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Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States.
PLoS One. 2021; 16(3):e0248702.Plos

Abstract

BACKGROUND

Socially vulnerable communities may be at higher risk for COVID-19 outbreaks in the US. However, no prior studies examined temporal trends and differential effects of social vulnerability on COVID-19 incidence and death rates. Therefore, we examined temporal trends among counties with high and low social vulnerability to quantify disparities in trends over time.

METHODS

We conducted a longitudinal analysis examining COVID-19 incidence and death rates from March 15 to December 31, 2020, for each US county using data from USAFacts. We classified counties using the Social Vulnerability Index (SVI), a percentile-based measure from the Centers for Disease Control and Prevention, with higher values indicating more vulnerability. Using a Bayesian hierarchical negative binomial model, we estimated daily risk ratios (RRs) comparing counties in the first (lower) and fourth (upper) SVI quartiles, adjusting for rurality, percentage in poor or fair health, percentage female, percentage of smokers, county average daily fine particulate matter (PM2.5), percentage of primary care physicians per 100,000 residents, daily temperature and precipitation, and proportion tested for COVID-19.

RESULTS

At the outset of the pandemic, the most vulnerable counties had, on average, fewer cases per 100,000 than least vulnerable SVI quartile. However, on March 28, we observed a crossover effect in which the most vulnerable counties experienced higher COVID-19 incidence rates compared to the least vulnerable counties (RR = 1.05, 95% PI: 0.98, 1.12). Vulnerable counties had higher death rates starting on May 21 (RR = 1.08, 95% PI: 1.00,1.16). However, by October, this trend reversed and the most vulnerable counties had lower death rates compared to least vulnerable counties.

CONCLUSIONS

The impact of COVID-19 is not static but can migrate from less vulnerable counties to more vulnerable counties and back again over time.

Authors+Show Affiliations

Division of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, United States of America. Charleston Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson VA Medical Center, Charleston, South Carolina, United States of America.Division of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, United States of America.Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America. Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland, United States of America.Division of Environmental Health, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, United States of America.Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

33760849

Citation

Neelon, Brian, et al. "Spatial and Temporal Trends in Social Vulnerability and COVID-19 Incidence and Death Rates in the United States." PloS One, vol. 16, no. 3, 2021, pp. e0248702.
Neelon B, Mutiso F, Mueller NT, et al. Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States. PLoS One. 2021;16(3):e0248702.
Neelon, B., Mutiso, F., Mueller, N. T., Pearce, J. L., & Benjamin-Neelon, S. E. (2021). Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States. PloS One, 16(3), e0248702. https://doi.org/10.1371/journal.pone.0248702
Neelon B, et al. Spatial and Temporal Trends in Social Vulnerability and COVID-19 Incidence and Death Rates in the United States. PLoS One. 2021;16(3):e0248702. PubMed PMID: 33760849.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States. AU - Neelon,Brian, AU - Mutiso,Fedelis, AU - Mueller,Noel T, AU - Pearce,John L, AU - Benjamin-Neelon,Sara E, Y1 - 2021/03/24/ PY - 2020/09/18/received PY - 2021/03/03/accepted PY - 2021/3/24/entrez PY - 2021/3/25/pubmed PY - 2021/4/22/medline SP - e0248702 EP - e0248702 JF - PloS one JO - PLoS One VL - 16 IS - 3 N2 - BACKGROUND: Socially vulnerable communities may be at higher risk for COVID-19 outbreaks in the US. However, no prior studies examined temporal trends and differential effects of social vulnerability on COVID-19 incidence and death rates. Therefore, we examined temporal trends among counties with high and low social vulnerability to quantify disparities in trends over time. METHODS: We conducted a longitudinal analysis examining COVID-19 incidence and death rates from March 15 to December 31, 2020, for each US county using data from USAFacts. We classified counties using the Social Vulnerability Index (SVI), a percentile-based measure from the Centers for Disease Control and Prevention, with higher values indicating more vulnerability. Using a Bayesian hierarchical negative binomial model, we estimated daily risk ratios (RRs) comparing counties in the first (lower) and fourth (upper) SVI quartiles, adjusting for rurality, percentage in poor or fair health, percentage female, percentage of smokers, county average daily fine particulate matter (PM2.5), percentage of primary care physicians per 100,000 residents, daily temperature and precipitation, and proportion tested for COVID-19. RESULTS: At the outset of the pandemic, the most vulnerable counties had, on average, fewer cases per 100,000 than least vulnerable SVI quartile. However, on March 28, we observed a crossover effect in which the most vulnerable counties experienced higher COVID-19 incidence rates compared to the least vulnerable counties (RR = 1.05, 95% PI: 0.98, 1.12). Vulnerable counties had higher death rates starting on May 21 (RR = 1.08, 95% PI: 1.00,1.16). However, by October, this trend reversed and the most vulnerable counties had lower death rates compared to least vulnerable counties. CONCLUSIONS: The impact of COVID-19 is not static but can migrate from less vulnerable counties to more vulnerable counties and back again over time. SN - 1932-6203 UR - https://www.unboundmedicine.com/medline/citation/33760849/Spatial_and_temporal_trends_in_social_vulnerability_and_COVID_19_incidence_and_death_rates_in_the_United_States_ L2 - https://dx.plos.org/10.1371/journal.pone.0248702 DB - PRIME DP - Unbound Medicine ER -