{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T17:35:39Z","timestamp":1784309739742,"version":"3.55.0"},"reference-count":38,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:00:00Z","timestamp":1740182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000030","name":"Centers for Disease Control and Prevention","doi-asserted-by":"publisher","award":["NH75OT000057-01-00"],"award-info":[{"award-number":["NH75OT000057-01-00"]}],"id":[{"id":"10.13039\/100000030","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Community vulnerability is influenced by various determinants beyond socioeconomic status and plays a crucial role in COVID-19 disparities. This study aimed to develop and evaluate a novel community vulnerability index (CVI) related to temporal variations in COVID-19 incidence to provide insights into spatial disparities and inform targeted public health interventions in Clark County, Nevada. Utilizing data from the American Community Survey and other sources, 23 community measures were identified at the census tract level. The CVI was constructed using a lagged weighted quantile sum (LWQS) regression linking these measures to the monthly COVID-19 incidence from March 2020 to November 2021. The Besag\u2013York\u2013Molli\u00e9 model subsequently evaluated the spatial association between the CVI and COVID-19 incidence, controlling for temporal and spatial autocorrelations. This study identified minority status, housing inadequacy, and inactive commuting as primary contributors to the CVI that consistently influenced COVID-19 vulnerability over time. The CVI demonstrated significant spatial disparities, with higher values found in northern Clark County and the northeastern Las Vegas metropolitan area. Spatial analyses revealed varying associations between COVID-19 incidence and the CVI across census tracts, with significant associations clustered in the northern and eastern regions of the Las Vegas metropolitan area. These findings advance our understanding of the complex interplay between community conditions and COVID-19. The CVI framework may be applied to other COVID-19 outcomes such as testing, vaccination, and hospitalization, offering a valuable tool for assessing and addressing community vulnerability.<\/jats:p>","DOI":"10.3390\/ijerph22030326","type":"journal-article","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T07:46:57Z","timestamp":1740383217000},"page":"326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Unveiling Community Vulnerability to COVID-19 Incidence: A Population-Based Spatial Analysis in Clark County, Nevada"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4515-0080","authenticated-orcid":false,"given":"Lung-Chang","family":"Chien","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Biostatistics, University of Nevada, Las Vegas, NV 89154, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2311-7506","authenticated-orcid":false,"given":"L.-W. Antony","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89154, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8756-5607","authenticated-orcid":false,"given":"Chad L.","family":"Cross","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, University of Nevada, Las Vegas, NV 89154, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edom","family":"Gelaw","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, University of Nevada, Las Vegas, NV 89154, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0608-9299","authenticated-orcid":false,"given":"Cheryl","family":"Collins","sequence":"additional","affiliation":[{"name":"Desert Research Institute, Las Vegas, NV 89119, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Southern Nevada Health District, Las Vegas, NV 89107, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1759-1105","authenticated-orcid":false,"given":"Anil T.","family":"Mangla","sequence":"additional","affiliation":[{"name":"Southern Nevada Health District, Las Vegas, NV 89107, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cassius","family":"Lockett","sequence":"additional","affiliation":[{"name":"Southern Nevada Health District, Las Vegas, NV 89107, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1016\/j.hlpt.2020.08.007","article-title":"COVID-19 pandemic in the United States","volume":"9","author":"Bergquist","year":"2020","journal-title":"Health Policy Technol."},{"key":"ref_2","unstructured":"Maragakis, L. (2024, August 13). (2021, 21 October 2021). Coronavirus Second Wave, Third Wave and Beyond: What Causes a COVID Surge. Available online: https:\/\/www.hopkinsmedicine.org\/health\/conditions-and-diseases\/coronavirus\/first-and-second-waves-of-coronavirus."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pathak, E.B., Menard, J.M., Garcia, R.B., and Salemi, J.L. (2022). Joint Effects of Socioeconomic Position, Race\/Ethnicity, and Gender on COVID-19 Mortality among Working-Age Adults in the United States. