Space and social distancing in managing and preventing COVID-19 community spread: An overview.

The spread of COVID-19 at a large scale and at a rapid pace indicates the lack of social distancing measures at multiple levels. The individuals are not to be blamed, nor should we assume the early measures were ineffective or not implemented. It is all down to the multiplicity of transmission factors that made the situation more complicated than initially anticipated.

Campus sustainability research: indicators and dimensions to consider for the design and assessment of a sustainable campus.

Assessment Tools have become the de facto method to address sustainability issues within the built environment. They provide a measurable third-party approach to ensuring sustainability design and directives are met through the use of indictors, criteria's and credit system. A key challenge is that the existing tools such as BREEAM Communities and LEED Neighbourhood Development address a wider community but cannot efficiently address the more nuanced and context specific sustainability requirements of campuses.

How does the COVID-19 fuel insomnia?

One of the leading health consequences of the pandemic is the prevalence of sleep-related issues, such as insomnia. Hence, this study highlights the relationship between COVID-19 and insomnia and how insomnia is increasing due to the pandemic. The study's findings summarise that the COVID-19 pandemic has produced ubiquitous mental challenges, including loneliness, anxiety, fear, stress, extreme tiredness, and health concerns.

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis.

With evidence-based measures, COVID-19 can be effectively controlled by advanced data analysis and prediction. However, while valuable insights are available, there is a shortage of robust and rigorous research on what factors shape COVID-19 transmissions at the city cluster level. Therefore, to bridge the research gap, we adopted a data-driven hierarchical modeling approach to identify the most influential factors in shaping COVID-19 transmissions across different Chinese cities and clusters.