Longitudinal analyses of the relationship between development density and the COVID-19 morbidity and mortality rates: Early evidence from 1,165 metropolitan counties in the United States

被引:109
作者
Hamidi, Shima [1 ]
Ewing, Reid [2 ]
Sabouri, Sadegh [2 ]
机构
[1] Johns Hopkins Univ, Dept Environm Hlth & Engn, Bloomberg Sch Publ Hlth, 615 N Wolfe St, Baltimore, MD 21205 USA
[2] Univ Utah, Dept City & Metropolitan Planning, Coll Architecture Planning, 3755 1530 E, Salt Lake City, UT 84112 USA
关键词
URBAN SPRAWL; HEALTH; IMPACT; TRANSMISSIBILITY; DISPARITIES; QUALITY; CITIES; UPDATE; CARE; FORM;
D O I
10.1016/j.healthplace.2020.102378
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
This longitudinal study aims to investigative the impacts of development density on the spread and mortality rates of COVID-19 in metropolitan counties in the United States. Multilevel Linear Modeling (MLM) is employed to model the infection rate and the mortality rate of COVID-19, accounting for the hierarchical (two-level) and longitudinal structure of the data. This study finds that large metropolitan size (measured in terms of population) leads to significantly higher COVID-19 infection rates and higher mortality rates. After controlling for metropolitan size and other confounding variables, county density leads to significantly lower infection rates and lower death rates. These findings recommend that urban planners and health professionals continue to advocate for compact development and continue to oppose urban sprawl for this and many other reasons documented in the literature, including the positive relationship between compact development and fitness and general health.
引用
收藏
页数:8
相关论文
共 64 条
[11]  
Carey B., 2020, NY TIMES
[12]  
Cascella M., 2021, EVALUATION TREATMENT, DOI DOI 10.1097/01.AOG.0000245442.29969.5c
[13]   Geographic Differences in COVID-19 Cases, Deaths, and Incidence - United States, February 12-April 7, 2020 [J].
MMWR-MORBIDITY AND MORTALITY WEEKLY REPORT, 2020, 69 (15) :465-471
[14]  
Centers for Disease Control and Prevention, 2020, BIRTH DEFECTS
[15]   A geographic analysis of population density thresholds in the influenza pandemic of 1918-19 [J].
Chandra, Siddharth ;
Kassens-Noor, Eva ;
Kuljanin, Goran ;
Vertalka, Joshua .
INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS, 2013, 12
[16]   The 1918-1919 influenza pandemic in England and Wales: spatial patterns in transmissibility and mortality impact [J].
Chowell, Gerardo ;
Bettencourt, Luis M. A. ;
Johnson, Niall ;
Alonso, Wladimir J. ;
Viboud, Cecile .
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2008, 275 (1634) :501-509
[17]   An interactive web-based dashboard to track COVID-19 in real time [J].
Dong, Ensheng ;
Du, Hongru ;
Gardner, Lauren .
LANCET INFECTIOUS DISEASES, 2020, 20 (05) :533-534
[18]   Health and urban living [J].
Dye, Christopher .
SCIENCE, 2008, 319 (5864) :766-769
[19]   Modelling disease outbreaks in realistic urban social networks [J].
Eubank, S ;
Guclu, H ;
Kumar, VSA ;
Marathe, MV ;
Srinivasan, A ;
Toroczkai, Z ;
Wang, N .
NATURE, 2004, 429 (6988) :180-184
[20]   Measuring sprawl and its transportation impacts [J].
Ewing, R ;
Pendall, R ;
Chen, D .
TRAVEL DEMAND AND LAND USE 2003: PLANNING AND ADMINISTRATION, 2003, (1831) :175-183