Interesting study from Cornell published in July:
Abstract:
This paper juxtaposes existing public policies and different planning paradigms with evidence from the first wave of the COVID-19 pandemic in New York City (NYC). Zip code tabulation area (ZCTA) data for NYC are used to address four main questions: (1) How do urban density and crowding affect infection rates? (2) How does the commuting environment relate to pandemic resilience? (3) How does the allocation of points of interest within a city impact the infection rate? (4) How do evident inequalities in a city influence vulnerability during a pandemic? The presented evidence is used to demonstrate that compact, well-mixed, and decentralized cities can increase pandemic resilience due to advantageous features such as short commute times and well-distributed points of interest. At the architectural level, more resilient apartment building typologies need to be developed to mitigate the ramifications of overcrowding. This analysis also reveals significant spatial disparities and how they disproportionally affect the pandemic risk of the vulnerable communities. These findings warrant a broader discussion on how urban design and planning can mitigate inequalities and transform cities into a resilient, inclusive, and sustainable urban environment.
A few excerpts:
The final MLR model in P3 shows the highest adjusted R2 value (0.646; p < 0.001), suggesting that the residential building density, building-level crowding, work commute time by public transit, reduced turnstile usage, and park area per capita could contribute at least 64.6% to the variation of the COVID-19 daily case rate during the NYC lockdown period.
Building-level crowding appears to be an unfavorable urban feature in almost all phases in the pandemic, probably because many residents sharing the confined circulation space and facilities in buildings (e.g. elevators and hallways) can facilitate disease transmissions. Room-level crowding also appears to seed the surge of the infection in vulnerable communities such as The Bronx according to the present case study. However, statistical evidence is needed in future studies for a more profound understanding about the effects of these crowding indicators and their potential interaction with other factors such as income and age (Ghosh et al. 2021).
Based on the presented evidence, it is proposed that a pandemic-resilient urban environment includes, notably, compact and mixed cities with decentralized urban activities, adequate affordable dwellings, resilient building typologies, good proximities between jobs and homes, restricted commute time, diverse mode choices, and balanced allocations of urban services and facilities in line with the residential density.
Link to the full study:
https://journal-buildingscities.org/articles/10.5334/bc.130/#B17
Poll
