CovidViT: a novel neural network with self-attention mechanism to detect Covid-19 through X-ray images.

Since the emergence of the novel coronavirus in December 2019, it has rapidly swept across the globe, with a huge impact on daily life, public health and the economy around the world. There is an urgent necessary for a rapid and economical detection method for the Covid-19. In this study, we used the transformers-based deep learning method to analyze the chest X-rays of normal, Covid-19 and viral pneumonia patients. Covid-Vision-Transformers (CovidViT) is proposed to detect Covid-19 cases through X-ray images. CovidViT is based on transformers block with the self-attention mechanism. In order to demonstrate its superiority, this research is also compared with other popular deep learning models, and the experimental result shows CovidViT outperforms other deep learning models and achieves 98.0% accuracy on test set, which means that the proposed model is excellent in Covid-19 detection. Besides, an online system for quick Covid-19 diagnosis is built on http://yanghang.site/covid19.

CovidViT: a novel neural network with self-attention mechanism to detect Covid-19 through X-ray images

Since the emergence of the novel coronavirus in December 2019, it has rapidly swept across the globe, with a huge impact on daily life, public health and the economy around the world. There is an urgent necessary for a rapid and economical detection method for the Covid-19. In this study, we used the transformers-based deep learning method to analyze the chest X-rays of normal, Covid-19 and viral pneumonia patients. Covid-Vision-Transformers (CovidViT) is proposed to detect Covid-19 cases through X-ray images. CovidViT is based on transformers block with the self-attention mechanism. In order to demonstrate its superiority, this research is also compared with other popular deep learning models, and the experimental result shows CovidViT outperforms other deep learning models and achieves 98.0% accuracy on test set, which means that the proposed model is excellent in Covid-19 detection. Besides, an online system for quick Covid-19 diagnosis is built on http://yanghang.site/covid19.

Rapid and Visual RPA-Cas12a Fluorescence Assay for Accurate Detection of Dermatophytes in Cats and Dogs.

Dermatophytosis, an infectious disease caused by several fungi, can affect the hair, nails, and/or superficial layers of the skin and is of global significance. The most common dermatophytes in cats and dogs are Microsporum canis and Trichophyton mentagrophytes. Wood's lamp examination, microscopic identification, and fungal culture are the conventional clinical diagnostic methods, while PCR (Polymerase Chain Reaction) and qPCR (Quantitative PCR) are playing an increasingly important role in the identification of dermatophytes. However, none of these methods could be applied to point-of-care testing (POCT). The recent development of the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) based diagnostic platform promises a rapid, accurate, and portable diagnostic tool. In this paper, we present a Cas12a-fluorescence assay to detect and differentiate the main dermatophytes in clinical samples with high specificity and sensitivity. The Cas12a-based assay was performed with a combination of recombinase polymerase amplification (RPA). The results could be directly visualized by naked eyes under blue light, and all tested samples were consistent with fungal culture and sequencing results. Compared with traditional methods, the RPA-Cas12a-fluorescence assay requires less time (about 30 min) and less complicated equipment, and the visual changes can be clearly observed with naked eyes, which is suitable for on-site clinical diagnosis.

The Conditional Configuration Path for Private Enterprises Participating in PPP: A Fuzzy-Set Qualitative Comparative Analysis

Public–private partnership (PPP) projects have been widely applied in infrastructure construction. Leveraging private capital is the key to promoting the high-quality development of PPP projects. This study examines the combined effect of seven factors determining private enterprises that participate in PPP and collects materials from 102 PPP sewage treatment projects to examine the causal configuration path of private enterprises participating in PPP (PEP3P) from an overall perspective by using necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The findings support the fact that any single antecedent condition is not a necessary condition for PEP3P and is instead the combined effect of different factors that commonly form the diversified causal configuration paths of PEP3P. There is an obvious asymmetry between the configuration paths of the high participation and low participation of private enterprises. The enterprise technology level (ETL) and doing business (DB) are important internal driving forces and give external traction for PEP3P, while the enterprise credit level (ECL) and project investment scale (PIS) are important factors that restrict private enterprises from participating in PPP. This research fills a theoretical gap for PEP3P and can be applied to developing strategies for attracting private enterprises to participate in PPP.

Cross-sectional observational study of epidemiology of COVID-19 and clinical outcomes of hospitalised patients in North West London during March and April 2020.

