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1.
Front Public Health ; 10: 926872, 2022.
Article in English | MEDLINE | ID: covidwho-2230616

ABSTRACT

Aims: The transport of patients suspected of having COVID-19 requires careful consideration. Using paths selected at random and not accounting for person flow along the path are risk factors for infection spread. Intrahospital transportation (IHT) protocols and guidelines should be used to help reduce the risk of secondary virus transmission during transport. This study aimed to propose optimal IHT for patients with an infectious disease presenting in an out-patient area. Design: The map of a West China Hospital was used. We also used field investigation findings and simulated person flow to establish pathway length and transportation time. We identified three optimum pathways and estimated safety boundary marks, including a patient transportation border (PTB) and safety transportation border (STB). Finally, IHT, PTB, and STP formed a virtual transport pipeline (VTP) and a traceable IHT management system, which can generate a virtual isolation space. Results: The three pathways met efficiency, accessibility, and by-stander flow criteria. No facility characteristic modification was required. Conclusions: Using virtual models to identify pathways through out-patient hospital areas may help reduce the risk of infection spread.


Subject(s)
COVID-19 , Communicable Diseases , Humans , Transportation of Patients/methods , COVID-19/epidemiology , Transportation , Risk Factors , Communicable Diseases/epidemiology
2.
Front Public Health ; 10: 883177, 2022.
Article in English | MEDLINE | ID: covidwho-1847243

ABSTRACT

The lack of physical activity has become a rigorous challenge for many countries, and the relationship between physical activity and the built environment has become a hot research topic in recent decades. This study uses the Strava Heatmap (novel crowdsourced data) to extract the distribution of cycling and running tracks in central Chengdu in December 2021 (during the COVID-19 pandemic) and develops spatial regression models for numerous 500 × 500 m grids (N = 2,788) to assess the impacts of the built environment on the cycling and running intensity indices. The findings are summarized as follows. First, land-use mix has insignificant effects on the physical activity of residents, which largely contrasts with the evidence gathered from previous studies. Second, road density, water area, green space area, number of stadiums, and number of enterprises significantly facilitate cycling and running. Third, river line length and the light index have positive associations with running but not with cycling. Fourth, housing price is positively correlated with cycling and running. Fifth, schools seem to discourage these two types of physical activities during the COVID-19 pandemic. This study provides practical implications (e.g., green space planning and public space management) for urban planners, practitioners, and policymakers.


Subject(s)
COVID-19 , Crowdsourcing , Built Environment , COVID-19/epidemiology , China , Environment Design , Exercise , Humans , Pandemics
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