How COVID-19 Affects the Willingness of the Elderly to Continue to Use the Online Health Community: A Longitudinal Survey

In response to the COVID-19 outbreak, the governments of different countries adopted restrictions, such as locking down cities and restricting travel and social contact. Online health communities (OHCs) with specialized physicians have become an important way for the elderly to access health information and social support, which has expanded their use since the outbreak. This paper examines the factors influencing elderly people's behavior in terms of the continuous use of OHCs from a social support perspective to understand the impact of public health emergencies. Research collected data from March to April 2019, February 2020, and August 2021 in China. A total of 189 samples were collected and analyzed by using SmartPLS. The results show that (1) social support to the elderly during different stages has different influences on their sense of community and (2) the influence of the sense of community on the intention to continuously use OHCs also seems to change over time. The results of this study provide important implications for research and practice related to both OHCs and COVID-19. © 2022 IGI Global. All rights reserved.

The COVID-19 pandemic and life expectancy among older adults in Asian countries

Millions of lives in Asia were lost in the ongoing COVID-19 pandemic, causing a reduction of 1.66 years in life expectancy at birth (e0) in 2019–2021 and a reduction of 1.41 years in life expectancy at age 60 (e60). Using the World Population Prospects 2022, we decomposed mortality changes at older ages (ages 60+) that contributed to Asia's reduction in e0 and e60. Overall, changes in mortality at older ages contributed to more than 70 per cent of reduction in e0 for all its subregions, except Eastern Asia (<37 per cent), and changes in mortality at oldest-old ages (80+) led to a reduction in e60 by 25 per cent. The sex difference in reduction of e60 varied across Asian countries, despite a similar pattern across subregions. These findings helped us understand the impacts of the COVID-19 pandemic on human mortality and the large variations across subregions and countries, which could have important policy implications. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

[Application of combined detection of multiple pathogens in diagnosis and treatment of coronavirus disease 2019].

Due to the wide variety of pathogens causing respiratory tract infection and the close symptoms, coronavirus disease 2019 (COVID-19) needs to be differentiated from other common infections. Early comprehensive detection and accurate identification of respiratory infection pathogens is of great value for early diagnosis, curative effect, as well as monitor of the diseases. Combined detection of multiple pathogens can quickly and accurately detect and distinguish the pathogens, then provide rapid and reliable laboratory diagnostic basis for further treatment. This article elaborates the application and development of multiplex detection assay in the diagnosis of COVID-19 according to the recent research.

Associations With Virtual Visit Use Among Patients Receiving Radiation Therapy

To test for associations in virtual visit use among radiation oncology patients. Using the electronic medical record, we extracted encounter data and corresponding patient information the 6 months prior to and 6 months of COVID-enabled virtual visits (10/1/2019-3/22/2020 versus 3/23/2020-9/1/2020) at a large tertiary cancer center. Encounters during COVID were categorized as in-person or virtual visits. Descriptive and univariate analysis was conducted on the characteristics of patient populations during the pre-COVID period to establish baseline demographics and compare to the during COVID period. Examined demographic variables included race, ethnicity, age, sex, marital status, preferred language, insurance status and tumor characteristics including disease site. Univariate and multivariable (MVA) logistic regression examined patient demographic and disease characteristics associated with virtual visit use. We analyzed 4,974 total encounters, (2,287 pre-COVID and 2,687 during COVID), among 3,960 total patients. All (100%) pre-COVID encounters were in-person whereas during COVID, 21% of encounters were via virtual visits. Overall, there were no differences identified in pre- versus during COVID patient characteristics. However, we found significant differences in patient characteristics for in-person versus virtual encounters during COVID. On MVA, virtual visit use was less common among patients of minority race (white n = 321 versus black n = 100 and other n = 35, OR 0.73, 95% CI 0.57-0.94, P = 0.014) and not married (OR 0.78, 95% CI 0.61-1.00, P = 0.048). Patients diagnosed with head and neck (OR 0.64, 95% CI 0.42-0.96, P = 0.030), breast (OR 0.35, 95% CI 0.20-0.60, P = < 0.001), GI/abdominal (OR 0.31, 95% CI 0.16-0.62, P = 0.001) or hematologic malignancy (OR 0.18, 95% CI 0.04-0.84, P = 0.029), were less likely to use virtual visits relative to patients with genitourinary malignancy. While the patient populations were similar prior to and during COVID, when controlling for available variables, we found significant differences in virtual visit use by patient characteristics, including race and marital status as well as disease characteristics. Further study is needed to elucidate additional factors that underlie these differences in virtual visit utilization;health equity should be considered when implementing virtual visits. Our findings raise the hypothesis that vulnerable patient groups may benefit from additional interventions and outreach to enable equitable access. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Radiation Oncology, Biology, Physics is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Covid-19 detection using disease monitoring systems based on vital-signs from smartwatch

Real-Time vital-sign from patients are important information that implies the current health status and behavior of patients. Recently, Mishra et al. [1] have shown that COVID-19 can be detected by analyzing the patient's vital signs and behaviors, i.e., heart rates and steps, using anomaly detection techniques. This paper presents a medical IoT platform, called MiT Eco-platform, which is designed to gather patient's physiological data through a smartwatch and to increase the efficiency of data labeling for building an AI model for medical diagnosis and treatment. Furthermore, we present a real-time COVID-19 detection approach advanced from the approach of using anomaly detection Mishra et al. [1] that will be run on MiT Eco-platform. As a result, we show performance evaluation results of preemptively detecting the COVID-19 infection for the same samples of the COVID-19 infected ones of Mishra et al.[1], comparing with the anomaly detection approach of Mishra et al.[1]. We expect that physiological data through smartwatches on daily life can be continuously gathered and effectively labeled by the MiT Eco-platform for various studies in medical area. © 2021 Korean Institute of Electrical Engineers. All rights reserved.

Does the stringency of government interventions for COVID19 reduce the negative impact on market growth? Evidence from Pacific and South Asia

The objective of this study is to empirically assess the effect of government decisions on market growth in response to social distancing initiatives, government reactions, economic support provision, and containment and health responses, to name a few. A panel dataset of daily stock market returns is analysed in this study, changes in COVID-19 cases, and government responses to 17 countries in the Pacific and South Asia from 1st January 2020 to 31st December 2020. Findings indicate that social distancing policies have a significant negative effect on stock returns but a substantial positive impact on market growth when new cases' growth rate declines after accounting for country characteristics and systematic risk due to foreign factors. A direct negative effect is seen almost immediately, and a subsequently indirect positive effect is noted. As expected, policies regarding social distancing have an immediate negative impact, attributed mainly to the expected negative effect on economic activity. Subsequently, we see an indirect positive effect on market return because social distancing measures reduced the growth of confirmed COVID-19 cases. Both awareness, containment, and health index (ACHI) and Income Support and Debt Relief Index (ISDRI) positively affect market growth, as they are perceived to support individuals' socio-economic well-being and mainly result in positive market returns. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.