OBJECTIVE: The aim of this paper is to describe evolution, epidemiology and clinical outcomes of COVID-19 in subjects tested at or admitted to hospitals in North West London. DESIGN: Observational cohort study. SETTING: London North West Healthcare NHS Trust (LNWH). PARTICIPANTS: Patients tested and/or admitted for COVID-19 at LNWH during March and April 2020 MAIN OUTCOME MEASURES: Descriptive and analytical epidemiology of demographic and clinical outcomes (intensive care unit (ICU) admission, mechanical ventilation and mortality) of those who tested positive for COVID-19. RESULTS: The outbreak began in the first week of March 2020 and reached a peak by the end of March and first week of April. In the study period, 6183 tests were performed in on 4981 people. Of the 2086 laboratory confirmed COVID-19 cases, 1901 were admitted to hospital. Older age group, men and those of black or Asian minority ethnic (BAME) group were predominantly affected (p<0.05). These groups also had more severe infection resulting in ICU admission and need for mechanical ventilation (p<0.05). However, in a multivariate analysis, only increasing age was independently associated with increased risk of death (p<0.05). Mortality rate was 26.9% in hospitalised patients. CONCLUSION: The findings confirm that men, BAME and older population were most commonly and severely affected groups. Only older age was independently associated with mortality.

Cross sectional investigation of a COVID-19 outbreak at a London Army barracks: Neutralising antibodies and virus isolation.

BACKGROUND: Military personnel in enclosed societies are at increased risk of respiratory infections. We investigated an outbreak of Coronavirus Disease 2019 in a London Army barracks early in the pandemic. METHODS: Army personnel, their families and civilians had nasal and throat swabs for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by reverse transcriptase -polymerase chain reaction (RT-PCR), virus isolation and whole genome sequencing, along with blood samples for SARS-CoV-2 antibodies. All tests were repeated 36 days later. FINDINGS: During the first visit, 304 (254 Army personnel, 10 family members, 36 civilians, 4 not stated) participated and 24/304 (8%) were SARS-CoV-2 RT-PCR positive. Infectious virus was isolated from 7/24 (29%). Of the 285 who provided a blood sample, 7% (19/285) were antibody positive and 63% (12/19) had neutralising antibodies. Twenty-two (22/34, 64%) individuals with laboratory-confirmed infection were asymptomatic. Nine SARS-CoV-2 RT-PCR positive participants were also antibody positive but those who had neutralising antibodies did not have infectious virus. At the second visit, no new infections were detected, and 13% (25/193) were seropositive, including 52% (13/25) with neutralising antibodies. Risk factors for SARS-CoV-2 antibody positivity included contact with a confirmed case (RR 25.2; 95% CI 14-45), being female (RR 2.5; 95% CI 1.0-6.0) and two-person shared bathroom (RR 2.6; 95% CI 1.1-6.4). INTERPRETATION: We identified high rates of asymptomatic SARS-CoV-2 infection. Public Health control measures can mitigate spread but virus re-introduction from asymptomatic individuals remains a risk. Most seropositive individuals had neutralising antibodies and infectious virus was not recovered from anyone with neutralising antibodies. FUNDING: PHE.

An observational cohort study of bacterial co-infection and implications for empirical antibiotic therapy in patients presenting with COVID-19 to hospitals in North West London.

OBJECTIVES: To describe the prevalence and nature of bacterial co-infections in COVID-19 patients within 48 hours of hospital admission and assess the appropriateness of empirical antibiotic treatment they received. METHODS: In this retrospective observational cohort study, we included all adult non-pregnant patients who were admitted to two acute hospitals in North West London in March and April 2020 and confirmed to have COVID-19 infection within 2 days of admission. Results of microbiological specimens taken within 48 hours of admission were reviewed and their clinical significance was assessed. Empirical antibiotic treatment of representative patients was reviewed. Patient age, gender, co-morbidities, inflammatory markers at admission, admission to ICU and 30 day all-cause in-hospital mortality were collected and compared between patients with and without bacterial co-infections. RESULTS: Of the 1396 COVID-19 patients included, 37 patients (2.7%) had clinically important bacterial co-infection within 48 hours of admission. The majority of patients (36/37 in those with co-infection and 98/100 in selected patients without co-infection) received empirical antibiotic treatment. There was no significant difference in age, gender, pre-existing illnesses, ICU admission or 30 day all-cause mortality in those with and without bacterial co-infection. However, white cell count, neutrophil count and CRP on admission were significantly higher in patients with bacterial co-infections. CONCLUSIONS: We found that bacterial co-infection was infrequent in hospitalized COVID-19 patients within 48 hours of admission. These results suggest that empirical antimicrobial treatment may not be necessary in all patients presenting with COVID-19 infection, although the decision could be guided by high inflammatory markers.