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Health Effects of Coastal Storms and Flooding in Urban Areas: A Review and Vulnerability Assessment
Open accessAbstract
Coastal storms can take a devastating toll on the public's health. Urban areas like New York City (NYC) may be particularly at risk, given their dense population, reliance on transportation, energy infrastructure that is vulnerable to flood damage, and high-rise residential housing, which may be hard-hit by power and utility outages. Climate change will exacerbate these risks in the coming decades. Sea levels are rising due to global warming, which will intensify storm surge. These projections make preparing for the health impacts of storms even more important. We conducted a broad review of the health impacts of US coastal storms to inform climate adaptation planning efforts, with a focus on outcomes relevant to NYC and urban coastal areas, and incorporated some lessons learned from recent experience with Superstorm Sandy. Based on the literature, indicators of health vulnerability were selected and mapped within NYC neighborhoods. Preparing for the broad range of anticipated effects of coastal storms and floods may help reduce the public health burden from these events.
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“Nevertheless, formerly redlined neighborhoods appear to be more likely than nonredlined neighborhoods to be facing high flood risk, disproportionately impacting households of color.148”
From NPCC4: Advancing climate justice in climate adaptation strategies for New York City (2024) · cites this paper as [148]
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“The history of redlining also contributes to inequities in disaster protection and recovery funding.”
From NPCC4: Advancing climate justice in climate adaptation strategies for New York City (2024) · cites this paper as [148]
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“For example, redlining has led to lower property values, which can result in fewer government flood-protection funds.148”
From NPCC4: Advancing climate justice in climate adaptation strategies for New York City (2024) · cites this paper as [148]
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Metadata
- Authors
- Lane, K., Charles-Guzman, K., Wheeler, K., Abid, Z., Graber, N., & Matte, T.
- Affiliations
- New York City Department of Health and Mental Hygiene (US)
- Bureau of Environmental Surveillance and Policy, New York City Department of Health and Mental Hygiene, New York, NY 10013, USA
- Corresponding author
- Lane, Kathryn
- Venue
- Journal of Environmental and Public Health
- Publisher
- Wiley
- Published
- 2013
- Volume
- 2013
- Pages
- 1-13
- ISSN
- 1687-9805 (ISSN-L)
- 1687-9813
- PMC
- PMC3683478
- OpenAlex
- W2038153217
- Cited by
- 232
- References
- 80
- Citations by year
- 2026: 9 · 2025: 19 · 2024: 33 · 2023: 24 · 2022: 18 · 2021: 20 · 2020: 12 · 2019: 22 · 2018: 25 · 2017: 13 · 2016: 20 · 2015: 11 · 2014: 4 · 2013: 2
- FWCI
- 1.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Environmental and Public Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Centers for Disease Control and Prevention (1UE1EH000757-01)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
- Health Sciences › Health Professions › Emergency Medical Services › Disaster Response and Management
- Social Sciences › Sociology and Political Science › Disaster Management and Resilience
- Keywords
- coastal storms, urban flooding, public health impact, climate change adaptation, sea level rise, storm surge, Superstorm Sandy, New York City, high-rise residential buildings, climate adaptation planning
- MeSH terms
- Disaster Planning, Housing, Humans, New York City, Oceans and Seas, Public Health, Residence Characteristics, United States, Urban Health, Cyclonic Storms, Floods, Climate Change
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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