To review the impact of social isolation during COVID-19 pandemic on mental and physical health of older people and the recommendations for patients, caregivers and health professionals. Narrative review. Non-institutionalized community-living people. 20.069 individuals from ten descriptive cross-sectional papers. Articles since 2019 to 2020 published on Pubmed, Scielo and Google Scholar databases with the following MeSh terms (‘COVID-19’, ‘coronavirus’, ‘aging’, ‘older people’, ‘elderly’, ‘social isolation’ and ‘quarantine’) in English, Spanish or Portuguese were included. The studies not including people over 60 were excluded. Guidelines, recommendations, and update documents from different international organizations related to mental and physical activity were also analysed. 41 documents have been included in this narrative review, involving a total of 20.069 individuals (58% women), from Asia, Europe and America. 31 articles included recommendations and 10 addressed the impact of social distancing on mental or physical health. The main outcomes reported were anxiety, depression, poor sleep quality and physical inactivity during the isolation period. Cognitive strategies and increasing physical activity levels using apps, online videos, telehealth, are the main international recommendations. Mental and physical health in older people are negatively affected during the social distancing for COVID-19. Therefore, a multicomponent program with exercise and psychological strategies are highly recommended for this population during the confinement. Future investigations are necessary in this field.

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Impact of Social Isolation Due to COVID-19 on Health in Older People: Mental and Physical Effects and Recommendations

As the novel coronavirus disease 2019 (COVID-19) continues to spread across countries, the need for innovative measures to provide high-quality patient care and manage its spread has become more imperative. Software-based systems such as medical software applications could provide valuable suggestion on health-related information to physicians towards improving quality of life, especially for outpatients (e.g., elderly, immunosuppressed, pregnant women). The use of telemedicine and virtual software offers promising potential in the fight against COVID-19. Accordingly, by means of expedited literature and document review, this paper provides implication on the opportunities, application, and challenges of telemedicine and existing virtual software currently adopted as suitable initiatives for reducing the spread of COVID-19. More importantly, findings present factors that impact adoption of telemedicine. The findings suggest that telemedicine and virtual software are capable of decreasing emergency room visits, safeguarding healthcare resources, and lessening the spread of COVID-19 by remotely treating patients during and after the COVID-19 pandemic.

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Exploring the adoption of telemedicine and virtual software for care of outpatients during and after COVID-19 pandemic.

Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world and has become one of the most acute and severe ailments in the past hundred years. The prevalence rate of COVID-19 is rapidly rising every day throughout the globe. Although no vaccines for this pandemic have been discovered yet, deep learning techniques proved themselves to be a powerful tool in the arsenal used by clinicians for the automatic diagnosis of COVID-19. This paper aims to overview the recently developed systems based on deep learning techniques using different medical imaging modalities like Computer Tomography (CT) and X-ray. This review specifically discusses the systems developed for COVID-19 diagnosis using deep learning techniques and provides insights on well-known data sets used to train these networks. It also highlights the data partitioning techniques and various performance measures developed by researchers in this field. A taxonomy is drawn to categorize the recent works for proper insight. Finally, we conclude by addressing the challenges associated with the use of deep learning methods for COVID-19 detection and probable future trends in this research area. The aim of this paper is to facilitate experts (medical or otherwise) and technicians in understanding the ways deep learning techniques are used in this regard and how they can be potentially further utilized to combat the outbreak of COVID-19.

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A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)

Coronavirus disease 2019 (COVID-19) is the second pandemic of the twenty-first century, with over one-hundred million infections and over two million deaths to date. It is a novel strain from the Coronaviridae family, named Severe Acute Respiratory Distress Syndrome Coronavirus-2 (SARS-CoV-2); the 7th known member of the coronavirus family to cause disease in humans, notably following the Middle East Respiratory syndrome (MERS), and Severe Acute Respiratory Distress Syndrome (SARS). The most characteristic feature of this single-stranded RNA molecule includes the spike glycoprotein on its surface. Most patients with COVID-19, of which the elderly and immunocompromised are most at risk, complain of flu-like symptoms, including dry cough and headache. The most common complications include pneumonia, acute respiratory distress syndrome, septic shock, and cardiovascular manifestations. Transmission of SARS-CoV-2 is mainly via respiratory droplets, either directly from the air when an infected patient coughs or sneezes, or in the form of fomites on surfaces. Maintaining hand-hygiene, social distancing, and personal protective equipment (i.e., masks) remain the most effective precautions. Patient management includes supportive care and anticoagulative measures, with a focus on maintaining respiratory function. Therapy with dexamethasone, remdesivir, and tocilizumab appear to be most promising to date, with hydroxychloroquine, lopinavir, ritonavir, and interferons falling out of favour. Additionally, accelerated vaccination efforts have taken place internationally, with several promising vaccinations being mass deployed. In response to the COVID-19 pandemic, countries and stakeholders have taken varying precautions to combat and contain the spread of the virus and dampen its collateral economic damage. This review paper aims to synthesize the impact of the virus on a global, micro to macro scale.

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COVID-19: breaking down a global health crisis.

