University of Surrey

About: University of Surrey is a education organization based out in Guildford, Surrey, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 17976 authors who have published 44951 publications receiving 1249993 citations. The organization is also known as: Battersea Polytechnic Institute & Battersea College of Technology.

Risk factors for SARS-CoV-2 among patients in the Oxford Royal College of General Practitioners Research and Surveillance Centre primary care network: a cross-sectional study.

Abstract: Summary Background There are few primary care studies of the COVID-19 pandemic. We aimed to identify demographic and clinical risk factors for testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre primary care network. Methods We analysed routinely collected, pseudonymised data for patients in the RCGP Research and Surveillance Centre primary care sentinel network who were tested for SARS-CoV-2 between Jan 28 and April 4, 2020. We used multivariable logistic regression models with multiple imputation to identify risk factors for positive SARS-CoV-2 tests within this surveillance network. Findings We identified 3802 SARS-CoV-2 test results, of which 587 were positive. In multivariable analysis, male sex was independently associated with testing positive for SARS-CoV-2 (296 [18·4%] of 1612 men vs 291 [13·3%] of 2190 women; adjusted odds ratio [OR] 1·55, 95% CI 1·27–1·89). Adults were at increased risk of testing positive for SARS-CoV-2 compared with children, and people aged 40–64 years were at greatest risk in the multivariable model (243 [18·5%] of 1316 adults aged 40–64 years vs 23 [4·6%] of 499 children; adjusted OR 5·36, 95% CI 3·28–8·76). Compared with white people, the adjusted odds of a positive test were greater in black people (388 [15·5%] of 2497 white people vs 36 [62·1%] of 58 black people; adjusted OR 4·75, 95% CI 2·65–8·51). People living in urban areas versus rural areas (476 [26·2%] of 1816 in urban areas vs 111 [5·6%] of 1986 in rural areas; adjusted OR 4·59, 95% CI 3·57–5·90) and in more deprived areas (197 [29·5%] of 668 in most deprived vs 143 [7·7%] of 1855 in least deprived; adjusted OR 2·03, 95% CI 1·51–2·71) were more likely to test positive. People with chronic kidney disease were more likely to test positive in the adjusted analysis (68 [32·9%] of 207 with chronic kidney disease vs 519 [14·4%] of 3595 without; adjusted OR 1·91, 95% CI 1·31–2·78), but there was no significant association with other chronic conditions in that analysis. We found increased odds of a positive test among people who are obese (142 [20·9%] of 680 people with obesity vs 171 [13·2%] of 1296 normal-weight people; adjusted OR 1·41, 95% CI 1·04–1·91). Notably, active smoking was linked with decreased odds of a positive test result (47 [11·4%] of 413 active smokers vs 201 [17·9%] of 1125 non-smokers; adjusted OR 0·49, 95% CI 0·34–0·71). Interpretation A positive SARS-CoV-2 test result in this primary care cohort was associated with similar risk factors as observed for severe outcomes of COVID-19 in hospital settings, except for smoking. We provide evidence of potential sociodemographic factors associated with a positive test, including deprivation, population density, ethnicity, and chronic kidney disease. Funding Wellcome Trust.

The Visual Object Tracking VOT2017 Challenge Results

Abstract: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.