Pablo Fdez-Arroyabe

Co-creation and Participatory Design of Big Data Infrastructures on the Field of Human Health Related Climate Services

Co-creation of scientific knowledge based on new technologies and big data sources is one of the main challenges for the digital society in the XXI century. Data management and the analysis of patterns among datasets based on machine learning and artificial intelligence has become essential for many sectors nowadays. The development of real time health-related climate services represents an example where abundant structured and unstructured information and transdisciplinary research are needed. The study of the interactions between atmospheric processes and human health through a big data approach can reveal the hidden value of data. The Oxyalert technological platform is presented as an example of a digital biometeorological infrastructure able to forecast, at an individual level, oxygen changes impacts on human health.

Past, present and future of the climate and human health commission

The following paper presents the history of the Climate and Human Health Commission at the International Society of Biometeorology after more than one decade since its creation. A brief history of the origins of the human biometeorology is revealed through some of the main research topics and publications of the founders of the society in this field. Secondly, it is presented as a brief review of the activities of the commission in the last 10xa0years, based on the reports that have periodically been submitted by members of the commission to the Bulletin of the society. A summary of the topics of interest on human biometeorology and the most frequent research topics are also described. Thirdly, the need of adapting human biometeorology contents, methods and techniques to a changing world is articulated according to some of the new environmental threats in the XXI century. Finally, a list of future actions and research lines collected through a form from members of the commission is presented. The paper concludes with the existence of great challenge for human biometeorology in order to transform biometeorological knowledge into specific services to improve the wellbeing of human beings.

Aerial and Satellite Imagery and Big Data: Blending Old Technologies with New Trends

Over the past decades, the successful employment of aerial and satellite imagery and remote sensing (RS) data has been very diverse and important in many scientific fields. Firstly, a brief review of RS history is presented in section one. Then, basic properties, which are also challenges, of RS big data are concisely discussed. Volume, variety and velocity are mainly described as characteristics of RS big data while variety, value and visualization are primarily denoted as new challenges. The third section is concentrated on justifying the relevance of RS big data in today’s society and the needs to integrate it with other kind of data sources to develop useful services. In this sense, a special section is dedicated to Copernicus initiative and some case studies of specific applications are also shown. Finally, some general conclusions are presented paying attention to the spatial nature of RS big data, which gives it a special added value in the new digital era.

Kawasaki disease in Spanish paediatric population and synoptic weather types: an observational study

Kawasaki disease (KD) is a vasculitis of unelucidated pathogenesis that usually occurs in paediatric patients. In this study we analyse the temporal pattern and geographical distribution of the disease in Spain, and its relationship with atmospheric circulation patterns. We performed a retrospective study in which we collected all hospital admissions due to KD in the country between 2005 and 2015 and explored their relationship with demographic and geographical characteristics. Moreover, we calculated daily surface atmospheric patterns over Spain to study the relationship between weather types (WT) and KD Admissions. The average admission rate for KD in the paediatric population was 3.90 per 100,000, with a male to female ratio of 1.56:1. The highest rate of admissions was found in the 0–4-year-old group, with an incidence of 11.7 cases per 100,000. Admissions followed an annual cyclic pattern with a peak of incidence in January (pu2009=u20090.022) and a nadir in September. There was an upwards trend in the number of KD admissions in male sex during the study period (pu2009=u20090.004). However, there were marked geographical differences in the incidence rate. Finally, the analysis of the relationship between the WT and the number of admissions by KD revealed no statistically significant association. KD admissions follow a peculiar seasonal and spatial distribution, that suggest the involvement of environmental factors in the disease; however, the absence of an association with WT should be interpreted with caution and regional studies should be done to explore this relationship.

Role of Apparent Temperature and Air Pollutants in Hospital Admissions for Acute Myocardial Infarction in the North of Spain

INTRODUCTION AND OBJECTIVESnThe role of the environment on cardiovascular health is becoming more prominent in the context of global change. The aim of this study was to analyze the relationship between apparent temperature (AT) and air pollutants and acute myocardial infarction (AMI) and to study the temporal pattern of this disease and its associated mortality.nnnMETHODSnWe performed a time-series study of admissions for AMI in Cantabria between 2001 and 2015. The association between environmental variables (including a biometeorological index, AT) and AMI was analyzed using a quasi-Poisson regression model. To assess potential delayed and non-linear effects of these variables on AMI, a lag non-linear model was fitted in a generalized additive model.nnnRESULTSnThe incidence rate and the mortality followed a downward trend during the study period (CC=-0.714; P=.0002). An annual pattern was found in hospital admissions (P=.005), with the highest values being registered in winter; a weekly trend was also identified, reaching a minimum during the weekends (P=.000005). There was an inverse association between AT and the number of hospital admissions due to AMI and a direct association with particulate matter with a diameter smaller than 10 μm.nnnCONCLUSIONSnHospital admissions for AMI followed a downward trend between 2007 and 2015. Mortality associated with admissions due to this diagnosis has decreased. Predictive factors for this disease were AT and particulate matter with a diameter smaller than 10 μm.

Digital divide, biometeorological data infrastructures and human vulnerability definition

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user’s geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.