Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis

Abstract

Background Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic.

311 service requests as indicators of neighborhood distress and opioid use disorder

“…Although quantitative assessment of how socio-neighborhood distress affects the opioid crisis can be challenging, it can also be beneficial in guiding policy responses 18 . Likely due to these challenges, few opioid-related research studies explore the effect of social distress at the neighborhood level.…”

“…Overdose-related events are spatially dynamic, spreading differentially through regions and neighborhoods [17][18][19] . Accurate surveillance is vital for detecting outbreaks and for guiding interventions to mitigate the opioid epidemic 20 .…”

Addressing the context and consequences of substance use, misuse, and dependence: A global imperative

“…The concept of the “risk environment” [19] may be useful to reference here, given its focus on the interplay between various structural factors that increase vulnerability to morbidity and mortality. The study by Zehang Li and colleagues [20] provides an example of the use of spatiotemporal data to characterize one aspect of the risk environment. Applying a Bayesian space–time model to emergency medical services dispatch data on suspected heroin-related overdose incidents from Cincinnati in 2015–2019, the investigators identified significant spatial heterogeneity in the distribution of these calls, with strong associations with features of the built environment and temporal spikes corresponding to local media reporting.…”

“…Current media attention devoted to the “mommy drinking” myth (debunked in the Special Issue study by Sarah McKetta and Katherine Keyes [57]) is driven by the stigma resulting from the intersecting levels of scrutiny targeted toward women who parent and toward those who consume alcohol. Moreover, the disparate geospatial burden of opioid-related incidents, such as those studied by Zehang Li and colleagues [20], generates a stigma that attaches to entire neighborhoods [58]. Indeed, as a class, harm-reduction interventions have been tainted by stigma, leading to their chronic underfunding and underutilization.…”

Patterns and risk factors of opioid-suspected EMS overdose in Houston metropolitan area, 2015-2019: A Bayesian spatiotemporal analysis

“…Early recognition of these hot spots is crucial for timely and targeted intervention and investigation over time, shed light on changes in opioid use and demographics, and projections of future hot spots. The use of Bayesian spatiotemporal models, which have recently gained popularity in research on opioid-related overdose and mortality [ 15 ], could be used to provide insight into the spatiotemporal risk of opioid-related incidents and hence guide subsequent policymaking and intervention design. Model based risk estimates offer advantages over the observed risks in that the model-based approaches examine a phenomenon that exists in a particular place and point in time by observing variables that are shared by geographical locations in addition to individual characteristics.…”