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BackgroundMen and older women have been shown to be at higher risk of adverse COVID-19 outcomes. Animal model studies of SARS-CoV and MERS suggest that the age and sex difference in COVID-19 symptom severity may be due to a protective effect of the female sex hormone estrogen. Females have shown an ability to mount a stronger immune response to a variety of viral infections because of more robust humoral and cellular immune responses.ObjectivesWe sought to determine whether COVID-19 positivity increases in women entering menopause. We also aimed to identify whether premenopausal women taking exogenous hormones in the form of the combined oral contraceptive pill (COCP) and post-menopausal women taking hormone replacement therapy (HRT) have lower predicted rates of COVID-19, using our published symptom-based model.DesignThe COVID Symptom Study developed by King’s College London and Zoe Global Limited was launched in the UK on 24th March 2020. It captured self-reported information related to COVID-19 symptoms. Data used for this study included records collected between 7th May - 15th June 2020.Main outcome measuresWe investigated links between COVID-19 rates and 1) menopausal status, 2) COCP use and 3) HRT use, using symptom-based predicted COVID-19, tested COVID-19, and disease severity based on requirement for hospital attendance or respiratory support.ParticipantsFemale users of the COVID Symptom Tracker Application in the UK, including 152,637 women for menopause status, 295,689 for COCP use, and 151,193 for HRT use. Analyses were adjusted for age, smoking and BMI.ResultsPost-menopausal women aged 40-60 years had a higher rate of predicted COVID (P=0.003) and a corresponding range of symptoms, with consistent, but not significant trends observed for tested COVID-19 and disease severity. Women aged 18-45 years taking COCP had a significantly lower predicted COVID-19 (P=8.03E-05), with a reduction in hospital attendance (P=0.023). Post-menopausal women using HRT or hormonal therapies did not exhibit consistent associations, including increased rates of predicted COVID-19 (P=2.22E-05) for HRT users alone.ConclusionsOur findings support a protective effect of estrogen on COVID-19, based on positive association between predicted COVID-19 and menopausal status, and a negative association with COCP use. HRT use was positively associated with COVID-19 symptoms; however, the results should be considered with caution due to lack of data on HRT type, route of administration, duration of treatment, and potential comorbidities.Trial registrationThe App Ethics has been approved by KCL ethics Committee REMAS ID 18210, review reference LRs-19/20-18210

Premi al millor PFC en l'Àrea de Sistemes de la informació d'Enginyeria de Telecomunicació o d'Enginyeria Electrònica de l'ETSETB-UPC (curs 2013-2014). Atorgat per Cátedra Red.es Social Recommender Systems were born with the goal to mitigate the current information overload caused by the birth of Social Networks among other causes. They have enabled Internet actors (e.g. users, web browsers, sensors, actuators, etc.) to make more informed decisions based on the information that is been shown to them, up to the point that some actors even blindly trust the recommendation generated by these systems. Within this scenario, this thesis proposes a novel Hybrid Social Recommender System purely based on the text reviews typed by users. The proposed engine treats the review content and sentiment separately and finally, combines both into a single recommendation. Very little scientific research has been published on mining text reviews with the aim of performing item recommendation. Moreover, among all Hybrid Recommendation Systems in the literature, none use the above-mentioned review features into a collaborative and content-based recommender. With the purpose in mind of assessing the platform effectiveness, we present a methodology that goes from the process of extracting the data directly from a Social Network, cleaning and pre-processing the text data, building the predictive model with different state-of-the art machine learning techniques, up to the point of evaluating the system in terms of several key metrics. The data extraction process gains our attention due to the challenges imposed by most social platforms in obtaining all the geo-positioned data generated in a bounded region. To overcome the platform limitations, we introduce the use of the Quadtree algorithm with the goal of crawling all the geo-positioned reviews. The algorithm is enhanced with a module that copes with the time dynamics and captures the time-stamped data as well. Moreover, we study the effectiveness of the Quadtree partition method to crawl any type of spatial data, which tends to be softly distributed in the area. This thesis draws several conclusions from the available data about the use of several state-of-the art text mining techniques and the effectiveness of the proposed recommender setup. Nonetheless, future work needs to design and propose novel evaluation methodologies that uncouple the system evaluation from the data. Award-winning

