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We focus on the prevalence of substance use and describe the patterns of drug consumption. These include pleasure and recreation, spiritual discovery, performance enhancement, experimentation, peer pressure, or to self-medicate physical problems, emotional pain or trauma. For those who use illicit substances, most will do so without encountering significant harm. However, some people will experience harm to their physical or mental health from either short or long-term use. There is a growing body of literature on the medicinal benefits of particular illicit drugs — in fact, most of the well-known substances have established medicinal uses. While this report does not explore why people use various substances, it is useful to keep in mind that there are a variety of reasons why New Zealanders use them. About the data sources. The substance use data NZ Health Survey is drawn from a large general population survey of New Zealanders which uses representative sampling. This allows us to gather information about substance use on a whole-population level. However, some substances are not widely used, which reduces the sample size and increases the risk of statistical errors. These errors are even more likely when looking at data for smaller demographic subgroups. This means that there may be year-to-year variation depending on recruitment in any given year, and comparing different groups of New Zealanders and trends over time needs to be done with caution. The survey also relies on self-reporting of substance use. We know that substance use carries a level of stigma in Aotearoa, so it is possible that survey participants may misrepresent their actual substance use. This is not a representative sample of the general population, as it specifically recruits people with experience of substance use. This is also a self-reported survey. The wastewater testing data used in this report relies on objective measures and is not influenced by societal views on substance use or participant errors. However, wastewater testing is only able to quantify the total volume of drugs consumed in a given catchment area, and is not able to provide us with patterns of use among people living there. At times, a decrease in detection in wastewater may also be a cause for concern — when a preferred substance is less available in the illicit market, its consumers may be switching to a different substance whose risk profile is less known. Wastewater testing is reported by Police district, however this report combines the three districts in the Auckland region. Past-year cannabis use has jumped Almost a quarter Disabled people are 3. Amphetamine-type stimulant use including methamphetamine has remained relatively stable since , with 1. Disabled people are 5. Illicit drugs are used by people in every city, town, and region of Aotearoa. This report describes some of the patterns and trends among different ages, ethnicities, genders, and locations. This report does not describe alcohol and tobacco consumption trends, instead focusing on illicit drugs. According to the NZ Health Survey, over half a million , adults used cannabis in the last year. An estimated , used cannabis at least once a week. Drugs like MDMA, methamphetamine, and opioids are used by a relatively small percentage of the population. Some drugs can be prescribed by a doctor, including cannabis, some types of amphetamines, and some types of opioids typically as pain medication. These drugs can also be obtained illicitly. Some are only available illicitly, for example heroin an opioid , methamphetamine, and psychedelics like LSD. Those who live in the most deprived neighbourhoods report higher rates of past-year use of cannabis, MDMA, amphetamines, opioids and psychedelics compared to those who live in our wealthiest areas. The reported prevalence of use of amphetamines 1. Per capita, cocaine use was more than 2. The prevalence of cocaine use in New Zealand overall is very low and has remained low for the past few years currently 1. This means that the numbers are small and are subject to fluctuation year on year. About the map data. The NZDTS surveys a very large number of people with recent experience and knowledge of drug use and drug markets across the country. While the NZDTS is not a representative sample, it broadly reflects the demographic profile and regional population distribution of New Zealand. The map categorises data according to Police district boundaries. Where locations do not match exactly for example Otago , this is noted in the specific fact. Text version of the map data. Men are 1. Almost one in ten adults aged 55—64 9. Looking further back, over the past decade, past-year cannabis use has increased across people of all ages. For example, 6. Caution is advised when interpreting these figures. MDMA use is concentrated among younger people. Use becomes far less common as people get older, with around 0. MDMA availability may be decreasing. Around 1. Because the increases in cocaine use have started from a very low baseline, any changing trends should be treated with caution. NZ Health Survey data on cocaine use prevalence does not show as rapid an increase as wastewater testing data, which may indicate that existing cocaine users may be consuming larger amounts, or that the increases in prevalence of use are very recent. Cocaine use is much more common among men 2. A record 3. Wastewater testing also reveals that the total amount of cocaine consumed in Aotearoa has more than doubled in the past two years. Latest figures for July to September show that cocaine use across those three months was 2. By contrast, just 0. Nationally, 1. The latest data shows that disabled people are 5. Amphetamine use is significantly more common among men than women. Methamphetamine use varies widely across the country. Methamphetamine use per capita is higher than the national average in every district of the North Island apart from Wellington. This