An analysis of morbidity and mortality using Google Trends

Improvement in information technology has led to an increase in the ability of individuals to access health information; however, there still exists a large gap between patient and physician knowledge about diseases and/or illnesses. Often patients find themselves in doubt or overwhelmed by the care they are given. High medical costs also persist which makes the experience of patients less than ideal. For these reasons, among others, the internet has become a very popular tool in the hands of individuals who may wish to better understand the status of their health, make more informed decisions about their treatment options, and/or find cheaper ways to maintain good health status or cure a disease. Internet search engines, especially Google, play a crucial role in providing a means for patients to get the health information they need. The analysis presented in this article seeks to investigate the possibility of using Google Trends data to analyze the relationship between internet searches on the major causes of death and actual mortality in the United States. Specifically, this research seeks to investigate how well Google search query data serve as proxy for data on the actual causes of death.     

Ichthyofauna diet changes in response to urbanization: the case of upper Paranapanema River basin (Brazil)

Alterations in stream environments can alter fish food availability, but there is little research data related to the impacts of urbanization on fish diets in tropical streams. Thus, we sought to compare the diet of ten fish species in urbanized and non-urbanized streams reaches. Fish stomach contents were obtained for four urban and five non-urban stream reaches from two medium-sized cities. We verified the similarity of diet composition from urbanized/non-urbanized streams. In-stream features mainly related to the substrate highlighted a perturbation gradient: gravel, pebbles and cobbles were associated to the wider urban reaches while silt were representative in the narrow pools from non-urban streams. Fishes changed their diet in response to urban and non-urban treatments. Omnivorous fishes consumed more detritus and Chironomidae and less terrestrial adult insects in urban reaches, while invertivorous fish consumed more terrestrial adult insects and Trichoptera larvae in the non-urbanized stream reaches. Although the management of the physical structure of streams in Brazil has been basically focused on riparian reforestation, our results suggest that a restoration plan for urban streams cannot be limited to reforestation of its surroundings, but also need to consider the physical structure of the channel, especially the substrate, which contributes to promote in-stream variability.     

Effects of resistance training on liver structure and function of aged rats

The aging process may cause negative physiological changes. However, exercises as resistance training (RT) have been considered an important intervention to attenuate these changes. Additionally, liver plays an important role in blood glucose homeostasis in exercise.

Aim: This study aimed to analyze the effects of RT on the liver components of aged animals.

Methods: Male Wistar rats were divided into two groups: 24 months’ group (CONTROL); and group submitted to a progressive RT protocol for 16 weeks (EXERCISE). Both groups were sacrificed at 24 months.

Results: We observed a decrease in blood flow due to the practice of resistance exercises. Besides, our results showed that hepatic tissue plays an important role in glycemic homeostasis during RT. In addition, RT increased mitogen capacity of hepatocytes.

Conclusions: Our study showed many implications for the knowledge about the effects of strength training on old animals’ liver.     

Improving Well-Being in Bhutan: A Pursuit of Happiness or Poverty Reduction?

Increasing happiness is a key priority for the Bhutanese government. This priority displaces more traditional (economic) objectives such as the pursuit of income growth and the reduction of income poverty. This paper examines the implications of this approach by examining whether there are common correlates of the four following measures of human well-being in Bhutan: income poverty; multidimensional poverty; perceived poverty; and happiness. Our findings suggest that whilst there is a degree of commonality, determinants of the different measures of well-being are distinct. Common factors include having a savings account, levels of literacy and household size. Further we show that higher levels of income poverty, multidimensional poverty and perceived poverty are found to be negatively associated with happiness. Importantly, our findings suggest that a focus on increasing happiness might come at the expense of improving other measures of wellbeing.     

Is there a causal relationship between oil prices and tourist arrivals?

This application note investigates the causal relationship between oil price and tourist arrivals to further explain the impact of oil price volatility on tourism-related economic activities. The analysis itself considers the time domain, frequency domain and information theory domain perspectives. Data relating to US and nine European countries are exploited in this paper with causality tests which include time domain, frequency domain, and Convergent Cross Mapping (CCM). The CCM approach is nonparametric and therefore not restricted by assumptions. We contribute to existing research through the successful and introductory application of an advanced method, and via the uncovering of significant causal links from oil prices to tourist arrivals.     

