenarios, we employ different models to describe incubation times of COVID-19. Our findings suggest that statistically, the 14-day quarantine time may not be long enough to control the probability of an early release of infected individuals to be small. While the size of the study data is not large enough to offer us a definitely acceptable quarantine time, and further in practice, the decision-makers may take account of other factors related to social and economic concerns to set up a practically acceptable quarantine time, our study demonstrates useful methods to determine a reasonable quarantine time from a statistical standpoint. Further, it reveals some associated complexity for fully understanding the COVID-19 incubation time distribution.Supplementary informationThe online version contains supplementary material available at 10.1007/s12561-021-09320-8.
Project description:Multi-omics single-cell profiling of surface proteins, gene expression and lymphocyte immune receptors from hospitalised COVID-19 patient peripheral blood immune cells and healthy controls donors. Identification of the coordinated immune cell compositional and state changes in response to SARS-CoV-2 infection or LPS challenge, compared to healthy control immune cells.
Project description:Objective: Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19) across the globe has pushed the health care system in many countries to the verge of collapse. Therefore, it is imperative to correctly identify COVID-19 positive patients and isolate them as soon as possible to contain the spread of the disease and reduce the ongoing burden on the healthcare system. The primary COVID-19 screening test, RT-PCR although accurate and reliable, has a long turn-around time. In the recent past, several researchers have demonstrated the use of Deep Learning (DL) methods on chest radiography (such as X-ray and CT) for COVID-19 detection. However, existing CNN based DL methods fail to capture the global context due to their inherent image-specific inductive bias. Methods: Motivated by this, in this work, we propose the use of vision transformers (instead of convolutional networks) for COVID-19 screening using the X-ray and CT images. We employ a multi-stage transfer learning technique to address the issue of data scarcity. Furthermore, we show that the features learned by our transformer networks are explainable. Results: We demonstrate that our method not only quantitatively outperforms the recent benchmarks but also focuses on meaningful regions in the images for detection (as confirmed by Radiologists), aiding not only in accurate diagnosis of COVID-19 but also in localization of the infected area. The code for our implementation can be found here - https://github.com/arnabkmondal/xViTCOS. Conclusion: The proposed method will help in timely identification of COVID-19 and efficient utilization of limited resources.
Project description:The COVID-19 crisis and the development of the first approved mRNA vaccine have highlighted the power of RNA-based therapeutic strategies for the development of new medicines. Aside from RNA-vaccines, antisense oligonucleotides (ASOs) represent a new and very promising class of RNA-targeted therapy. Few drugs have already received approval from the Food and Drug Administration. Here, we underscored why and how ASOs hold the potential to change the therapeutic landscape to beat SARS-CoV-2 viral infections. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions.
Project description:Rapid changes in the viral genome allow viruses to evade threats posed by the host immune response or antiviral drugs, and can lead to viral persistence in the host cells. RNA-dependent RNA polymerase (RdRp) is an essential enzyme in RNA viruses, which is involved in RNA synthesis through the formation of phosphodiester bonds. Therefore, in RNA viral infections such as SARS-CoV-2, RdRp could be a crucial therapeutic target. The present review discusses the promising application of RdRp inhibitors, previously approved or currently being tested in human clinical trials, in the treatment of RNA virus infections. Nucleoside inhibitors (NIs) bind to the active site of RdRp, while nonnucleoside inhibitors (NNIs) bind to allosteric sites. Given the absence of highly effective drugs for the treatment of COVID-19, the discovery of an efficient treatment for this pandemic is an urgent concern for researchers around the world. We review the evidence for molnupiravir (MK-4482, EIDD-2801), an antiviral drug originally designed for Alphavirus infections, as a potential preventive and therapeutic agent for the management of COVID-19. At the beginning of this pandemic, molnupiravir was in preclinical development for seasonal influenza. When COVID-19 spread dramatically, the timeline for development was accelerated to focus on the treatment of this pandemic. Real time consultation with regulators took place to expedite this program. We summarize the therapeutic potential of RdRp inhibitors, and highlight molnupiravir as a new small molecule drug for COVID-19 treatment.
Project description:With over 16 million cases reported from across the globe, the SARS-CoV-2, a mere 125 microns in diameter, has left an indelible impact on our world. With the paucity of new drugs to combat this disease, the medical community is in a race to identify repurposed drugs that may be effective against this novel coronavirus. One of the drugs which has recently garnered much attention, especially in India, is an anti-viral drug originally designed for influenza, called favipiravir. In this article, we have tried to provide a comprehensive, evidence-based review of this drug in the context of the present pandemic to elucidate its role in the management of COVID-19.