Integrating data at multiple spatial scales to estimate the local burden of the opioid syndemic.

The opioid epidemic has been particularly severe in Ohio, prompting significant efforts to understand its spatial patterns, mainly using available data at the county level. However, relying solely on county-level analysis can overlook crucial information relevant to localized effects. To address this, we integrate spatially misaligned data observed at the county and ZIP code levels to explore the complex interaction of five opioid-related outcomes, providing a more detailed local understanding of the opioid epidemic. We demonstrate how to map ZIP-code level data to ZIP-code Tabulation Areas (ZCTAs) and relate the county-level and ZCTA-level outcomes to a spatially correlated latent factor. The latent factor is defined on the intersection of the misaligned areal units, which provides a more granular understanding of the opioid epidemic. Furthermore, this approach allows us to identify areas with varying levels of opioid burden and reveals local regions with relatively high burden that county-level analyses might miss. Finally, we highlight the need for careful consideration when relying solely on ZIP code level data for naloxone, as it may lead to misinterpretations, particularly in rural regions.