Elderly mobility during the COVID-19 pandemic: A qualitative exploration in Kunming, China

Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition

“…Similarly, the spread of COVID-19 decelerated the people’s trips of automobiles, public transits and air transportations Chang et al, 2021, Kim et al, 2021, Li et al, 2021, van Wee Witlox, 2021, Wang et al (2021), and modified their way of deciding their trips (Balbontin et al, 2021; Beck et al, 2021; Borkowski et al, 2021). The correlation between prevalence of the disease and local socio-economic conditions and turned out to indicate asymmetries in the level of urbanization, the population pyramid, racial distribution, and their political orientation [22] , [23] .…”

“…The higher the median age, the more successful was the practice of reducing trips or social distancing according to the spread of diseases. The elderly people considerably reduced their trips during the COVID-19 pandemic, as they are thought to be one of the most susceptible populations [22] . This is also comparable to the results from [3] that a higher proportions of the 40 to 65 age groups are more likely to reduce more trips than the 0 to 24 age group.…”

COVID-19 Adaptive Interventions: Implications for Wellbeing and Quality-of-Life

“…Another group of the society which has been significantly impacted are elderly populations ( Patel and Clark-Ginsberg, 2020 ). Many governments strongly discouraged elderly mobility during the COVID-19 which could have contributed to higher levels of loneliness and depression impacting on their quality of life ( Liu et al, 2021 ). The COVID-19 traumatic event continues to add pressure on the healthcare systems demanding that we find additional and complementary means of support for those in need.…”

Smartphone-based services, perceived accessibility, and transport inequity during the COVID-19 pandemic: A cross-lagged panel study

“…More specifically, the discussion and empirical evidence on transport equity issues can be roughly categorised into four groups: transport poverty, transport disadvantage, accessibility, and transport-related social exclusion (e.g., Levine, 2020 , Lucas, 2012 , Lucas, 2019 , Mattioli et al, 2017 ). A great deal of research on transport equity focuses on measuring the spatial distribution of accessibility to activities and opportunities (e.g., Chang et al, 2019 , Liu et al, 2018 , Rietveld, 2000 ); however, a previous study discussing elderly mobility during the COVID-19 pandemic in China revealed that vulnerable groups who suffered from food deprivation, loneliness, and depression due to containment measures had to travel for activities whilst better-off groups stayed at home because they could acquire daily necessities and fulfil the demand for social interactions via smartphone-based services ( Liu et al, 2021 ). Measured objectively, activities were accessible to disadvantaged groups who were actually more excluded and marginalised by the containment measures because they suffered the risks of infection, extensive social pressure, and various other burdens while walking outdoors.…”

“…With the increasing use of smartphone-based services, it is no longer necessary for some people to access certain services by conducting trips by themselves. It is noticeable that wealthier or more technology-savvy people had a very high level of accessibility to services without leaving their home whilst disadvantaged groups had to travel to access such services in the first few weeks of the COVID-19 outbreak ( Liu et al, 2021 ). Similar results were found without the impact of the pandemic.…”