is around 18, adults. The relatively low prevalence of opioid use means that there can be large variation in the numbers year-to-year. Disabled adults are 3. Some illicit drugs for example stimulants, synthetic cannabinoids can be adulterated with ultra-potent opioids like fentanyl, which people might not be aware of when they obtain them. Data for previous years is not directly comparable, however, it appears that the proportion of client visits for stimulant injecting may be increasing. At the same time, client visits for opioids methadone, morphine, heroin may be decreasing. The NZNEP report also found an increase in the proportion of client visits for steroid injecting, with latest figures showing a concentration of steroid injecting in the Auckland, Mount Maunganui, Hamilton, and central Christchurch areas. Our latest report pulls together international evidence and local experiences of how neurodivergence impacts drug use. Researcher Robin Murphy talks us through the latest Auckland University microdosing study. Policy and advocacy Drug law Submissions and reports Drugs in Aotearoa - an overview. For parents and caregivers. Workplaces and venues Bars and hospo Events For employers. Who we are Our mahi Our strategy Contact us Work for us. People use alcohol and other drugs for many reasons. About the data sources Each data source has strengths and limitations associated with the methodology used. These include: The substance use data NZ Health Survey is drawn from a large general population survey of New Zealanders which uses representative sampling. Stimulants Amphetamine-type stimulant use including methamphetamine has remained relatively stable since , with 1. Overview Illicit drugs are used by people in every city, town, and region of Aotearoa. Disabled people are more likely to have used cannabis in the past week 3. Disabled people are also more likely to report past-year opioid use compared with non-disabled people 3. Men are significantly more likely than women to report past-year use of certain illicit substances like amphetamines 2. Most illicit drug use declines as people age. However, past year cannabis use has increased across all age groups in the past decade. Cocaine was reportedly becoming easier to obtain. Illicit drug use prevalence remains relatively stable, and cannabis is still our most commonly used drug. Cannabis Cannabis use has increased among older people View this in the Drug Data section. At least-weekly cannabis use appears to be rising, especially among women. Prevalence of psychedelic use over time by gender. This is more than three times the total amount seized in kg. Amphetamines, including methamphetamine Amphetamine use is concentrated in our most deprived neighbourhoods. Prevalence of opioid use over time. References Denning P, Little J. Over the Influence. New York: The Guildford Press; Intoxication: self, state and society. Palgrave Macmillan Cham; Ministry of Health. Cocaine availability increasing in urban centres. Declines in meth prices over past four years. Cannabis prices decline as availability increases. Recent declines in MDMA availability in many regions. Psychedelic use and availability stable over time. Drug seizures. Quarter Three July - September Quarter Three: July - September Key findings. Aotearoa at a glance.

Report: Drug use in Aotearoa 2022/23

Hamilton Island buying Heroin

Official websites use. Share sensitive information only on official, secure websites. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. This research uses longitudinal data to investigate if illegal online drug purchases changed over time during the COVID pandemic, and if these changes were primarily driven by users adjusting to market conditions or by a heightened level of pandemic-induced strain that could drive a greater demand for drugs. Data were collected across four waves between fall and fall using an online survey. Strain was also related to buying illegal drugs online as those respondents who made illegal online purchased had an average of 5. However, the influence of strain on online purchases remained consistent across time. These results suggest that the increase in online drug purchases was primarily driven by users adapting to changing market conditions rather than the cumulative strains associated with the pandemic producing a greater effect on purchases. Policy implications are also discussed. Life as we knew it was dramatically altered when the first cases of severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 were reported in December While responses to the pandemic varied Capano et al. For example, online sales of cannabis reportedly increased in the first three months of COVID pandemic see Groshkova et al. Several scholars have discussed how COVID could alter drug use, prices, purity, and markets, and many of these scholars discussed plausible reasons for the increase in online drug purchases e. However, little research has gone beyond theorizing the market changes that could possibly affect drug use and sales and documenting if illegal purchases of drugs have indeed occurred. We aim to fill that gap by using longitudinal data to investigate if illegal online drug purchases changed over time, and if these changes were primarily driven by users adjusting to market conditions or by changes in other criminogenic factors induced by the pandemic such as heightened levels of strain that could drive a greater demand for drugs. Most evidence suggests illegal drug use decreased when the pandemic first upended social life. For example, preliminary findings suggest an overall decline in drug use in Europe during the early stages of the pandemic, and this was especially true for amphetamine, cocaine and MDMA use Been et al. In Australia, users noted that cocaine and methamphetamine became harder to obtain, and most of those surveyed reported either no change or a reduction in their use since COVID restrictions were introduced Price et al. There were also localized shortages