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19095479"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1007\/s40615-021-01110-8","article-title":"Racial Disparity in Potential Occupational Exposure to COVID-19","volume":"9","author":"Asfaw","year":"2022","journal-title":"J. Racial Ethn. Health Disparities"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1016\/j.jaci.2021.09.007","article-title":"Occupational health disparities: The pandemic as prism and prod","volume":"148","author":"Brigham","year":"2021","journal-title":"J. Allergy Clin. Immunol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Coroiu, A., Moran, C., Campbell, T., and Geller, A.C. (2020). Barriers and facilitators of adherence to social distancing recommendations during COVID-19 among a large international sample of adults. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0239795"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mahmoudi, J., and Xiong, C. (2022). How social distancing, mobility, and preventive policies affect COVID-19 outcomes: Big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion. PLoS ONE, 17.","DOI":"10.1371\/journal.pone.0263820"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Mah, J.C., Penwarden, J.L., Pott, H., Theou, O., and Andrew, M.K. (2023). Social vulnerability indices: A scoping review. BMC Public Health, 23.","DOI":"10.1186\/s12889-023-16097-6"},{"key":"ref_9","unstructured":"Centers for Disease Control and Prevention (2024, August 13). (22 July 2024). Social Vulnerability Index, Available online: https:\/\/www.atsdr.cdc.gov\/place-health\/php\/svi\/index.html."},{"key":"ref_10","unstructured":"Centers for Disease Control and Prevention (2024, August 13). (16 December 2024). SVI Data & Documentation Download, Available online: https:\/\/www.atsdr.cdc.gov\/place-health\/php\/svi\/svi-data-documentation-download.html."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e024414","DOI":"10.1161\/JAHA.121.024414","article-title":"Association Between Social Vulnerability Index and Cardiovascular Disease: A Behavioral Risk Factor Surveillance System Study","volume":"11","author":"Jain","year":"2022","journal-title":"J. Am. Heart Assoc."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.jsr.2023.07.003","article-title":"Association between social vulnerability factors and unintentional fatal injury rates\u2013United States, 2015\u20132019","volume":"86","author":"Wulz","year":"2023","journal-title":"J. Saf. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.jss.2019.05.022","article-title":"Using the Social Vulnerability Index to Examine Local Disparities in Emergent and Elective Cholecystectomy","volume":"243","author":"Carmichael","year":"2019","journal-title":"J. Surg. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e2036462","DOI":"10.1001\/jamanetworkopen.2020.36462","article-title":"Association of Social and Demographic Factors With COVID-19 Incidence and Death Rates in the US","volume":"4","author":"Karmakar","year":"2021","journal-title":"JAMA Netw. Open"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.eiar.2013.08.002","article-title":"Social vulnerability indicators as a sustainable planning tool","volume":"44","author":"Lee","year":"2014","journal-title":"Environ. Impact Assess. Rev."},{"key":"ref_16","first-page":"71","article-title":"Social vulnerability assessment to earthquakes in cities. Case study: Zanjan city","volume":"7","author":"Roshti","year":"2010","journal-title":"Munic. Reg. Res. Stud"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/00291951.2010.550167","article-title":"Social vulnerability assessment for Norway: A quantitative approach","volume":"65","author":"Holand","year":"2011","journal-title":"Nor. Geogr. Tidsskr. Nor. J. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1073\/pnas.0710375105","article-title":"Temporal and spatial changes in social vulnerability to natural hazards","volume":"105","author":"Cutter","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_19","first-page":"0000102202154773551792","article-title":"A social vulnerability index for disaster management","volume":"8","author":"Flanagan","year":"2011","journal-title":"J. Homel. Secur. Emerg. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1111\/j.1467-7717.1995.tb00367.x","article-title":"Risk Factors for Death in the 27 March 1994 Georgia and Alabama Tornadoes","volume":"19","author":"Schmidlin","year":"1995","journal-title":"Disasters"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1007\/s11069-019-03820-z","article-title":"Evaluating social vulnerability indicators: Criteria and their application to the Social Vulnerability Index","volume":"100","author":"Spielman","year":"2020","journal-title":"Nat. Hazards"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"10775","DOI":"10.1007\/s12517-015-1939-8","article-title":"The social and physical vulnerability assessment of old texture against earthquake (case study: Fahadan district in Yazd City)","volume":"8","author":"Sarsangi","year":"2015","journal-title":"Arab. J. Geosci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.ijdrr.2015.07.003","article-title":"GIS