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IMPORTANCE An important consequence of cannabis legalization is the potential increase in the number of cannabis-impaired drivers on roads, which may result in higher rates of traffic-related injuries and fatalities. To date, limited information about the effects of recreational cannabis laws (RCLs) on traffic fatalities is available.OBJECTIVE To estimate the extent to which the implementation of RCLs is associated with traffic fatalities in Colorado and Washington State. DESIGN, SETTING, AND PARTICIPANTSThis ecological study used a synthetic control approach to examine the association between RCLs and changes in traffic fatalities in Colorado and Washington State in the post-RCL period (2014)(2015)(2016)(2017). Traffic fatalities data were obtained from the

Background: The rapid growth of opioid abuse and the related mortality across the United States has spurred the development of predictive models for the allocation of public health resources. These models should characterize heterogeneous growth across states using a drug epidemic framework that enables assessments of epidemic onset, rates of growth, and limited capacities for epidemic growth. Methods: We used opioid overdose mortality data for 146 North and South Carolina counties from 2001 through 2014 to compare the retrodictive and predictive performance of a logistic growth model that parameterizes onsets, growth, and carrying capacity within a traditional Bayesian Poisson space–time model. Results: In fitting the models to past data, the performance of the logistic growth model was superior to the standard Bayesian Poisson space–time model (deviance information criterion: 8,088 vs. 8,256), with reduced spatial and independent errors. Predictively, the logistic model more accurately estimated fatality rates 1, 2, and 3 years in the future (root mean squared error medians were lower for 95.7% of counties from 2012 to 2014). Capacity limits were higher in counties with greater population size, percent population age 45–64, and percent white population. Epidemic onset was associated with greater same-year and past-year incidence of overdose hospitalizations. Conclusion: Growth in annual rates of opioid fatalities was capacity limited, heterogeneous across counties, and spatially correlated, requiring spatial epidemic models for the accurate and reliable prediction of future outcomes related to opioid abuse. Indicators of risk are identifiable and can be used to predict future mortality outcomes.

Pain management clinic (PMC) laws were enacted by 12 states to promote appropriate opioid prescribing, but their impact is inadequately understood. We analyzed county-level opioid overdose deaths (National Vital Statistics System) and patients filling long-duration (≥30 day) or high-dose (≥90 morphine milligram equivalents) opioid prescriptions (IQVIA, Inc) in the United States from 2010-2018. We fit Besag-York-Mollié spatiotemporal models to estimate annual relative rates (RR) of overdose and prevalence ratios (PR) of high-risk prescribing associated with any PMC law and three provisions: payment restrictions, site inspections, and criminal penalties. Laws with criminal penalties were significantly associated with reduced PRs of long-duration and high-dose opioid prescriptions (adjusted PR: 0.82, 95% credible interval (CrI) 0.92-0.83, and 0.73, and 0.73, 0.74 respectively), and reduced RRs of total and natural/semi-synthetic opioid overdoses (adjusted RR: 0.86, 95% CrI: 0.80, 0.92; and 0.84, and 0.77, 0.92, respectively). Conversely, PMC laws were associated with increased relative rates of synthetic opioid and heroin overdose deaths, especially criminal penalties (adjusted RR: 1.83, 95% CrI: 1.59, 2.11; and 2.59, and 2.22, 3.02, respectively). Findings suggest laws with criminal penalties were associated with intended reductions in high-risk opioid prescribing and some opioid overdoses, but raise concerns regarding unintended consequences on heroin/synthetic overdoses.

Mandating CO alarms significantly increased the detection of potentially hazardous CO levels in NYC homes. Small numbers and detection bias might have limited the discovery of significant decreases in poisoning outcomes. Investigation of individual poisoning circumstances since the law might elucidate remaining gaps in awareness and proper use of CO alarms.