ABSTRACT
Introduction: Public perception regarding clinical diagnostic sample types as well as personal experiences can influence willingness to test. As such, public preferences for specific sample type(s) should be used to inform diagnostic and surveillance testing programs to improve public health response efforts. To understand where preferences lie, we conducted an international survey regarding sample types used for SARS-CoV-2 tests. Methods A Qualtrics survey regarding SARS-CoV-2 testing preferences was distributed via social media and email. The survey collected preferences regarding test sample types and key demographic data. Python was used to analyze survey responses. Results From March 30th to June 15th, 2022, 2,094 responses were collected from 125 countries. Participants were 55% female and predominantly aged 25-34 years (27%). Education and employment were skewed: 51% had graduate degrees, 26% had bachelor's degrees, 27% were scientists/researchers, and 29% were healthcare workers. By rank sum analysis, the most preferred sample type globally was the oral swab, followed by saliva, with parents/guardians preferring saliva-based testing for children. Respondents indicated a higher degree of trust in PCR testing (84%) vs. rapid antigen testing (36%). Preferences for self- or healthcare worker-collected sampling varied across regions. Conclusions This international survey identified a preference for oral sample types when testing for SARS-CoV-2. Notably, respondents indicated that if they could be assured that all sample types performed equally, then saliva was preferred. Overall, survey responses reflected the region-specific testing experiences during the COVID-19. Public preferences should be considered when designing future response efforts to increase utilization, with oral sample types providing a practical option for large-scale, accessible diagnostic testing.
Subject(s)
COVID-19ABSTRACT
Early warning of the novel coronavirus pneumonia (COVID-19) during the evolving pandemic waves is crucial for the timely treatment of patients and optimization of medical resource allocation. However, prior AI-based models often lack the reliability and performance validation under data distribution drifts, and are therefore problematic to be reliably utilized in real-world clinical practice. To address this challenge, we developed a tri-light warning system based on conformal prediction for rapidly stratification of COVID-19 inpatients. This system can automatically extract radiomic features from CT images and integrate clinical record information to output a prediction probability, as well as a credibility of each prediction. This system classifies patients in the general ward into red label (high risk) indicating a possible admission to ICU care, yellow label (uncertain risk) indicating closer monitoring, and green label (low risk) indicating a stable condition. The subsequent health policies can be further designed based on this system according to the specific needs of different hospitals. Extensive experiment from a multi-center cohort (n= 8,721) shows that our method is applicable to both the original strain and the variant strains of COVID-19. Given the rapid mutation rate of COVID-19, the proposed system demonstrates its potential to identify epidemiological risks early to improve patient stratification performance under data shift.
Subject(s)
COVID-19 , Coronavirus InfectionsABSTRACT
Objectives To assess the association of habitual glucosamine use with coronavirus 2 (SARS-CoV-2) infection, hospital admission, or mortality with Corona Virus Disease-19 (COVID-19) in a large population based cohort. Design Population based, prospective cohort study. Setting UK Biobank. Participants Participants with complete information on habitual glucosamine use and SARS-CoV-2 infection or COVID-19-related outcomes were included. These participants were registered from 2006 to 2010, followed up until 2022 and participated in SARS-CoV-2 tests between 2020 and 2022. Main outcome measures SARS-CoV-2 infection, COVID-19 hospital admission, and COVID-19 mortality. Results At baseline, 20,118 (15.9%) of the 126,518 participants reported as habitual glucosamine users. During the median follow-up 12.16 years, there were 53,682 cases of SARS-CoV-2 infection, 2,120 cases of COVID-19 hospital admission and 548 cases of COVID-19 mortality. The multivariate adjusted hazard ratios of habitual glucosamine users to non-users were 1.02 (95% confidence interval [CI] 0.99 to 1.05) for SARS-CoV-2 infection, 0.73 (95% CI 0.63 to 0.85) for COVID-19 hospital admission, and 0.74 (95% CI 0.56 to 0.98) for COVID-19 mortality. The Cox proportional hazard analysis after propensity-score matching yielded consistent results. Conclusions Habitual glucosamine use seems to be associated with a lower risk of hospital admission and mortality with COVID-19, but not the risk of SARS-CoV-2 infection.