of heroin in many European countries Aldridge et al. Yet, the pattern of decreasing rates of use were not universal nor long lasting. Data from the U. In addition to affecting the rates of use and rates of problematic use, the pandemic also changed the nature of buying and selling illicit drugs. Most evidence suggests that the lockdown orders and other pandemic-induced restrictions led to a contraction of traditional, in-person drug markets EMCDDA, b. Although the effects of lockdowns on drug markets were likely dependent on the intensity and timing of lockdowns Aldridge et al. Moreover, the closure of usual recreational settings such as nightclubs, bars, and dance clubs likely led to a decrease in the sale of stimulants see Winstock et al. Yet, as with past market disruptions, drug dealers and users adapted to the changing market conditions. It appears the pandemic and the resulting lockdowns led to an increase in darknet drug purchases Groshkova et al. Assuming there was an increased use of online drug markets, the question remains why this happened during the pandemic. There are several plausible explanations, but two seem to be particularly likely. The first possible reason is that users adapted to the changing market and turned to online purchases in response to decreased opportunities to obtain their drugs of choice using traditional, face-to-face offline purchases. The second possible reason is that there was greater demand for drugs as COVID and the resulting lockdowns led to heightened strains. All else being equal, the increase in demand for drugs would likely lead to an increase in purchases, including online purchases. These reasons will now be discussed. While online sales are only a small fraction of the total global drug trade, there was already a considerable online drug market prior to the pandemic. Statista, This increase in online drug purchases is undoubtedly due in part to natural increases in e-commerce that have been observed with other products; however, the pandemic likely contributed to this growth significantly if one considers how cryptomarkets operate. Online drug markets host multiple vendors who earn commission on sales in return for providing drug buyers anonymity via encrypted messaging and payments. Therefore, cryptomarkets allow buyers to purchase drugs from a far wider selection of dealers—and dealers to reach a far broader market of buyers—than would ever be possible with face-to-face trade. The increased access to drugs via numerous vendors is particularly important in the context of COVID First, stay-at-home orders and other restrictions on in-person interactions would likely limit access to the offline drug-dealing networks one has. Second, restrictions on social gatherings and lock-down orders would limit the number of people in public spaces that need to be observed, face-to-face drug transactions likely involved greater risk of detection during the pandemic than they did prior to the pandemic. Police presence on the street continued to be heavy and border controls became more robust UNODC, , and border patrol seized more drug shipments in the first months of the pandemic than in the three months before the pandemic UNODC, Because of the pandemic induced lockdown orders, individuals stayed home and shifted many of their daily activities online. On the now-empty streets, dealers and buyers would become significantly more visible. These circumstances may have initiated market adaptation, where drug transactions were shifted online and drug delivers are made via postal or individual courier services. Limiting face-to-face contact would also reduce the risks of contracting the virus. Thus, online drug purchases would likely appeal to those wanting to avoid potential legal and health consequences. Finally, as noted previously, the apparent increase in online drug sales during the pandemic was primarily driven by online cannabis sales. It is possible this market adjustment was due to those who typically buy larger quantities for resale limited their purchases while casual users increased their purchases. The increase of small-quantity purchases could have been due to existing online cannabis buyers stockpiling their drug of choice in case of market disruptions or users who had not previously made online purchases turning to online purchases as a means of securing their drugs see Groshkova et al. Yet, an increase in online drug purchases could also result from other, non-market related factors. Instead of adjusting to changes in the market supply of drugs, increased online purchases could also simply reflect a greater pandemic-induced demand for drugs. The pandemic has been extremely disruptive in numerous ways, and this disruption in our daily routines undoubtedly contributed to strains. As Agnew argues, strain results from failing to achieve a positive goal, the removal of positive stimuli, or the addition of negative or noxious stimuli. The pandemic undoubtedly was a source of all these types of strain to many people. Strain also appears to be related to online drug purchases. For example, in a sample of young adults from the United States and Spain, purchasing illegal drugs online was related to higher psychological distress, which can be considered a manifestation of strain, even after controlling for self-control, social bonds, excessive gambling behaviors, and excessive internet use Oksanen et al. While strain appears to be related to drug use and online drug purchasing in general, studies analyzing the relationship between drug use and strain and negative emotions during the COVID pandemic also suggest that pandemic-induced strains could lead to an increased drug use. For example, increased use of cannabis and benzodiazepines was reported due to the general feeling of stress caused by the pandemic and associated restrictions Winstock et al. In addition, online opioid purchases were associated with lower self-control, elevated social anxiety, heavy gambling, and Internet use