ABSTRACT
The paralysis of global tourism caused by COVID-19 made it possible to conduct a unique and nearly real-time online survey to investigate adaptations and reactions to sudden severe leisure travel restrictions among residents in the Oslo metropolitan area of Norway during the 2020 Easter/spring holiday period. Stress relief, socialising, social bonds and discoveries of local recreation options were important home holiday experiences. Vacation challenges under lockdown included few opportunities for novelty and the chance of liminoid situations–reversal or bracketing of everyday routine existence. The enforced Easter staycation advanced reflections on impending leisure travel, indicating limited opportunities to boost future low-carbon near-home Easter holiday experiences. Path dependencies towards second homes and spatially stretched social obligations, as well as emphasis on freedom of movement, ostensibly constrain vacation travel habit discontinuities at this time of the year. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
Semi-supervised learning (SSL) leverages both labeled and unlabeled data for training models when the labeled data is limited and the unlabeled data is vast. Frequently, the unlabeled data is more widely available than the labeled data, hence this data is used to improve the level of generalization of a model when the labeled data is scarce. However, in real-world settings unlabeled data might depict a different distribution than the labeled dataset distribution. This is known as distribution mismatch. Such problem generally occurs when the source of unlabeled data is different from the labeled data. For instance, in the medical imaging domain, when training a COVID-19 detector using chest X-ray images, different unlabeled datasets sampled from different hospitals might be used. In this work, we propose an automatic thresholding method to filter out-of-distribution data in the unlabeled dataset. We use the Mahalanobis distance between the labeled and unlabeled datasets using the feature space built by a pre-trained Image-net Feature Extractor (FE) to score each unlabeled observation. We test two simple automatic thresholding methods in the context of training a COVID-19 detector using chest X-ray images. The tested methods provide an automatic manner to define what unlabeled data to preserve when training a semi-supervised deep learning architecture. © 2022 IEEE.
ABSTRACT
Objective: To share with researchers the strategies used in the Parkinson's Foundation (PF) PDGENEration study to encourage the recruitment of minorities in genetic research. Background: Hispanics are interested in research participation and believe these efforts are key [1];but hindering barriers (i.e., transportation, low education, childcare, work schedules, English only documents) remain unaddressed by researchers. [2]. Methods: The PF created the GEN-EP Latino Advisory Committee to aid in the recruitment of Hispanic participants. The members of the advisory committee encompass representatives of the Hispanic community that work closely in the field of PD. Monthly meetings take place to continuously evaluate the needs of the community, identify study and recruitment barriers, create culturally appropriate study materials, evaluate the content of educational videos and plan outreach events. Results: All created documents were culturally tailored ensuring careful consideration of dialectal variations of the Spanish language. Access barriers were addressed by 1) Providing multiple ways for study sign up (phone, zoom events, and website), and 2) Recruitment of Spanish speaking staff to allow participants to experience the whole study in their native language. Due to COVID, all events were virtual and included relevant PD topics, engaging at home exercises with music, and panels of professionals, promotores, and Hispanics with PD sharing their points of view. Since 2020, we have hosted four events with a total of 280 attendees. [table1] After all these efforts, the recruitment of Hispanics has doubled to more than 6%. [table2]. Conclusion: Although the study is still in progress, we wish to share our strategies to spark recruitment of minorities across all research. The Hispanic community is eager to help in the advancement of science and it is now our job, as researchers, to address existing barriers. Creative thinking and additional efforts across all areas of study design and implementation ensure culturally competent research. It is time to achieve greater and more diverse knowledge that applies beyond the overrepresented majority.
ABSTRACT
The pandemic shows how closely health is linked to the economy, employment and wider issues. The EU works across all these areas and has tried to respond accordingly. The European Commission (EC) works in close coordination between the different services to align health and other perspectives: tests and distancing measures are a case in point. The EU will continue to address the pandemic with the utmost care and responsibility to: (1) Ensure that health is a central part of the European road to recovery: the forward-looking EU4Health program is a clear signal that health is health of EU citizens is a priority. It reflects aspirations to take a real step forward in how the EU deals with health. The Commission has the potential to help MS make their health systems more resilient so that quality health care is available to all, (2) Prepare health systems and programs for the future and make the recovery agenda health-proof: EC will propose a more robust framework for health threats and seek to strengthen and strengthen the EMA and ECDC (European Center for Disease Prevention and Control), (3) Promotion of unity among citizens, Member States and between authorities: continuous commitment and communication with citizens take on greater importance since "isolation fatigue" threatens compliance with the measures of containment. Human behavior remains key to control of the pandemic, and the EC will strive to foster a sense of mutual obligation and unity.
ABSTRACT
From the early days of the pandemic policy analysts have been trying to understand what constitutes a resilient health systems response. This article takes stock of the national responses over the past ten months and distils strategies and general lessons for enhancing health systems resilience. Among health systems functions, effective governance, while not easy to pinpoint or secure, has been key to a resilient response, constituting a mortar binding everything else together. The pandemic has also highlighted the importance of solidarity, both within and between countries - bringing us to a realisation that we cannot be truly safe until everybody is safe. Over the course of the pandemic, the focus in studying resilience has broadened towards a more holistic recovery that extends beyond the health system.