TY - JOUR
T1 - COVID-19 testing, case, and death rates and spatial socio-demographics in New York City
T2 - An ecological analysis as of June 2020
AU - Kim, Byoungjun
AU - Rundle, Andrew G.
AU - Goodwin, Alicia T.Singham
AU - Morrison, Christopher N.
AU - Branas, Charles C.
AU - El-Sadr, Wafaa
AU - Duncan, Dustin T.
N1 - Funding Information:
The authors gratefully acknowledge Kevin Quealy at the New York Times for providing the cellular phone usage data that supported this analysis. The authors also thank the New York City Department of Health and Mental Hygiene for the rapid and open provision of COVID-19 data.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/3
Y1 - 2021/3
N2 - We assessed the geographic variation in socio-demographics, mobility, and built environmental factors in relation to COVID-19 testing, case, and death rates in New York City (NYC). COVID-19 rates (as of June 10, 2020), relevant socio-demographic information, and built environment characteristics were aggregated by ZIP Code Tabulation Area (ZCTA). Spatially adjusted multivariable regression models were fitted to account for spatial autocorrelation. The results show that different sets of neighborhood characteristics were independently associated with COVID-19 testing, case, and death rates. For example, the proportions of Blacks and Hispanics in a ZCTA were positively associated with COVID-19 case rate. Contrary to the conventional hypothesis, neighborhoods with low-density housing experienced higher COVID-19 case rates. In addition, demographic changes (e.g. out-migration) during the pandemic may bias the estimates of COVID-19 rates. Future research should further investigate these neighborhood-level factors and their interactions over time to better understand the mechanisms by which they affect COVID-19.
AB - We assessed the geographic variation in socio-demographics, mobility, and built environmental factors in relation to COVID-19 testing, case, and death rates in New York City (NYC). COVID-19 rates (as of June 10, 2020), relevant socio-demographic information, and built environment characteristics were aggregated by ZIP Code Tabulation Area (ZCTA). Spatially adjusted multivariable regression models were fitted to account for spatial autocorrelation. The results show that different sets of neighborhood characteristics were independently associated with COVID-19 testing, case, and death rates. For example, the proportions of Blacks and Hispanics in a ZCTA were positively associated with COVID-19 case rate. Contrary to the conventional hypothesis, neighborhoods with low-density housing experienced higher COVID-19 case rates. In addition, demographic changes (e.g. out-migration) during the pandemic may bias the estimates of COVID-19 rates. Future research should further investigate these neighborhood-level factors and their interactions over time to better understand the mechanisms by which they affect COVID-19.
KW - COVID-19
KW - Neighborhood
KW - Spatial analysis
KW - Spatial demography
KW - Spatial epidemiology
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U2 - 10.1016/j.healthplace.2021.102539
DO - 10.1016/j.healthplace.2021.102539
M3 - Article
C2 - 33639446
AN - SCOPUS:85101363042
SN - 1353-8292
VL - 68
JO - Health and Place
JF - Health and Place
M1 - 102539
ER -