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Nations are imposing unprecedented measures at a large scale to contain the spread of the COVID-19 pandemic. While recent studies show that non-pharmaceutical intervention measures such as lockdowns may have mitigated the spread of COVID-19, those measures also lead to substantial economic and social costs, and might limit exposure to ultraviolet-B radiation (UVB). Emerging observational evidence indicates the protective role of UVB and vitamin D in reducing the severity and mortality of COVID-19 deaths. This observational study empirically outlines the protective roles of lockdown and UVB exposure as measured by the ultraviolet index (UVI). Specifically, we examine whether the severity of lockdown is associated with a reduction in the protective role of UVB exposure. We use a log-linear fixed-effects model on a panel dataset of secondary data of 155 countries from 22 January 2020 until 7 October 2020 (n = 29,327). We use the cumulative number of COVID-19 deaths as the dependent variable and isolate the mitigating influence of lockdown severity on the association between UVI and growth rates of COVID-19 deaths from time-constant country-specific and time-varying country-specific potentially confounding factors. After controlling for time-constant and time-varying factors, we find that a unit increase in UVI and lockdown severity are independently associated with − 0.85 percentage points (p.p) and − 4.7 p.p decline in COVID-19 deaths growth rate, indicating their respective protective roles. The change of UVI over time is typically large (e.g., on average, UVI in New York City increases up to 6 units between January until June), indicating that the protective role of UVI might be substantial. However, the widely utilized and least severe lockdown (governmental recommendation to not leave the house) is associated with the mitigation of the protective role of UVI by 81% (0.76 p.p), which indicates a downside risk associated with its widespread use. We find that lockdown severity and UVI are independently associated with a slowdown in the daily growth rates of cumulative COVID-19 deaths. However, we find evidence that an increase in lockdown severity is associated with significant mitigation in the protective role of UVI in reducing COVID-19 deaths. Our results suggest that lockdowns in conjunction with adequate exposure to UVB radiation might have even reduced the number of COVID-19 deaths more strongly than lockdowns alone. For example, we estimate that there would be 11% fewer deaths on average with sufficient UVB exposure during the period people were recommended not to leave their house. Therefore, our study outlines the importance of considering UVB exposure, especially while implementing lockdowns, and could inspire further clinical studies that may support policy decision-making in countries imposing such measures.
Coronavirus disease 2019 (COVID-19) is a global pandemic posing significant health risks. The diagnostic test sensitivity of COVID-19 is limited due to irregularities in specimen handling. We propose a deep learning framework that identifies COVID-19 from medical images as an auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography images to train the convolutional neural network, which achieves a performance similar to that of experts and provides high scores for multiple statistical indices (F1 scores > 96.72% (0.9307, 0.9890) and specificity >99.33% (0.9792, 1.0000)). Heatmaps are used to visualize the salient features extracted by the neural network. The neural network-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, resulting in high accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.
The genus Ebolavirus comprises some of the deadliest viruses for primates and humans and associated disease outbreaks are increasing in Africa. Different evidence suggests that bats are putative reservoir hosts and play a major role in the transmission cycle of these filoviruses. Thus, detailed knowledge about their distribution might improve risk estimations of where future disease outbreaks might occur. A MaxEnt niche modelling approach based on climatic variables and land cover was used to investigate the potential distribution of 9 bat species associated to the Zaire ebolavirus. This viral species has led to major Ebola outbreaks in Africa and is known for causing high mortalities. Modelling results suggest suitable areas mainly in the areas near the coasts of West Africa with extensions into Central Africa, where almost all of the 9 species studied find suitable habitat conditions. Previous spillover events and outbreak sites of the virus are covered by the modelled distribution of 3 bat species that have been tested positive for the virus not only using serology tests but also PCR methods. Modelling the habitat suitability of the bats is an important step that can benefit public information campaigns and may ultimately help control future outbreaks of the disease.
Introduction: The new direct acting antiviral (DAA) therapies are able to effectively treat chronic hepatitis C (CHC). This study elicited the preferences of CHC patients for treatment attributes of new DAAs.
Methods: An online discrete choice experiment survey was designed to collect data from adult CHC patients in the USA, UK, France, Germany, Spain, and Italy. Patients were asked to choose from alternative hypothetical DAA options, defined by differing levels of nine attributes [i.e., treatment duration, tablet count and packaging, cure rate, required office visits when on treatment, modifications to statins or to proton pump inhibitors (PPIs), and risks of diarrhea, headache and nausea]. Logistic regression was used to assess preference for the treatment options.
Results: A total of 328 patients with CHC completed the survey (USA, n = 227; European countries, n = 101), with a mean age of 47.7 years (SD = 14.4) and an average 11.2 years since CHC diagnosis; 51% of patients were female. More than half (60%) of the patients had treatment for CHC. Patients significantly preferred a DAA regimen with higher cure rate, shorter treatment duration, lower risks of diarrhea, headache, and nausea (all p < 0.001), reduced need for office visits when on treatment (p = 0.044), and without requiring dose reduction or timing change in PPIs (p = 0.032). Tablet counts were not found to be statistically significant.
Conclusion: Given the overall high cure rates of new DAAs, CHC patients' preferences for therapy may be influenced by treatment attributes other than cure rates and tolerability. Treatments that are more convenient and require less disruption to their daily life (e.g., shorter treatment duration, no modification in PPI use, and fewer office visits when on treatment) are important to patients with CHC and should be considered when making treatment decisions.
Evaluation of INSTAND e.V.’s external quality assessment for C-reactive protein and procalcitonin
(2019)
Background: The purpose of this paper was to analyze the general diagnostic strength and performance of in vitro diagnostics for C-reactive protein and procalcitonin based on the results of external quality assessment schemes (EQAs).
Methods: We analyzed qualitative and quantitative data on both markers collected by the Society for Promotion Quality Assurance in Medical Laboratories (INSTAND e.V.) from 20 EQAs. The C-reactive protein evaluation was method-specific and the procalcitonin evaluation manufacturer-specific (pseudonymized). Coefficients of variation were determined in order to evaluate interlaboratory comparability and the performance of individual laboratories during the analyzed period was examined.
Results: Overall most of our participants were able to correctly distinguish the positive from the negative samples, but we occasionally observed also false-positive results for the immunological detection of C-reactive protein. For the semi-quantitative results of C-reactive protein we observed an overall median difference below 5% except for dry chemistry methods (≤ 21%). For procalcitonin two manufacturer collectives showed a good comparability, while one manufacturer detected up to 42% higher results. The coefficients of variation are promising for both analytes even though they surpass the manufacturer’s indication for some collectives. The performance of individual laboratories during the analyzed period was more stable for C-reactive protein than for procalcitonin.
Conclusion: In-vitro diagnostic testing for C-reactive protein and procalcitonin showed promising results in our EQAs but still further improvements are needed. We recommend stepping up research on reference measurement methods for both parameters to possibly enhancing the accuracy and diagnostic strength of such assays.