Lessons learned from urgent computing in Europe: Tackling the COVID-19 pandemic.

PRACE (Partnership for Advanced Computing in Europe), an international not-for-profit association that brings together the five largest European supercomputing centers and involves 26 European countries, has allocated more than half a billion core hours to computer simulations to fight the COVID-19 pandemic. Alongside experiments, these simulations are a pillar of research to assess the risks of different scenarios and investigate mitigation strategies. While the world deals with the subsequent waves of the pandemic, we present a reflection on the use of urgent supercomputing for global societal challenges and crisis management.

[The importance of digitalisation in urology]. / Stellenwert der Digitalisierung im urologischen Alltag.

The Internet has shaped and changed society like no other technology. Culturally, the emergence of the Internet is being described as having the same impact on society as the invention of printing. In 2018, more than 4 billion people had access to the Internet. Among all Internet users, approximately 80 % search the Internet for health-related information, with cancer being the most frequently searched condition. Patients rate the Internet as the second most helpful source of information, outranked only by consultation with a medical doctor. There are more than 2.6 billion active social media users. Among urological residents, 97 % use social media on a regular basis. Digitalisation has the potential to strengthen patients' health literacy and optimise patient care, especially in the oncologic field. In summary, digitalisation bears an enormous potential for the field of urology.

A statistician's perspective on digital epidemiology.

We address the question "does digital epidemiology represent an epistemic shift in infectious disease epidemiology" from a statistician's viewpoint. Our main argument is that infectious disease epidemiology has not changed fundamentally as it always has been data-driven. However, as the data aspect has become more prominent, we discuss the statistical toolbox of the modern epidemiologist and argue that problem solving in the digital age, more than ever requires an interdisciplinary quantitative approach.

Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings.

Internet-derived information has been recently recognized as a valuable tool for epidemiological investigation. Google Trends, a Google Inc. portal, generates data on geographical and temporal patterns according to specified keywords. The aim of this study was to compare the reliability of Google Trends in different clinical settings, for both common diseases with lower media coverage, and for less common diseases attracting major media coverage. We carried out a search in Google Trends using the keywords "renal colic", "epistaxis", and "mushroom poisoning", selected on the basis of available and reliable epidemiological data. Besides this search, we carried out a second search for three clinical conditions (i.e., "meningitis", "Legionella Pneumophila pneumonia", and "Ebola fever"), which recently received major focus by the Italian media. In our analysis, no correlation was found between data captured from Google Trends and epidemiology of renal colics, epistaxis and mushroom poisoning. Only when searching for the term "mushroom" alone the Google Trends search generated a seasonal pattern which almost overlaps with the epidemiological profile, but this was probably mostly due to searches for harvesting and cooking rather than to for poisoning. The Google Trends data also failed to reflect the geographical and temporary patterns of disease for meningitis, Legionella Pneumophila pneumonia and Ebola fever. The results of our study confirm that Google Trends has modest reliability for defining the epidemiology of relatively common diseases with minor media coverage, or relatively rare diseases with higher audience. Overall, Google Trends seems to be more influenced by the media clamor than by true epidemiological burden.

Errores correlacionados y estimación de la fiabilidad en estudios de validación: comentarios al trabajo validación de la Escala Ehealth Literacy (EHEALS) en población universitaria española / No disponible

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Respuesta de los autores. Errores correlacionados y estimación de la fiabilidad en estudios de validación: comentarios al trabajo validación de la Escala EHealth Literacy (EHEALS) en población universitaria española / No disponible

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Service oriented architecture for clinical decision support: a systematic review and future directions.

The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS.

The promise of data-driven care.

The growing adoption of electronic medical records and advances in health information technology are fueling an explosion of new health data. Expectations are high that new data resources will guide the transformation of the health care industry and positively influence population health. There have been challenges and opportunities at every turn, and progress has been slow, but mounting evidence suggests that better use of data is moving health care in the right direction.

Growth in health care data causing an evolution in the pharmaceutical industry.

