In his recent editorial Forecasting the opioid epidemic, Don Burke discussed the rise in opioid addiction in the United States and pointed to the need for data openness and analysis in developing strategies and policies to help mitigate this epidemic. Burke and his co-workers have now posted a preprint on bioRxiv, Exponential Growth of the USA Overdose Epidemic, that reveals that the number of deaths reported as accidental poisonings that can reasonably be associated with opioid overdoses in the United States grew from 2475 cases in 1979 to over 44,000 in 2015. The growth curve over this 37-year period is very close to exponential, with a fit to an exponential curve showing a correlation coefficient of R2 = 0.99. The exponential fit reveals a doubling time in the number of deaths of approximately 8 years.
Note that this is a preprint that has not been peer reviewed. Nonetheless, the result is straightforward, and the remarkably good fit of this potentially complicated data set to a simple function has several important implications. First, the fit enables a simple forecasting approach. In this case, the forecast is that there will be over 300,000 opioid overdose deaths in the 5-year period from 2016 to 2020 across the United States. Such a high number highlights the importance of developing effective strategies for addressing the epidemic and slowing its exponential growth. Second, the observation of deviations from exponential behavior such as the acceleration from 2002 to 2006 provides clues about the changes that might be driving the growth of the epidemic.
This new result once again illustrates the importance of data in public health, as discussed in my recent editorial.