Problem, research strategy, and findings: The impact of density on emerging highly contagious infectious diseases has rarely been studied. In theory, dense areas lead to more face-to-face interaction among residents, which makes them potential hotspots for the rapid spread of pandemics. On the other hand, dense areas may have better access to health care facilities and greater implementation of social distancing policies and practices. The current COVID-19 pandemic is a perfect case study to investigate these relationships. Our study uses structural equation modeling to account for both direct and indirect impacts of density on the COVID-19 infection and mortality rates for 913 U.S. metropolitan counties, controlling for key confounding factors. We find metropolitan population to be one of the most significant predictors of infection rates; larger metropolitan areas have higher infection and higher mortality rates. We also find that after controlling for metropolitan population, county density is not significantly related to the infection rate, possibly due to more adherence to social distancing guidelines. However, counties with higher densities have significantly lower virus-related mortality rates than do counties with lower densities, possibly due to superior health care systems. Takeaway for practice: These findings suggest that connectivity matters more than density in the spread of the COVID-19 pandemic. Large metropolitan areas with a higher number of counties tightly linked together through economic, social, and commuting relationships are the most vulnerable to the pandemic outbreaks. They are more likely to exchange tourists and businesspeople within themselves and with other parts, thus increasing the risk of cross-border infections. Our study concludes with a key recommendation that planners continue to advocate dense development for a host of reasons, including lower death rates due to infectious diseases like COVID-19.

Problem, research strategy, and findings: The monocentric development pattern in the Alonso–Mills–Muth model underpinned theoretical discussions of urban form in the 1960s and 1970s and truly dominated theory up to the point when Joel Garreau published Edge City: Life on the New Frontier in the early 1990s. Monocentric development patterns remain dominant to this day among smaller metropolitan areas in the United States. However, for larger metropolitan areas in the United States, regional transportation plans suggest a paradigm shift to a polycentric structure. We review 126 regional transportation plans in the United States and find that a hierarchy of centers connected by high-quality transit has become the dominant vision for most of them. The plan for Salt Lake City (UT), for example, strives for a multicentered region even though secondary centers are only beginning to emerge beyond a dominant downtown. Generally missing from regional transportation plans are quantitative criteria for designating and guiding centers: In no case are the quantitative criteria empirically based on proven transportation benefits. Here we investigate how the built environment characteristics of centers are associated with people’s travel mode choices and vehicle use. We employ visual and exploratory approaches through a generalized additive model (GAM) to identify nonlinear relationships between travel outcomes and “D” variables (density, diversity, design, destination accessibility, and distance to transit) within centers. The model and plots help us recommend the built environment characteristics of centers. Takeaway for practice: The built environment thresholds and relevant tools provided here can enable planners to make informed decisions about future growth patterns, set realistic—yet visionary—goals, and improve the overall health of its residents and communities. We provide strategies and tools that planning agencies, such as metropolitan planning organizations, transit agencies, and municipalities, can adopt to channel developments into centers.