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However, to provide more solid evidence on whether our findings are also valid for the general population, collaboration with Facebook is required to better understand how the data is being produced and pre-processed.Assistive products outcomes are needed globally to inform policy, practice, and drive investment. The International Society of Wheelchair Professionals developed a Minimum Uniform Dataset (MUD) for wheelchair services worldwide with the intent to gather data that is comparable globally. The MUD was developed with the participation of members from around the globe and its feasibility piloted at 3 sites. Three versions of the MUD are now available-a short form with 29 data points (available in English, Spanish, and French) and a standard version with 38 data points in English. Future work is to validate and complete the translation cycles followed by promoting the use of the MUD globally so that the data can be leveraged to inform policy, practice and direct investments.The expansion of Covid-19 has severely hit the community's health all over the world, killing hundreds of thousands of people, subjecting health systems to an enormous stress (besides derailing economic activities and altering personal and social behavior). Two elements are essential to monitor the evolution of the pandemic as well as to analyze the effectiveness of the response measures reliable data and useful indicators. We present an indicator that helps to assess the impact of Covid-19 on the community's health, combining two different components the extent of the pandemics (i.e. the share of the population affected) and its severity (the intensity of the disease on those affected). The severity measure derives from the application of an evaluation protocol that allows comparing population distributions based on the proportions of those affected with different health conditions. We illustrate the functioning of this indicator over a case study regarding the situation of the Italian regions on March 9 (the beginning of the confinement) and April 8, 2020, one month later.
Due to a high prevalence of chronic non-degenerative diseases, it is suspected that COVID 19 poses a high risk of fatal complications for the Mexican population. The present study aims to estimate the risk factors for hospitalization and death in the Mexican population infected by SARS-CoV-2.
We used the publicly available data released by the Epidemiological Surveillance System for Viral Respiratory Diseases of the Mexican Ministry of Health (Secretaría de Salud, SSA). All records of positive SARS-CoV-2 cases were included. Two multiple logistic regression models were fitted to estimate the association between hospitalization and mortality, with other covariables. read more Data on 10,544 individuals (57.68% men), with mean age 46.47±15.62, were analyzed. Men were about 1.54 times more likely to be hospitalized than women (p<0.001, 95% C.I. 1.37-1.74); individuals aged 50-74 and ≥74 were more likely to be hospitalized than people aged 25-49 (OR 2.05, p<0.001, 95% C.I. 1.81-2.32, and OR 3.84, p<0.001, 95% rtion of the population has two or more chronic conditions simultaneously, a high mortality rate is a serious risk for those infected by SARS-CoV-2.
The present study points out that in Mexico, where an important proportion of the population has two or more chronic conditions simultaneously, a high mortality rate is a serious risk for those infected by SARS-CoV-2.The stem volume of commercial trees is an important variable that assists in decision making and economic analysis in forest management. Wood from forest plantations can be used for several purposes, which makes estimating multi-volumes for the same tree a necessary task. Defining its exploitation and use potential, such as the total and merchantable volumes (up to a minimum diameter of interest), with or without bark, is a possible work. The goal of this study was to use different strategies to model multi-volumes of the stem of eucalyptus trees. The data came from rigorous scaling of 460 felled trees stems from four eucalyptus clones in high forest and coppice regimes. The diameters were measured at different heights, with the volume of the sections obtained by the Smalian method. Data were randomly separated into fit and validation data. The single multi-volume model, volume-specific models, and the training of artificial neural networks (ANNs) were fitted. The evaluation criteria of the models were coefficient of determination, root mean square error, mean absolute error, mean bias error, as well as graphical analysis of observed and estimated values and distribution of residuals. Additionally, the t-test (α = 0.05) was performed between the volume obtained in the rigorous scaling and estimated by each strategy with the validation data. Results showed that the strategies used to model different tree stem volumes are efficient. The actual and estimated volumes showed no differences. The multi-volume model had the most considerable advantage in volume estimation practicality, while the volume-specific models were more efficient in the accuracy of estimates. Given the conditions of this study, the ANNs are more suitable than the regression models in the estimation of multi-volumes of eucalyptus trees, revealing greater accuracy and practicality.Economic evaluations of new youth mental health interventions require preference-based outcome measures that capture the broad benefits these interventions can have for adolescents. The Abbreviated Self Completion Teen-Addiction Severity Index (ASC T-ASI) was developed to meet the need for such a broader measure. It assesses self reported problems in seven important domains of adolescents' lives, including school performance and family relationships, and is intended for use in economic evaluations of relevant interventions. The aim of the current study was to present the ASC T-ASI and examine its validity as well as its ability to distinguish between adolescents with and without problems associated with substance use and delinquency. The validation study was conducted in a sample of adolescents (n = 167) aged 12-18 years, who received in- or outpatient care in a youth mental health and (enclosed) care facility in the Netherlands. To examine its feasibility, test-retest reliability, and convergent validity, respondents completed the ASC T-ASI, as well as the EQ-5D-3L and SDQ at baseline and after a two-week interval using a counterbalanced method.