Augmented-limited regression models with an application to the study of the risk perceived using continuous scales

Studies of risk perceived using continuous scales of [0,100] were recently introduced in psychometrics, which can be transformed to the unit interval, but the presence of zeros or ones are commonly observed. Motivated by this, we introduce a full inferential set of tools that allows for augmented and limited data modeling. We considered parameter estimation, residual analysis, influence diagnostic and model selection for zero-and/or-one augmented beta rectangular (ZOABR) regression models and their particular nested models, which is based on a new parameterization of the beta rectangular distribution. Different from other alternatives, we performed maximum-likelihood estimation using a combination of the EM algorithm (for the continuous part) and Fisher scoring algorithm (for the discrete part). Also, we perform an additional step, by considering other link functions, besides the usual logistic link, for modeling the response mean. By considering randomized quantile residuals, (local) influence diagnostics and model selection tools, we identified that the ZOABR regression model is the best one. We also conducted extensive simulations studies, which indicate that all developed tools work properly. Finally, we discuss the use of this type of models to treat psychometric data. It is worthwhile to mention that applications of the developed methods go beyond to Psychometric data. Indeed, they can be useful when the response variable in bounded, including or not the respective limits.     

Sustainability Ranking for Cuban Tourist Destinations Based on Composite Indexes

This investigation approaches the levels and the predictors of loneliness among migrant youths from returned migrant families from France to Portugal. Three research questions guided the study: (1) Does loneliness of migrant youths differ from those who have never migrated? (2) Are migrant youths’ re-acculturation factors related to their loneliness? (3) Is the adaptation of migrant youths linked to their loneliness? The answer to these questions is important to improve migrant youths’ re-acculturation experiences and their adaptation. The sample included 222 youths from returned migrant families from France. Participants completed the brief Portuguese version of the Revised UCLA Loneliness Scale (ULS-6), in addition to measures of re-acculturation and adaptation. A control group comprised of 211 Portuguese adolescents who have never migrated was also involved in the investigation. Youths from returned migrant families showed lower levels of loneliness than their native Portuguese counterparts who have never migrated. Demographic, re-acculturation, and adaptation factors were significantly related to adolescents’ loneliness. Major predictors of loneliness were age at return, contacts with peers without migratory experience, perceived discrimination, stressful adaptation experience, and satisfaction with life.     

Asymmetric autoregressive models: statistical aspects and a financial application under COVID-19 pandemic

In the present study, we provide a motivating example with a financial application under COVID-19 pandemic to investigate autoregressive (AR) modeling and its diagnostics based on asymmetric distributions. The objectives of this work are: (i) to formulate asymmetric AR models and their estimation and diagnostics; (ii) to assess the performance of the parameters estimators and of the local influence technique for these models; and (iii) to provide a tool to show how data following an asymmetric distribution under an AR structure should be analyzed. We take the advantages of the stochastic representation of the skew-normal distribution to estimate the parameters of the corresponding AR model efficiently with the expectation-maximization algorithm. Diagnostic analytics are conducted by using the local influence technique with four perturbation schemes. By employing Monte Carlo simulations, we evaluate the statistical behavior of the corresponding estimators and of the local influence technique. An illustration with financial data updated until 2020, analyzed using the methodology introduced in the present work, is presented as an example of effective applications, from where it is possible to explain atypical cases from the COVID-19 pandemic.     

Contextual movement models based on normalizing flows

AStA Advances in Statistical Analysis - Movement models predict positions of players (or objects in general) over time and are thus key to analyzing spatiotemporal data as it is often used in...     

Radiological Risk Assessment by Convergence Methodology Model in RDD Scenarios

A radiological dispersal device (RDD) is a simple weapon capable of causing human harm, environmental contamination, disruption, area denial, and economic cost. It can affect small, large, or long areas depending on atmospheric stability. The risk of developing a radio‐induced cancer depends on exposure, and an effective response depends upon available timely guidance. This article proposes and demonstrates a convergence of three different capabilities to assess risk and support rapid safe resource efficient response. The three capabilities that are integrated are Hotspot for dispersion, RERF for epidemiological risk, and RESRAD‐RDD for response guidance. The combined methodology supports decisions on risk reduction and resource allocation through work schedules, the designation and composition of response teams, and siting for operations. In the illustrative RDD scenario, the contamination area for sheltering, evacuation, and long‐term public concern was greatest for calm atmospheric conditions, whilst close‐quarter responders faced highest dose rates for neutral atmospheric conditions. Generally, the risks to women responders were found to be significantly greater than for men, and the risks to 20‐year‐old responders were three times that of their 60‐year‐old counterparts for similar exposure.