Background: The COVID-19 pandemic has drastically changed the lives of countless members of the general population. Older adults are known to experience loneliness, age discrimination, and excessive worry. It is therefore reasonable to anticipate that they would experience greater negative outcomes related to the COVID-19 pandemic given their increased isolation and risk for complications than younger adults. Objective: This study aims to synthesize the existing research on the impact of the COVID-19 pandemic, and associated isolation and protective measures, on older adults. The secondary objective is to investigate the impact of the COVID-19 pandemic, and associated isolation and protective measures, on older adults with Alzheimer disease and related dementias. Methods: A rapid review of the published literature was conducted on October 6, 2020, through a search of 6 online databases to synthesize results from published original studies regarding the impact of the COVID-19 pandemic on older adults. The Human Development Model conceptual framework–Disability Creation Process was used to describe and understand interactions between personal factors, environmental factors, and life habits. Methods and results are reported following the Preferred Reporting Items for Systematic Reviews and Meta-analyses Statement. Results: A total of 135 records were included from the initial search strategy of 13,452 individual studies. Of these, 113 (83.7%) studies were determined to be of level 4 according to the levels of evidence classification by the Centre for Evidence-Based Medicine. The presence of psychological symptoms, exacerbation of ageism, and physical deterioration of aged populations were reported in the included studies. Decreased social life and fewer in-person social interactions reported during the COVID-19 pandemic were occasionally associated with reduced quality of life and increased depression. Difficulties accessing services, sleep disturbances, and a reduction of physical activity were also noted. Conclusions: Our results highlight the need for adequate isolation and protective measures. Older adults represent a heterogeneous group, which could explain the contradictory results found in the literature. Individual, organizational, and institutional strategies should be established to ensure that older adults are able to maintain social contacts, preserve family ties, and maintain the ability to give or receive help during the current pandemic. Future studies should focus on specific consequences and needs of more at-risk older adults to ensure their inclusion, both in public health recommendations and considerations made by policy makers.

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Impact of the COVID-19 Pandemic on Older Adults: Rapid Review.

The maintenance of well-being, healthcare, and social connection is crucial for older adults (OA) and has become a topic of debate as much of the world faces lockdown during the coronavirus disease 2019 (COVID-19) pandemic. OAs have been advised to isolate themselves because they are at higher risk for developing serious complications from severe acute respiratory syndrome coronavirus. Additionally, nursing homes and assisted-living facilities across the country have closed their doors to visitors to protect their residents. Mobile technology such as applications (apps) could provide a valuable tool to help families stay connected, and to help OAs maintain mobility and link them to resources that encourage physical and mental well-being. Apps could address cognitive, visual, and hearing impairments. Our objective was to narratively summarize 15 apps that address physical and cognitive limitations and have the potential to improve OAs' quality of life, especially during social distancing or self-quarantine.

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15 Smartphone Apps for Older Adults to Use While in Isolation During the COVID-19 Pandemic.

Rural communities with predominantly older adult populations could be especially vulnerable to poor outcomes from COVID-19 due to lacking intensive care unit (ICU) capacity. Our objective is to des...

https://journals.sagepub.com/doi/pdf/10.1177/2333721420936168

Rural America’s Hospitals are Not Prepared to Protect Older Adults From a Surge in COVID-19 Cases

Background: Falls are a common problem among older adults that lead to injury, emergency department (ED) visits, and institutionalization. The Apple Watch can detect falls and alert caregivers and clinicians that help is needed; the device could also be used to objectively collect data on gait, fitness, and falls as part of clinical trials. However, little is known about the ease of use of this technology among older adult ED patients, a population at high risk of recurrent falls. Objective: The goal of this study—the Geriatric Acute and Post-Acute Fall Prevention Intervention (GAPcare) II—is to examine the feasibility, acceptability, and usability of the Apple Watch Series 4 paired with the iPhone and our research app Rhode Island FitTest (RIFitTest) among older adult ED patients seeking care for falls. Methods: We will conduct field-testing with older adult ED patients (n=25) who sustained a fall and their caregivers (n=5) to determine whether they can use the Apple Watch, iPhone, and app either (1) continuously or (2) periodically, with or without telephone assistance from the research staff, to assess gait, fitness, and/or falls over time. During the initial encounter, participants will receive training in the Apple Watch, iPhone, and our research app. They will receive an illustrated training manual and a number to call if they have questions about the research protocol or device usage. Participants will complete surveys and cognitive and motor assessments on the app during the study period. At the conclusion of the study, we will solicit participant feedback through semistructured interviews. Qualitative data will be summarized using framework matrix analyses. Sensor and survey response data will be analyzed using descriptive statistics. Results: Recruitment began in December 2019 and was on pause from April 2020 until September 2020 due to the COVID-19 pandemic. Study recruitment will continue until 30 participants are enrolled. This study has been approved by the Rhode Island Hospital Institutional Review Board (approval 1400781-16). Conclusions: GAPcare II will provide insights into the feasibility, acceptability, and usability of the Apple Watch, iPhone, and the RIFitTest app in the population most likely to benefit from the technology: older adults at high risk of recurrent falls. In the future, wearables could be used as part of fall prevention interventions to prevent injury before it occurs. Clinical Trial: ClinicalTrials.gov NCT04304495; https://clinicaltrials.gov/ct2/show/NCT04304495

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The Geriatric Acute and Post-Acute Fall Prevention Intervention (GAPcare) II to Assess the Use of the Apple Watch in Older Emergency Department Patients With Falls: Protocol for a Mixed Methods Study.

Margaret Healy

Papers

15 Smartphone Apps for Older Adults to Use While in Isolation During the COVID-19 Pandemic.

Rural America’s Hospitals are Not Prepared to Protect Older Adults From a Surge in COVID-19 Cases

The Geriatric Acute and Post-Acute Fall Prevention Intervention (GAPcare) II to Assess the Use of the Apple Watch in Older Emergency Department Patients With Falls: Protocol for a Mixed Methods Study.