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The author’s research reviewed herein was supported by Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP; grant Nos. 12/03831-8, 16/04921-1 & 18/03418-0).

Joseph Sonnabend, a pioneering figure in the early effort to confront the multiple dimensions of the AIDS epidemic in the United States, died January 24, 2021, at the age of 88. A lengthy and admiring obituary published in the New York Times said of him that he was "one of the most important figures in the fight against AIDS, if also one of the most unheralded."1(pD6) In the current moment, when the language of heroism is routinely employed in describing the work of medical workers struggling to control COVID-19, it is sometimes difficult to recall that the life and work of those regarded as AIDS pioneers were all too often tinged by recrimination and bitter controversy. Such was the career of Sonnabend, someone who saw himself and was viewed by others as a devoted clinician and a combative iconoclast. (Am J Public Health. Published online ahead of print June 10, 2021: e1-e3. https://doi.org/10.2105/AJPH.2021.306291).

Abstract: The COVID-19 pandemic and related physical distancing measures have disproportionally affected older adults living alone due to their greater social isolation. Unlike previous studies on the subject, the current research recognizes the diversity amongst older adults living alone by considering the impact of marital history. Combining information from Wave 8 of the Survey of Health Ageing and Retirement (SHARE), with data of SHARELIFE and the SHARE Corona survey, we investigated the differential impact of the COVID-19 pandemic on loneliness in older men (N = 1504) and women (N = 4822) living alone. Logistic multilevel analyses were performed on data from 26 European countries and Israel. For men, we found that the short-term widowed were more likely to report increased loneliness than the medium- and long-term widowed and those living apart together (LAT). For women, the results indicated that the short- and medium-term widowed and the divorced were at greater risk for increased loneliness than those in a LAT relationship. Also, medium-term widowed women were more likely to report increased loneliness than their long-term widowed counterparts. The three hypothesized underlying mechanisms – i.e., (i) the opportunity mechanism, (ii) the expectation mechanism, and (iii) the vulnerability mechanism – only played a small role in explaining the observed differences. In sum, our study highlights the importance of recognizing the diversity within the group of older adults living alone when investigating the effects of the pandemic on loneliness, yet the mechanisms behind the stratifying role of marital history are not fully understood.

Patients experience various symptoms when they haveeither acute or chronic diseases or undergo some treatments for diseases. Symptoms are often indicators of the severity of the disease and the need for hospitalization. Symptoms are often described in free text written as clinical notes in the Electronic Health Records (EHR) and are not integrated with other clinical factors for disease prediction and healthcare outcome management. In this research, we propose a novel deep language model to extract patient-reported symptoms from clinical text. The deep language model integrates syntactic and semantic analysis for symptom extraction and identifies the actual symptoms reported by patients and conditional or negation symptoms. The deep language model can extract both complex and straightforward symptom expressions. We used a real-world clinical notes dataset to evaluate our model and demonstrated that our model achieves superior performance compared to three other state-of-the-art symptom extraction models. We extensively analyzed our model to illustrate its effectiveness by examining each component's contribution to the model. Finally, we applied our model on a COVID-19 tweets data set to extract COVID-19 symptoms. The results show that our model can identify all the symptoms suggested by the Center for Disease Control (CDC) ahead of their timeline and many rare symptoms.

Space is critical in teacher education because it shapes and is shaped by different aspects of teacher learning. This study examines how a group of language teacher educators and student-teachers understood space and the effects of that understanding on their practices and conceptions before, during, and after Covid-19 restrictions. Set in Argentina, the study collected data by means of walking interviews, drawings, photos, and follow-up interviews. Qualitative content analysis shows that space and matter can exert a powerful influence on educational trajectories as they affect educational actors’ wellbeing, perceptions, and practices. The study proposes a model of spatiality of language teacher education.