The past decade saw increasing attention turned toward Canada as an active supplier of synthetic drugs to the U.S. and wider international market. Other than occasional drug seizures at border crossings and news stories, no systematic research has been conducted to verify or ascertain such claims. This study assesses the Canadian synthetic drugs market by using multiple sources of data and three methods (georeferencing, economic modeling, and chemical composition analysis) to establish the scope, scale, and structure of synthetic drugs production in Canada, with a particular focus on the province of Quebec. The study’s findings indicate that: 1) smuggling patterns at the country’s border are scattered with no indication of an organized or concentrated system of traffic; 2) synthetic drugs production is not high enough to substantiate a significant exportation potential; and 3) contradictions in the pricing and quality of synthetic drugs at the retail level indicate an unsophisticated and typically immature consumer market. Overall, the synthetic drugs market in Canada emerges as a decentralized, largely localized, and young phenomenon, thus, making it an unlikely significant source of supply or threat for the U.S. and beyond.
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Decentralized patterns of drug trafficking are associated with less sophisticated methods and a larger number of “opportunistic” participants who engage in a range of illegal activities to generate revenues .
Recognizing that cross-border shipments represent one of the riskiest points along a transnational drug shipment, it may be argued that organized crime groups adopt diverse importation strategies to mitigate these risks. However, given the level of coordination and increased risks associated with a pure decentralized/random smuggling strategy (greater geographical distances, increased number of participants), we expect that even in these more decentralized strategies patterns will emerge. This is particularly relevant given the persistence of drug trafficking endeavours to continue using similar routes despite the loss of their product through repeated seizures .
It should be noted that many seizures in airports, cargo facilities, and mail centers are “in transit” and may have been international shipments that are passing through Canada on route to other destinations.
A longer and more detailed version of this section can be found in Bouchard et al. (2012).
For example, the homeless population overlaps with the prison population, and prisoners who are released in any given year may be counted as being part of both the prison and the general population.
The assumption is not a particularly controversial one, but it is worth providing more details for the interested reader. Assuming that the ratio of ATS use to any drug use is the same in the prison population as it is in the general population (as reported in CADUMS), Pa/Pd = Ga/Gd, so that Pa = (Ga/Gd)Pd, where
Pa = Prison ATS use (to be estimated)
Pd = Prison drug use (any drug) (50.0 % - )
Ga = General population ATS use (ecstasy = 0.9 %; meth = 0.1 % - )
Gd = General population drug use (any drug) (11.4 % - )
Using daily counts instead of yearly admissions makes sense since many prisoners enter and leave (and occasionally re-enter) prison in the course of a given year. Taking yearly prison admission numbers as the population not eligible to be counted in the general population surveys would therefore overestimate the population of incarcerated ATS users. The daily count is more likely to represent the user population not found in general population surveys since it would indicate the number of individuals not eligible for general population surveys on any given day.
The range is arguably extremely wide, but useful in that: 1) we can more safely assume that the actual seizure rate falls within the range, and 2) it is within the ballpark range of what we would expect these rates to be, providing face value validity to the estimation exercise.
Purity data was unavailable. The purity parameter was thus held at 1.0 for the purpose of this study.
For more details, see Ouellet and Morselli .
Of course, many do not succeed in getting employed or start a licit business with equal revenues.
Despite our best efforts to locate ecstasy specific production data, the simple fact is that more data is available on methamphetamine labs than ecstasy labs. Given this situation, we settled on accumulating as much data as possible on methamphetamine production for the purpose of estimating the number of ATS labs more generally.
It also seems plausible based on risks of detection for producers. If there are between three and four co-offenders per lab, we would find a population of producers between 2000 and 5000. If this is the case, and assuming about 130 arrests/year in Canada for production , the risk of being arrested for synthetic drug production would be 2.5–6.5 %. This range would be consistent with the one found through capture-recapture estimates of the number of cannabis growers in Quebec: 2–5 % .
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This study was supported by a grant from the National Institute of Justice, U.S. Department of Justice (2010-94019-CA-IJ). The authors are solely responsible for the viewpoints expressed herein this article. The authors thank Dominique Laferrière and Pier-Olivier Poulin for their help with the coding and analysis of some of the data used in this study.
Appendix: An economic model to estimate the number of ATS labs
Appendix: An economic model to estimate the number of ATS labs
The basic outline consists of the recognition that these are businesses that are consequently subject to many of the same pressures facing legitimate enterprises. Illegal producers must make a rate of return that is at least as great as that which is received by other legitimate activitiesFootnote 11; additional risk from both competitors and from law enforcement must be compensated by a higher rate of return; and, producers have to pay people who work for the business a competitive wage whether in goods in kind or in cash.
It is possible to identify the rate of return (ρ) of the operation as the value of sales (Q) times the price (P) less costs (C) relative to total cost:
But ATS lab operations also face operating risks not faced by legitimate businesses: they run the risk of losing their product from raids by the authorities. This is not the same kind of business risk faced by legitimate operators who may also lose their product due to fire, flood, and so forth. Illegal operators are not able to insure their equipment or product and that raises the risk. To model this risk, assume that the producer faces a probability, π, of losing his production. This means that the expected value of the production that is being brought to market is reduced by that risk to (1- π)xPxQ.
