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. 2021 Feb 3;67:102752. doi: 10.1016/j.scs.2021.102752

Table 1.

Major references about the association of the BE attributes with the spread of COVID-19.

Source BE Attributes Analysis method Scale Major findings related to the present study
Nguyen et al., 2020 Presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires Google Street View (GSV) images and computer vision; Poisson regression models 164 million images
in the USA
Indicators of mixed land use (non-single-family home), walkability (sidewalks) and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were associated with fewer COVID-19 cases.
Hamidi et al., 2020a Metropolitan population, activity density (population & employment per square mile), ICU beds per 10,000 population, primary care physicians per 10,000 population Multi-level linear model 1165 metropolitan counties in the USA Larger metropolitan areas lead to significantly higher COVID-19 infection rates and higher mortality rates
Lee et al., 2020 Traffic volumes on roads Single linear regression 6307 vehicle detection systems (VDS) in South Korea In Incheon there was a positive, but insignificant, linear relationship between the increasing numbers of newly confirmed cases and increasing traffic.
Ghosh et al., 2020 Travel distance to London, population density Mixed-effects model Distance from London to four other cities (Birmingham, Leeds, Manchester and Sheffield) As the distance from London increases, the number of COVID-19 cases decreases.
Mizumoto & Chowell, 2020 Occupant density on the Diamond Princess cruise ship Mathematical modeling 621epidemiological incidence cases The increased exposure risks associated with high occupant density were demonstrated in the COVID-19 outbreak that occurred on the ship.
Emeruwa et al. 2020 Building-level variables, including the number of residential units per building and mean assessed value (per square foot), and neighborhood-level variables, including population density, household membership (persons per household) and household crowding. Bivariable logistic Regression model 71 infected cases in New York COVID-19 transmission among pregnant women was associated with neighborhood- and building-level markers of large household membership and household crowding.
Dai & Zhao, 2020 Ventilation rate Wells–Riley equation Typical scenarios, including offices, classrooms, buses and aircraft cabins. An infection probability of less than 1% requires a ventilation rate larger than 100–350 m3/h per infector and 1200–4000 m3/h per infector for 0.25 h and 3 h of exposure.
Antony, Velray & Fariborz, 2020 Population density, climate severity, the volume of indoor spaces and air-conditioning usage Statistical analysis of correlations Various states in India Fast drying and size reduction of respiratory droplets makes the virus more active.
Auger, Shah & Richardson, 2020 Schools Population-based time series analysis All USA states School closure was associated with a significant decline in the incidence of COVID-19 and mortality.
Brown et al. 2020 Nursing homes crowding Population-based retrospective cohort study 78,000 residents of 618 distinct nursing homes in Ontario, Canada Crowding in nursing homes was associated with a higher incidence of COVID-19 infection and mortality.
Hamidi et al., 2020b County activity density and metropolitan area population Structural equation model 913 metropolitan counties in the USA Metropolitan population is one of the most significant predictors of infection rates; larger metropolitan areas have higher infection and higher mortality rates.