A health care ecosystem is evolving in which all stakeholders will need to work together, apply new technologies, and use disparate data sources to gain insights, increase efficiencies, and improve patient outcomes. The pharmaceutical industry is leveraging its experience and analytics capabilities to play an important role in this evolution.

A new approach for differential item functioning detection using mantel-haenszel methods. The GMHDIF program

To date, the statistical software designed for assessing differential item functioning (DIF) with Mantel-Haenszel procedures has employed the following statistics: the Mantel-Haenszel chi-square statistic, the generalized Mantel-Haenszel test and the Mantel test. These statistics permit detecting DIF in dichotomous and polytomous items, although they limit the analysis to two groups. On the contrary, this article describes a new approach (and the related software) that, using the generalized Mantel-Haenszel statistic proposed by Landis, Heyman, and Koch (1978), permits DIF assessment in multiple groups, both for dichotomous and polytomous items. The program is free of charge and is available in the following languages: Spanish, English and Portuguese (AU)

Hasta la fecha, los programas informáticos diseñados específicamente para detectar el funcionamiento diferencial de los ítems (DIF) usando los métodos Mantel-Haenszel han empleado los siguientes estadísticos: el estadístico ji-cuadrado de Mantel-Haenszel, el test generalizado de Mantel-Haenszel y el test de Mantel. El presente artículo describe una nueva aproximación (y el software correspondiente) que permite evaluar el DIF en múltiples grupos, tanto en ítems dicotómicos como politómicos, empleando el estadístico generalizado de Mantel-Haenszel propuesto por Landis, Heyman, and Koch (1978). El programa es gratuito y está disponible en español, inglés y portugués (AU)

[Facing the challenges of ubiquitous computing in the health care sector]. / Herausforderungen durch ubiquitäres Computing im Gesundheitsbereich.

The steady progress of microelectronics, communications and information technology will enable the realisation of the vision for "ubiquitous computing" where the Internet extends into the real world embracing everyday objects. The necessary technical basis is already in place. Due to their diminishing size, constantly falling price and declining energy consumption, processors, communications modules and sensors are being increasingly integrated into everyday objects today. This development is opening up huge opportunities for both the economy and individuals. In the present paper we discuss possible applications, but also technical, social and economic barriers to a wide-spread use of ubiquitous computing in the health care sector.

Pervasive healthcare: paving the way for a pervasive, user-centered and preventive healthcare model.

OBJECTIVES: The aging of the population creates pressure on the healthcare systems in various ways. A massive increase of chronic disease conditions and age-related illness are predicted as the dominant forces driving the future health care. The objective of this paper is to present future research demands in pervasive healthcare with the goal to meet the healthcare challenges by paving the way for a pervasive, user-centered and preventive healthcare model. METHODS: This paper presents recent methodological approaches and proposes future research topics in three areas: i) pervasive, continuous and reliable long-term monitoring systems; ii) prevention through pervasive technology as a key element to maintain lifelong wellness; and iii) design and evaluation methods for ubiquitous, patient-centric technologies. RESULTS: Pervasive technology has been identified as a strong asset for achieving the vision of user-centered preventive healthcare. In order to make this vision a reality, new strategies for design, development and evaluation of technology have to find a common denominator and consequently interoperate. Moreover, the potential of pervasive healthcare technologies offers new opportunities beyond traditional disease treatment and may play a major role in prevention, e.g. motivate healthy behavior and disease prevention throughout all stages of life. In this sense, open challenges in future research have to be addressed such as the variability of health indicators between individuals and the manner in which relevant health indicators are provided to the users in order to maximize their motivation to mitigate or prevent unhealthy behaviors. Additionally, collecting evidence that pervasive technology improves health is seen as one of the toughest challenges. Promising approaches are recently introduced, such as "clinical proof-of-concept" and balanced observational studies. CONCLUSIONS: The paper concludes that pervasive healthcare will enable a paradigm shift from the established centralized healthcare model to a pervasive, user-centered and preventive overall lifestyle health management. In order to provide these new opportunities everywhere, anytime and to anyone, future research in the fields of pervasive sensing, pervasive prevention and evaluation of pervasive technology is inevitably needed.