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The evidence for cannabis’s treatment efficacy across different conditions varies widely, and comprehensive data on the conditions for which people use cannabis is lacking. We analyzed state registry data to provide nationwide estimates characterizing the qualifying conditions for which patients are licensed to use cannabis medically. We also compared the prevalence of medical cannabis qualifying conditions to recent evidence from the National Academies of Sciences, Engineering, and Medicine report on cannabis’s efficacy in treating each condition. Twenty states and Washington DC had available registry data on patient number, and fourteen states had data on patient-reported qualifying conditions. Chronic pain is currently and historically the most common qualifying condition reported by medical cannabis patients (67.5% in 2016). 85.5% of patient-reported qualifying conditions had either substantial or conclusive evidence of therapeutic efficacy. As medical cannabis use continues to increase, creating a nationwide patient registry will facilitate better understanding of use trends and potential effectiveness.

Middle Eastern respiratory syndrome, an emerging viral infection with a global case fatality rate of 35.5%, caused major outbreaks first in 2012 and 2015, though new cases are continuously reported around the world. Transmission is believed to mainly occur in healthcare settings through aerosolized particles. This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies. The exposure scenario includes a single index patient emitting virus-containing aerosols into the air by coughing, leading to short-and long-range airborne exposures for other patients in the same room, nurses, healthcare workers, and family visitors. Aerosol transport modeling was coupled with Monte Carlo simulation to evaluate the risk of MERS illness for the exposed population. Results from a typical scenario show the daily mean risk of infection to be the highest for the nurses and healthcare workers (8.49 × 10 −4 and 7.91 × 10 −4 , respectively), and the lowest for family visitors and patients staying in the same room (3.12 × 10 −4 and 1.29 × 10 −4 , respectively). Sensitivity analysis indicates that more than 90% of the uncertainty in the risk characterization is due to the viral concentration in saliva. Assessment of risk interventions showed that respiratory masks were found to have a greater effect in reducing the risks for all the groups evaluated (>90% risk reduction), while increasing the air exchange was effective for the other patients in the same room only (up to 58% risk reduction).

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