Cebo, Similarly, in a study of Slovenian licit and illicit drug users who used more drugs during the pandemic than before, Sande et al. Carlyle et al. It is worth noting that other than enjoyment, these factors can be all considered stressors Brooks et al. Therefore, the COVID pandemic could lead to increases in online drug purchases 1 by forcing users and dealers to adapt to changing market conditions, 2 by inducing more strain and negative emotions therefore producing greater demand for drugs, or 3 by a combination of inducing demand for drugs through heightened strains and forcing users to adapt to changing market conditions. We try to disentangle these possible effects by analyzing illegal online drug purchases over time as the pandemic unfolds. This combination of factors has led us to three hypotheses:. Hypothesis 2: Individuals who were more strained were more likely to have purchased illegal drugs online;. Data were collected using an online survey. Dynata uses random digit dialing, banner ads, and other permission-based techniques to recruit respondents and create a database. They then select samples for surveys and respondents are contacted via email. Participants who complete the survey and who are not removed due to patterns of fraud or speed receive a small fee or reward from Dynata. As such, the participants are motivated to successfully complete the survey. In terms of data quality, population representation, honesty, and attention of participants, prolific panel platforms such as Dynata provide higher quality samples compared to self-service survey platforms such as MTurk, CloudResearch, Prolific, and SurveyMonkey Eyal et al. Moreover, Dynata is one of the highest data quality prolific panel providers Eyal et al. The authors coded the survey using the Qualtrics online platform. The survey included several parts. Second, a series of demographic and computer use questions provided a baseline to ensure the sample was within the expected margin of error for a nationally representative sample when compared to U. Census data. Third, questions related to cybervictimization and cyber offending were asked. These questions were derived from prior research and included 10 individual acts of offending and victimization e. Finally, participants were asked a series of questions that reflect concepts from various criminological theories. These items were part of a larger project. In this paper we utilized questions about general strain theory that were derived from Hinduja and Patchin Data were collected across multiple waves. Table 1 shows the characteristics of each wave. Across all four waves there were 4, participants, however, listwise deletion of missing data resulted in 60 respondents who did not respond to the drug question being dropped from the analysis. Listwise deletion was used because there were no discernable patterns related to the missing data as they appear to be missing at random. All samples were balanced according to census data on sex, ethnicity, and race. Online samples are generally found to be similar to random probability-based samples MacInnis et al. The survey took an average of 15 min 45 s across all waves. The average difference can be accounted for by difference in which theories were included on the survey as some theories require more items to test than do others. These other theories were part of a larger project and not tested in this paper. The focus of our research pertains to illegal online drug purchases. To measure general strain, we used questions developed by Hinduja and Patchin We adjusted the questions to be more appropriate for an adult sample. For example, instead of asking whether the individual has received a bad grade in the past 12 months, we asked if they recently got a bad grade, performance review, or evaluation. A total of nine questions were asked about strain. These were then summated into a general strain scale. The general strain scale had a range of 0—9, indicating all possible levels of strain across participants. The average strain score was 2. We also included a series of control variables. These encompassed gender, race, ethnicity, family income, education, and age see Table 4 for categories of income and education. Age was measured continuously. Due to low numbers of several genders and races, these variables are coded as binary variables Male and White. While gender and race were balanced during data collection, family income, education and age were not. Nevertheless, these variables still appear comparable to U. Given that the sample does not include those under 18, our sample is likely very close to the U. For further information on control variables see Table 4. In total, 9. H1: To examine the first hypothesis, wave of data was used to predict online purchases. Generally, we see an increase in reported online drug purchases across the waves see Table 2 for specific differences. In , 7. H2: Testing the second hypothesis, a t-test revealed a significant difference between those participants who bought illegal drugs online and those who did not in terms of their reported levels of strain. Participants who reported buying illegal drugs online had an average of 5. While independent analyses revealed both the wave and GST influenced online illegal purchasing, the potential interaction of these factors was also analyzed. To do so, we utilized several logistic regressions. All models met the basic assumptions of logistic regression in that the observations were independent, there were no problems of multicollinearity, and the samples were sufficiently large. First, we examined a logistic regression that included all four waves of data as discrete variables and the measure of GST. The subsequent two waves, Spring and Fall , were not a significant predictor of online drug purchases. However, Fall and the GST index were significant. Table 5 reports the results of the logistics regressions. H3: We then proceeded to examine the third hypothesis by testing if there was an interaction