Projecte fet en col.laboració amb Georgia Institute of Technology Català: En aquest projecte estudiem la comunicació entre diversos nano-dispositius que configuren una Nanoxarxa Electromagnètica sense cables. Tenint en compte les peculiaritats de la capa física, proposem un mètode d'accés múltiple, Rate Division Time Spread On-Off (RD TS-OOK), basat en la transmissió de polsos de femto-segons de duració, els quals són enviats a diferents temps entre símbols per a cada usuari. A sobre d'aquest mètode d'accés múltiple construïm un nou protocol MAC, interference-Aware Adaptive Asynchronous (i-AAA), el qual assegura una entrega justa del paquests de manera asíncrona, simple, però robusta. Finalment, analitzem el rendiment dels mecanismes proposats i optimitzem els seus paràmetres de manera que funcionin de la manera més eficient. La longitud dels paquets de dades té un impacte especial sobre el rendiment del protocols. És per això, que optimitzem el seu valor en base a una mètrica què té en compte l'eficiència energètica del protocol. Castellano: En este proyecto estudiamos la comunicación entre varios nano-dispositivos que configuran una Nanored electromágnetica sin cables. Teniendo en cuenta las peculiaridades de la capa física, proponemos un método de acceso múltiple, Rate Division Time Spread On-Off (RD TS-OOK), basado en la transmisión de pulsos de femto-segundos de duración, los cuales son enviados a diferente tiempo entre símbolos para cada usuario. En base a este método de acceso múltiple construimos un nuevo protocolo MAC, interference-Aware Adaptive Asynchronous (i-AAA), el cual asegura la entrega de los paquetes de forma asíncrona, simple, pero robusta. Finalmente, analizamos el rendimiento de los mecanimos propuestos y optimizamos sus parámetros de modo que funcionen de manera más eficiente. La longitud de los paquetes de datos tiene un impacto especial en el rendimiento de los protocolos. Es por eso, que optimizamos su valor en base a una métrica que tiene en cuenta la eficiencia energetic del protocolo. English: In this work, we study the communication among many nano-devices configuring electromagnetic Nanonetworks. Taking into account the underlying physical layer, we propose a multiple access method, Rate Division Time Spread On-Off Keying (RD TS-OOK), which is based on the radiation of femtosecond-long pulses with different intersymbol durations for each user. On top of this multiple access method, we build up a new MAC protocol, interference-Aware Adaptive Asynchronous (i-AAA), that ensures fair packet delivery in an asynchronous, simple but robust way. Finally, the performances of the proposed mechanisms are analytically studied and their parameters optimized in order to efficiently adjust them. Packet size has an special impact on the protocol performances; this is why, we lastly optimize its value based on an energy efficiency metric.

Background: Multiple participatory surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of community-wide COVID-19 epidemiology. During this time, testing criteria broadened and healthcare policies matured. We sought to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three national surveillance platforms, during periods of testing and policy changes, and whether inconsistencies could better inform our understanding and future studies as the COVID-19 pandemic progresses., Methods: Four months (1st April 2020 to 31st July 2020) of observation through three volunteer COVID-19 digital surveillance platforms targeting communities in three countries (Israel, United Kingdom, and United States). Logistic regression of self-reported symptom on self-reported SARS-CoV-2 test status (or test access), adjusted for age and sex, in each of the study cohorts. Odds ratios over time were compared to known changes in testing policies and fluctuations in COVID-19 incidence., Findings: Anosmia/ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test, based on 658,325 tests (5% positive) from over 10 million respondents in three digital surveillance platforms using longitudinal and cross-sectional survey methodologies. During higher-incidence periods with broader testing criteria, core COVID-19 symptoms were more strongly associated with test status. Lower incidence periods had, overall, larger confidence intervals., Interpretation: The strong association of anosmia/ageusia with self-reported SARS-CoV-2 test positivity is omnipresent, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform or testing policy. This analysis highlights that precise effect estimates, as well as an understanding of test access patterns to interpret differences, are best done only when incidence is high. These findings strongly support the need for testing access to be as open as possible both for real-time epidemiologic investigation and public health utility., Funding: NIH, NIHR, Alzheimer's Society, Wellcome Trust.