based mapping of vulnerability to earthquake and fire hazard in Dhaka city, Bangladesh","volume":"13","author":"Rahman","year":"2015","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1007\/s11069-012-0084-x","article-title":"Social vulnerability assessment to seismic risk using multicriteria analysis: The case study of Vila Franca do Campo (S\u00e3o Miguel Island, Azores, Portugal)","volume":"62","author":"Martins","year":"2012","journal-title":"Nat. Hazards"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e100703","DOI":"10.1136\/bmjhci-2022-100703","article-title":"Social vulnerability and initial COVID-19 community spread in the US South: A machine learning approach","volume":"30","author":"Tatar","year":"2023","journal-title":"BMJ Health Care Inform."},{"key":"ref_26","unstructured":"United States Census Bureau (2024, August 13). (2024, 10 June 2024). American Community Survey (ACS), Available online: https:\/\/www.census.gov\/programs-surveys\/acs."},{"key":"ref_27","unstructured":"Environmetal Protection Agency (2024, August 13). (2024, 25 July 2024). Smart Growth: Smart Location Mapping, Available online: https:\/\/www.epa.gov\/smartgrowth\/smart-location-mapping."},{"key":"ref_28","unstructured":"HUD\u2019s Office of Policy Development and Research (2024, August 13). Comprehensive Housing Affordability Strategy (CHAS), Available online: https:\/\/www.huduser.gov\/portal\/datasets\/cp.html."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1007\/s11524-016-0116-z","article-title":"Local residential segregation matters: Stronger association of census tract compared to conventional city-level measures with fatal and non-fatal assaults (total and firearm related), using the index of concentration at the extremes (ICE) for racial, economic, and racialized economic segregation, Massachusetts (US), 1995\u20132010","volume":"94","author":"Krieger","year":"2017","journal-title":"J. Urban Health"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"109529","DOI":"10.1016\/j.envres.2020.109529","article-title":"Lagged WQS regression for mixtures with many components","volume":"186","author":"Gennings","year":"2020","journal-title":"Environ. Res."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wheeler, D.C., Rustom, S., Carli, M., Whitehead, T.P., Ward, M.H., and Metayer, C. (2021). Assessment of Grouped Weighted Quantile Sum Regression for Modeling Chemical Mixtures and Cancer Risk. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18020504"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/BF00116466","article-title":"Bayesian image restoration, with two applications in spatial statistics","volume":"43","author":"Besag","year":"1991","journal-title":"Ann. Inst. Stat. Math."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1111\/j.1467-9868.2008.00700.x","article-title":"Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations","volume":"71","author":"Rue","year":"2009","journal-title":"J. R. Stat. Soc. Ser. B Stat. Methodol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Letta, T.T., Belay, D.B., and Ali, E.A. (2022). Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling. BMC Public Health, 22.","DOI":"10.1186\/s12889-022-14153-1"},{"key":"ref_35","unstructured":"Nevada Division of Environmental Protection, Governor\u2019s Office of Energy, Sustainability Solutions Group (SSG), Ericka Aviles Consulting, & CIVIX (2024, August 13). State of Nevada Priority Climate Action Plan, Available online: https:\/\/www.epa.gov\/system\/files\/documents\/2024-03\/state-of-nevada-priority-climate-action-plan.pdf."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Disalvatore, R., Bauer, S.K., Ahn, J.E., and Jahan, K. (2023). Development of a COVID-19 Vulnerability Index (CVI) for the Counties and Residents of New Jersey, USA. Int. J. Environ. Res. Public Health, 20.","DOI":"10.3390\/ijerph20136312"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1057\/s41599-022-01437-5","article-title":"Social vulnerability amplifies the disparate impact of mobility on COVID-19 transmissibility across the United States","volume":"9","author":"Huang","year":"2022","journal-title":"Humanit. Soc. Sci. Commun."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1535","DOI":"10.15585\/mmwr.mm6942a3","article-title":"Association Between Social Vulnerability and a County\u2019s Risk for Becoming a COVID-19 Hotspot\u2014United States, 1 June\u201325 July 2020","volume":"69","author":"Dasgupta","year":"2020","journal-title":"MMWR. Morb. Mortal. Wkly. Rep."}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/22\/3\/326\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:40:19Z","timestamp":1760028019000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/22\/3\/326"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,22]]},"references-count":38,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["ijerph22030326"],"URL":"https:\/\/doi.org\/10.3390\/ijerph22030326","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,22]]}}}