Spatialising urban health vulnerability: An analysis of NYC’s critical infrastructure during COVID-19

Gayatri Kawlra and Kazuki Sakamoto
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Gayatri Kawlra: Columbia University, USA
Kazuki Sakamoto: Columbia University, USA

Urban Studies, 2023, vol. 60, issue 9, 1629-1649

Abstract: This paper examines how fragmentation of critical infrastructure impacts the spread of the coronavirus outbreak in New York City at the neighbourhood level. The location of transportation hubs, grocery stores, pharmacies, hospitals and parks plays an important role in shaping spatial disparities in virus spread. Using supervised machine learning and spatial regression modelling we examine how the geography of COVID-19 case rates is influenced by the spatial arrangement of four critical sectors of the built environment during the public health emergency in New York City: health care facilities, mobility networks, food and nutrition and open space. Our models suggest that an analysis of urban health vulnerability is incomplete without the inclusion of critical infrastructure metrics in dense urban geographies. Our findings show that COVID-19 risk at the zip code level is influenced by (1) socio-demographic vulnerability, (2) epidemiological risk, and (3) availability and access to critical infrastructure.

Keywords: built environment; health; inequality; infrastructure; machine learning; social justice; spatial regression analysis; 建筑环境; å ¥åº·; ä¸ å¹³ç­‰; 基础设施; 机器学ä¹; 社会正义; ç©ºé—´å›žå½’åˆ†æž (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:urbstu:v:60:y:2023:i:9:p:1629-1649

DOI: 10.1177/00420980211044304

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