Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009–2014

Yusuf Ransome, S. V. Subramanian, Dustin T. Duncan, Daivid Vlahov, Joshua Warren

Research output: Contribution to journalArticle

Abstract

Drug- and alcohol-poisoning deaths remain current public health problems. Studies to date have typically focused on individual-level predictors of drug overdose deaths, and there remains a limited understanding of the spatiotemporal patterns and predictors of the joint outcomes. We use a hierarchical Bayesian spatiotemporal multivariate Poisson regression model on data from (N = 167) ZIP-codes between 2009 and 2014 in New York City to examine the spatiotemporal patterns of the joint occurrence of drug (opioids) and alcohol-poisoning deaths, and the covariates associated with each outcome. Results indicate that rates of both outcomes were highly positively correlated across ZIP-codes (cross-correlation: 0.57, 95% credible interval (CrI): 0.29, 0.77). ZIP-codes with a higher prevalence of heavy drinking had higher alcohol-poisoning deaths (relative risk (RR):1.63, 95% CrI: 1.26, 2.05) and drug-poisoning deaths (RR: 1.29, 95% CrI: 1.03, 1.59). These spatial patterns may guide public health planners to target specific areas to address these co-occurring epidemics.

Original languageEnglish (US)
Article number100306
JournalSpatial and Spatio-temporal Epidemiology
Volume32
DOIs
StatePublished - Feb 2020

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Keywords

  • Alcohol
  • Drug overdose
  • Multivariate
  • Poverty
  • Spatiotemporal

ASJC Scopus subject areas

  • Epidemiology
  • Geography, Planning and Development
  • Infectious Diseases
  • Health, Toxicology and Mutagenesis

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