COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning.

A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function is minimized in the framework of trigonometric regression. While, in our subsequent spatial residual correlation analysis, maximization of the likelihood allows us to compute the posterior mode in a Bayesian multivariate time series soft-data framework. The presented approach is applied to the analysis of COVID-19 mortality in the first wave affecting the Spanish Communities, since March 8, 2020 until May 13, 2020. An empirical comparative study with Machine Learning (ML) regression, based on random k-fold cross-validation, and bootstrapping confidence interval and probability density estimation, is carried out. This empirical analysis also investigates the performance of ML regression models in a hard- and soft-data frameworks. The results could be extrapolated to other counts, countries, and posterior COVID-19 waves. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00477-021-02021-0.

Use of multivariate NMR analysis in the content prediction of hemicellulose, cellulose and lignin in greenhouse crop residues.

We have introduced the use of multivariate NMR analysis in the development of accurate and robust prediction models, potentially arising from a correlation between soluble metabolite profiles and cell wall composition, for the determination of hemicellulose, cellulose and lignin contents in 8 species of greenhouse crop residues. The present paper demonstrates that discriminant buckets coming from a PLS-DA model in combination with linear models provide a useful and rapid tool for the determination of cell wall composition of these plant wastes. Regularized linear regression methods have also been applied to avoid overfitting, producing improved models specifically for lignin and cellulose determinations. The predictive models are also presented in a desktop application available at http://www2.ual.es/NMRMBC/solutions. To verify the rationality and reliability of the models, control experiments following generally accepted protocols have been performed and compared to our predicted values.

Screening for hazardous drinking in migrant workers in southeastern Spain.

OBJECTIVES: Despite the great impact the migration has had in economic, social and health-related fields, and the repercussions of alcohol consumption on them, few data exist concerning the extent of alcohol consumption in migrant workers. The aims of this study were to identify workers with a hazardous drinking problem by means of a self-reported questionnaire (Alcohol Use Disorders Identification Test-AUDIT) and a biomarker (carbohydrate-deficient transferrin-CDT) and to ascertain associated risk factors. METHODS: A cross-sectional survey was conducted using a random sample of 385 migrant workers, undergoing a routine health examination as part of occupational health services. RESULTS: The results showed that 13.8% (n=53) of the workers were screened as positive with the AUDIT (≥8) and/or CDT (>2.6) and identified as hazardous drinkers and that 53.8% (n=207) were teetotallers. Being a man (OR: 2.0), working in the construction industry (OR: 2.8) or agriculture (OR: 2.2), being resident in Spain for more than 7 years (OR: 2.3) and sharing a house with friends were the factors most closely associated with hazardous drinking. CONCLUSIONS: Prevention-orientated programs, adjusted to the characteristics of each country and the origin of the migrants themselves, should be instituted to modify the drinking habits of migrant workers considered at risk.

Screening for hepatitis B virus and hepatitis C virus at a community fair: a single-center experience.

Despite recommendations for screening for hepatitis B virus (HBV) and hepatitis C virus (HCV), most individuals are still unaware of their infection status. The disparities in screening for HBV and HCV can be attributed to lack of awareness, language barriers, and difficulty in accessing healthcare. To address these issues, an exhibit booth was set up at an annual cultural festival to promote awareness about HBV and HCV and also provide free screening for a local Floridian community. Recruitment was conducted in various languages by physicians and nurses who specialize in hepatology. All materials associated with the screening process were sponsored by the Schiff Center for Liver Diseases, which is located at the University of Miami Miller School of Medicine in Florida. In the first year of the screening initiative, 173 of 11,000 fair attendees were screened for HBV. Twenty-nine (17%) of those screened tested positive for antibodies to hepatitis B core antigen (anti-HBc), and only 1 individual tested positive for chronic HBV, with positive hepatitis B surface antigen (HBsAg). Screening for HCV and an extended patient questionnaire were added to the screening program in the second year of the initiative. A total 231 of 9,000 fair attendees volunteered to be screened for both HBV and HCV. Twenty-nine (13%) of these people tested positive for anti-HBc, and 3 tested positive for HBsAg. Only 1 person tested positive for anti-HCV, but this individual had undetectable HCV RNA levels. Our single-center experience illustrates that, despite efforts to improve access to screening, only 2-3% of attendees at a cultural fair embraced the screening efforts. Other strategies will be required to enhance participation in screening programs for viral hepatitis.