The Lived Experience of Already-Lonely Older Adults During COVID-19.

BACKGROUND AND OBJECTIVES: From the outset of the coronavirus disease 2019 (COVID-19) pandemic, analysts warned that older populations, due to their age, chronic illnesses, and lack of technological facility, would suffer disproportionately from loneliness as they sheltered in place indefinitely. Several studies have recently been published on the impact of COVID-19-related loneliness among older populations, but little has been written about the experiences of already-lonely older individuals; those who had lived with persistent loneliness before the advent of COVID-19. This qualitative study sought to understand how already-lonely older individuals navigated and endured the social isolation of the pandemic. RESEARCH DESIGN AND METHODS: Twelve semistructured interviews were conducted with individuals aged 65 or older who scored a 6 or above on the 3-item UCLA Loneliness Risk screening tool. Interviews were coded using the constant comparative method. Themes and understandings of loneliness that reoccurred within and across interviews were identified and collected. RESULTS: Already-isolated older interviewees did not necessarily experience the abject loneliness hypothesized by analysts. Most interviewees used longstanding arrangements, in place to mitigate loneliness and endure social isolation, to manage the social deprivation of COVID-19. As a result, their loneliness did not compound during long bouts of mandated social isolation. To the contrary, loneliness during the pandemic appeared to carry a new valence for interviewees, as COVID-19 imbued their isolation with new meaning, rendering their loneliness necessary and responsible. DISCUSSION AND IMPLICATIONS: Exploring individuals' subjective perceptions of loneliness can help provide a deeper understanding of what it means to be isolated and alone during COVID-19 and aid in designing strategies to mitigate loneliness.

The COVID- 19 Impact on Health Administration Education: Understanding Student Perspectives on the Transition From In-Person to Remote Course Instruction

COVID-19 has infected millions of Americans. To combat the spread of the virus, state and local officials instituted social distancing guidelines that forced schools to shutter campuses and transition from in-person to remote learning. In this study, we examined health administration (HA) student perspectives on the transition from in-person to remote learning. We sought to understand how schools attempted to manage student concerns, how adaptations to remote learning were implemented, and what influences the transition had on student stress and anxiety. We used a mixed-methods study design that included (1) a survey of undergraduate and graduate students from six geographically diverse HA programs, and (2) a focus group with 6–10 students from each program. Our survey response rate was 52% (n =215). We found that students experienced five phases following the transition: grief, loss of engagement, fatigue, coping, and resilience. Focus groups also revealed stress and anxiety, as well as communication from leaders, as important themes. We present integrated survey and focus group findings, and supplement with exemplary quotes where applicable. We conclude by discussing a number of insights provided by HA students that may help guide program leadership and HA faculty who are teaching future remote courses.

A phase 1, randomized, placebo-controlled study to evaluate the safety and immunogenicity of an mRNA-based RSV prefusion F protein vaccine in healthy younger and older adults.

Respiratory Syncytial Virus (RSV) causes lower respiratory tract infections that can be severe and sometimes fatal. The risk for severe RSV infection is highest in infants and older adults. A safe and effective RSV vaccine for older adults represents a serious unmet medical need due to higher morbidity and mortality in this age group. In this randomized, partially double-blind, placebo-controlled, phase 1 dose-escalation study, we evaluated the safety, tolerability and immunogenicity of an investigational messenger ribonucleic acid (mRNA) vaccine encoding the RSV fusion protein (F) stabilized in the prefusion conformation. The study was conducted in healthy younger adults (ages ≥18 and ≤49 years) and healthy older adults (ages ≥60 and ≤79 years). Participants received mRNA-1777 (V171) or placebo as a single intramuscular dose. For each dose level, three sentinel participants were administered open-label mRNA-1777 (V171). Seventy-two younger adults were randomized and administered 25, 100, or 200 µg mRNA-1777 (V171) or placebo, and 107 older adults were randomized and administered 25, 100, 200 or 300 µg mRNA-1777 (V171) or placebo. Primary objectives were safety and tolerability and secondary objectives included humoral and cell-mediated immunogenicity. All dose levels of mRNA-1777 (V171) were generally well tolerated and no serious adverse events related to the vaccine were reported. Immunization with mRNA-1777 (V171) elicited a humoral immune response as measured by increases in RSV neutralizing antibody titers, serum antibody titers to RSV prefusion F protein, D25 competing antibody titers to RSV prefusion F protein, and cell-mediated immune responses to RSV-F peptides.

Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study.

Data privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward robust and generalizable machine learning systems. In the current COVID-19 pandemic, a major focus of artificial intelligence (AI) is interpreting chest CT, which can be readily used in the assessment and management of the disease. This paper demonstrates the feasibility of a federated learning method for detecting COVID-19 related CT abnormalities with external validation on patients from a multinational study. We recruited 132 patients from seven multinational different centers, with three internal hospitals from Hong Kong for training and testing, and four external, independent datasets from Mainland China and Germany, for validating model generalizability. We also conducted case studies on longitudinal scans for automated estimation of lesion burden for hospitalized COVID-19 patients. We explore the federated learning algorithms to develop a privacy-preserving AI model for COVID-19 medical image diagnosis with good generalization capability on unseen multinational datasets. Federated learning could provide an effective mechanism during pandemics to rapidly develop clinically useful AI across institutions and countries overcoming the burden of central aggregation of large amounts of sensitive data.

Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series.

OBJECTIVE: To characterize patients with coronavirus disease 2019 (covid-19) in a large New York City medical center and describe their clinical course across the emergency department, hospital wards, and intensive care units. DESIGN: Retrospective manual medical record review. SETTING: NewYork-Presbyterian/Columbia University Irving Medical Center, a quaternary care academic medical center in New York City. PARTICIPANTS: The first 1000 consecutive patients with a positive result on the reverse transcriptase polymerase chain reaction assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who presented to the emergency department or were admitted to hospital between 1 March and 5 April 2020. Patient data were manually abstracted from electronic medical records. MAIN OUTCOME MEASURES: Characterization of patients, including demographics, presenting symptoms, comorbidities on presentation, hospital course, time to intubation, complications, mortality, and disposition. RESULTS: Of the first 1000 patients, 150 presented to the emergency department, 614 were admitted to hospital (not intensive care units), and 236 were admitted or transferred to intensive care units. The most common presenting symptoms were cough (732/1000), fever (728/1000), and dyspnea (631/1000). Patients in hospital, particularly those treated in intensive care units, often had baseline comorbidities including hypertension, diabetes, and obesity. Patients admitted to intensive care units were older, predominantly male (158/236, 66.9%), and had long lengths of stay (median 23 days, interquartile range 12-32 days); 78.0% (184/236) developed acute kidney injury and 35.2% (83/236) needed dialysis. Only 4.4% (6/136) of patients who required mechanical ventilation were first intubated more than 14 days after symptom onset. Time to intubation from symptom onset had a bimodal distribution, with modes at three to four days, and at nine days. As of 30 April, 90 patients remained in hospital and 211 had died in hospital. CONCLUSIONS: Patients admitted to hospital with covid-19 at this medical center faced major morbidity and mortality, with high rates of acute kidney injury and inpatient dialysis, prolonged intubations, and a bimodal distribution of time to intubation from symptom onset.