At the same time, we need to recognize that the rate of return faced by the producer must be augmented by the risk he bears. This means that the rate of return, ρ, should be augmented by the risk so that the correct measure of the return is ρ + π. This leads to an equation that permits identification of the size of the ATS production industry in Canada:
Equation 3 permits identification of the size of the industry. The probability of being discovered by police (‘busted’), π, can be calculated as B/T where B is the number of ATS lab “busts”, and T is the total number of labs. “B″ is known from police data. “T” is to be calculated. We know the rate of return to small businesses, ρ, as it has been the same for the past fifty years or so: 10 %. We use a figure of 50 % below in illustrating different estimate scenarios. We know the value of production for the average lab operation from police busts across the province. We can calculate the cost of operating an ATS lab. In terms of Eq. 2 above, we know the values of all the variables, ρ, P, Q, and C, and we know the number of “busts”, B. Eq. 2 can be solved for T, the total number of ATS labs.
Drug specific data on ATS seizures involves very small numbers, and some uncertainty in regards to actual drugs being produced. In their survey of synthetic drug production in B.C., Diplock et al.  reported that 27 of the 33 files analyzed involved methamphetamine labs, five were ecstasy labs, and one was a GHB lab. They note that 7 of the 27 methamphetamine labs were set up to produce ecstasy as well. The RCMP  reported that, among the 45 synthetic drug lab seizures in 2008, 12 were ecstasy labs and 21 were methamphetamine labs. Given the results presented in Diplock et al. , however, and the small number of labs involved in seizures annually, we are not confident enough in the distinction between the type of synthetic drug lab to produce drug specific estimates. With little data on ecstasy production available at current time, we make the assumption that the cost structure of ecstasy production is comparable to what is derived for methamphetamine below.
We derived a partial estimate of the cost structure of methamphetamine production.Footnote 12 It takes about 10–20 mg to have an effect in controlled conditions . The assertion is that there are roughly 110 doses per ounce or 3.88 doses per gram. If we take the smaller amount, we have about 10 doses to the gram. If methamphetamine retails for $25 per quarter gram and $100 per gram, then one dose is $10. If you have 110 doses per ounce and 28 g/oz., then each gram yields an average hit of 250 mg. We assume that the total investment needed for a one ounce production of methamphetamine is approximately $200 plus the cost of anhydrous ammonia and the labor cost of production which should take the better part of a day (this is for a small lab since larger amounts are produced by labs and “super labs”.) The cooked product is diluted to become two to three ounces and sold for approximately $1500 an ounce, although this may vary by region. Labor costs and risks are not included in the assessment.
The value of a gram of methamphetamine is assumed to be worth $100, which is consistent with the UNODC  retail estimate. The wholesale price reported by UNODC is $22,086/kg. Following Eq. 3, with 50 ‘busts’ of methamphetamine labs and an assumption that the cost of producing an ounce of methamphetamine is $200 worth of materials plus another $200 in wages for the producer and another $100 for rent and protection, yields unrealistically small estimate of the number of labs outstanding. The number of doses produced in a small lab will nonetheless be substantial, amounting to revenue of $2800.
A more conservative approach to the economics of methamphetamine production leads to an estimate of the number of producers that is significantly greater. In particular, if we believe that the cost of production is higher than the simple value of the ingredients since there is an apartment to be rented, risk attached to the purchase of the materials, and the possibility of permanent injury during the process of production, combined with a higher rate of return required on the production process leads to an estimate of the number of ATS labs to about 1400. The assumptions are that the value of production is $100 per gram, that a return of 50 % is required, and that the cost of production is about $1800 an ounce. With 50 busts a year, this would imply a detection rate of 3.6 %, which would be 3 times lower than the rate for cannabis cultivation sites in Quebec [4, 5]. Decreasing the cost assumption to $1700 yields an estimate of 560 labs, for a detection rate of 9 %. Another $100 decrease produces an estimate of 350 labs (14 % detection rate). To refine this estimate and get a stronger sense of the number of labs, we need data from the larger labs so that their economies of scale and cost of production can be more systematically developed. In the absence of better data on ATS labs in Canada, a 560–1400 range appears to be plausible, especially given the amount of methamphetamine and ecstasy seized in 2007–2008 [44, 45].Footnote 13
Table 4 illustrates how estimates are sensitive to a change in the cost parameter, which we make vary from $400 to $1800. This method also relies heavily on the number of labs detected – a significant change in the number of labs detected would produce a significant change in the prevalence estimate. Variations in costs across this range would lead to estimates of the number of labs (N) from a low of 64 to a high of 1400. The probability of discovery (π) also decreases radically (from 0.79 to 0.04) as the costs or estimated number of labs increases.
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Morselli, C., Bouchard, M., Zhang, S. et al. It came from the north: assessing the claim of Canada’s rising role as a global supplier of synthetic drugs. Crime Law Soc Change 66, 247–270 (2016). https://doi.org/10.1007/s10611-016-9627-5
- Drug Trafficking
- Border Crossing
- Synthetic Drug
- Ecstasy User