Exploring the determinants of synergetic development of social organizations participating in home-based elderly care service: An SEM method

Smart transition pathways and development incentive mechanism of China's smart community elderly care industry under market dominance: Considering a multi-subjective behavior game

Against the backdrop of an aging population, China is actively experimenting with an innovative elderly care model, so smart community elderly care has recently received widespread attention. However, the results of the implementation of the model have not yet met the expectation due to the variety of interests among the relevant participants. In this study, we identified the most core stakeholders in smart community elderly care, developed a four-party evolutionary game model including local governments, communities, service supply enterprises and households with elderly members. By applying the system dynamics method, we simulate the evolutionary paths and explore the complex interactions at the multiparticipant level in order to facilitate the transition of community elderly care services from traditional to smart, and then propose managerial insights for accelerating the construction of smart community elderly care. The results suggest that: (1) the four players in the game influence each other and are intimately related, and the benign interaction between them will further stimulate the vitality of the smart community elderly care industry; (2) appropriate improvement in policy support will strongly promote smart community elderly care, and the incentive effect on the demand side (households with elderly members) is more significant; (3) when households' preference for smart services increases, and the perceived value to communities and enterprises reaches a certain threshold, communities and enterprises will actively adopt smart solution and technology as well as develop stable portfolio strategy; (4) measures such as simultaneously increasing the level of smart and resource synergy will promote the system evolution toward smart services, and the system is more sensitive to the internal behavior of the enterprise than the external behavior between community and enterprise.

Association of history of cerebrovascular disease with severity of COVID-19

OBJECTIVE

To determine whether a history of cerebrovascular disease (CVD) increases risk of severe coronavirus disease 2019 (COVID-19).

METHODS

In a retrospective multicenter study, we retrieved individual data from in-patients treated March 1 to April 15, 2020 from COVID-19 registries of three hospitals in Saxony, Germany. We also performed a systematic review and meta-analysis following PRISMA recommendations using PubMed, EMBASE, Cochrane Library databases and bibliographies of identified papers (last search on April 11, 2020) and pooled data with those deriving from our multicenter study. Of 3762 records identified, 11 eligible observational studies of laboratory-confirmed COVID-19 patients were included in quantitative data synthesis. Risk ratios (RR) of severe COVID-19 according to history of CVD were pooled using DerSimonian and Laird random effects model. Between-study heterogeneity was assessed using Cochran's Q and I2-statistics. Severity of COVID-19 according to definitions applied in included studies was the main outcome. Sensitivity analyses were conducted for clusters of studies with equal definitions of severity.

RESULTS

Pooled analysis included data from 1906 laboratory-confirmed COVID-19 patients (43.9% females, median age ranging from 39 to 76 years). Patients with previous CVD had higher risk of severe COVID-19 than those without [RR 2.07, 95% confidence interval (CI) 1.52-2.81; p < 0.0001]. This association was also observed in clusters of studies that defined severe manifestation of the disease by clinical parameters (RR 1.44, 95% CI 1.22-1.71; p < 0.0001), necessity of intensive care (RR 2.79, 95% CI 1.83-4.24; p < 0.0001) and in-hospital death (RR 2.18, 95% CI 1.75-2.7; p < 0.0001).

CONCLUSION

A history of CVD might constitute an important risk factor of unfavorable clinical course of COVID-19  suggesting a need of tailored infection prevention and clinical management strategies for this population at risk.