Characterizing personalized effects of family information on disease risk using graph representation learning

Family history is considered a risk factor for many diseases because it implicitly captures shared genetic, environmental and lifestyle factors. A nationwide electronic health record (EHR) system spanning multiple generations presents new opportunities for studying a connected network of medical histories for entire families. In this work we present a graph-based deep learning approach for learning explainable, supervised representations of how each family member's longitudinal medical history influences a patient's disease risk. We demonstrate that this approach is beneficial for predicting 10-year disease onset for 5 complex disease phenotypes, compared to clinically-inspired and deep learning baselines for a nationwide EHR system comprising 7 million individuals with up to third-degree relatives. Through the use of graph explainability techniques, we illustrate that a graph-based approach enables more personalized modeling of family information and disease risk by identifying important relatives and features for prediction

Coping with Coping:International migrants’ experiences of the Covid-19 lockdown in the UK

Globally, policymakers have overlooked the challenges faced by international migrants in host countries during the Covid-19 pandemic. The policies and support systems designed by host governments highlight the lack of social justice and raise concerns for scholarly attention. Considering the experiences of international migrants living in the UK during the Covid-19 lockdown from the theoretical perspective of coping, this interpretivist study investigates international migrants’ coping strategies adopted during the first UK national lockdown. Data collected from 60 Chinese, Italian and Iranian migrants using semi-structured interviews during the lockdown period were analysed thematically using NVivo. The findings show that migrants adopted multi-layered and multi-phase coping strategies. To cope with the anxiety and uncertainties caused by the pandemic, they initiated new practices informed by both home and host institution logics. Nevertheless, the hostile context's responses provoked unexpected new worries and triggered the adoption of additional and compromising practices. The paper illustrates how coping became paradoxical because migrants had to cope with the hostile reactions that their initial coping strategies provoked in the host environment. By introducing the new concept of coping with coping, this paper extends previous theoretical debate and leads to several managerial implications for governments and policymakers.</p