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• W4313410010 abstract "Opioid overdoses within the United States continue to rise and have been negatively impacting the social and economic status of the country. In order to effectively allocate resources and identify policy solutions to reduce the number of overdoses, it is important to understand the geographical differences in opioid overdose rates and their causes. In this study, we utilized data on emergency department opioid overdose (EDOOD) visits to explore the county-level spatio-temporal distribution of opioid overdose rates within the state of Virginia and their association with aggregate socio-ecological factors. The analyses were performed using a combination of techniques including Moran’s I and multilevel modeling. Using data from 2016–2021, we found that Virginia counties had notable differences in their EDOOD visit rates with significant neighborhood-level associations: many counties in the southwestern region were consistently identified as the hotspots (areas with a higher concentration of EDOOD visits) whereas many counties in the northern region were consistently identified as the coldspots (areas with a lower concentration of EDOOD visits). In most Virginia counties, EDOOD visit rates declined from 2017 to 2018. In more recent years (since 2019), the visit rates showed an increasing trend. The multilevel modeling revealed that the change in clinical care factors (i.e., access to care and quality of care) and socio-economic factors (i.e., levels of education, employment, income, family and social support, and community safety) were significantly associated with the change in the EDOOD visit rates. The findings from this study have the potential to assist policymakers in proper resource planning thereby improving health outcomes." @default.
• W4313410010 created "2023-01-06" @default.
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• W4313410010 date "2022-12-30" @default.
• W4313410010 modified "2023-10-18" @default.
• W4313410010 title "Exploring county-level spatio-temporal patterns in opioid overdose related emergency department visits" @default.
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• W4313410010 doi "https://doi.org/10.1371/journal.pone.0269509" @default.
• W4313410010 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36584000" @default.
• W4313410010 hasPublicationYear "2022" @default.
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