between strain and wave of data collection with another logistic regression. These interactions test if strain and COVID cumulated to create a heightened chance of buying illegal drugs online beyond any main effects. None of the interaction terms achieved statistical significance. Moreover, the addition of the interactions did not significantly increase the explained variance. As such, the final model does not include interaction terms. The final model includes the wave of data, GST and a series of control variables, including gender, race, ethnicity, age, income, and education. The final model produced similar results as the earlier main-effect model for both the wave variables and GST. The first two waves were not statistically significant, while the final wave and GST were significant predictors of online purchases. Similar significance and odds ratios were found across both the first and third model. These results show that control variables did not influence the relationship between online drug purchases and wave of data collection or strain. However, several control variables were also significant predictors of online drug purchases. Having higher income also increased the odds of purchasing illegal drugs online. Of note as well was the variable that failed to achieve statistical significance. The paper explored illegal online drug purchases during the pandemic and if these were related to time i. In a national sample of adult Americans, we analyzed data collected at four different times, once before the pandemic Fall, and three times as the pandemic unfolded in Spring , Fall , and Fall , respectively. Because of lockdown measures and greater difficulties and dangers associated with traditional street-based drug dealing, we hypothesized that online drug purchase would increase during the pandemic H1. We also hypothesized that strain would increase online drug purchasing H2. Furthermore, we expected that strain and time into the pandemic would interact to increase the purchase of illegal drugs online above the main effect associated with time and strain H3. These findings suggest that market forces were likely the primary driver of the increased use of online drug markets during the COVID pandemic. As the pandemic disrupted traditional drug markets by halting shipments and allowing for increased police presence on streets, it likely triggered an increased use of digital technology in drug distribution, including increased mail delivery and contactless methods for reaching buyers such as web-based purchases UNODC, However, our data shows that this increase was delayed, not truly increasing until Fall Conversely, while strain increases the likelihood of purchasing drugs online, the effect of strain on online purchases remained consistent across time as the pandemic unfolded. Therefore, it does not appear that any heightened strains experienced because of the pandemic drove the greater use of online markets observed in our data. Although people undoubtedly experienced greater strains during the pandemic, and this may have driven greater drug use, there is no evidence that these strained drug purchasers were more likely to buy their drugs online than they were prior to the pandemic. Online drug purchasers tend to have additional characteristics beyond strain, such as low levels of self-control, excessive gambling behaviors, excessive levels of internet use, and relatively weak offline social bonds see Oksanen et al. Thus, increased stain alone may not produce enough motivation to turn to the internet for drug purchases. In addition, having strong offline social networks could provide greater access to drugs without relying on internet sells. Our data reveals a robust drug market and innovative adaptations to the new challenges posed to it by the pandemic, but our data suggests it took drug buyers time to adapt to these changing market forces. It was not until the Fall of that we see a significant increase in online purchases. While we do not have the data to confirm this assertion, the delayed increase in online purchases may well be because these sales were primarily driven by small quantity purchases rather than the purchases of large quantities for resale Groshkova et al. It appears that as the pandemic wore on users who had not previously made online purchases turned to online purchases as a means of securing their drugs. This conclusion is consistent with other known facts about changes in the drug market after the pandemic. Moreover, several studies suggest Namli, ; Sande et al. Either way, the data suggest there was a dynamic adaptation to the pandemic by drug purchasers. Given this change may have been driven more by convenience than any severe disruption in the supply of drugs, it is likely that those who experimented with online drug purchasing during the pandemic will continue this practice after the pandemic. In addition to our findings concerning online purchases over time and strain, the demographic characteristics of online drug buyers in our study align with many previous findings. First, adolescents and young adults are more likely to use drugs than are older individuals Chassin et al. Males are also far more likely to use drugs than are females Alves et al. In the current data, participants who purchased illegal drugs online were also disproportionately males, well educated, and have higher incomes. Although, our survey did not allow for a comparison of buyer activity in online and offline drug markets, we suggest that the findings that young, highly educated males with higher incomes are the ones who purchase drugs online might be indicative of different demographic compositions of offline and online drug market customers rather than differences in drug users, per se. Online drug markets are not easily accessible for everyone. Users need a stable internet connection, and must download specific browsers and buy cryptocurrency to be able to purchase on the dark web Norbutas, ; Norbutas et al. To be comfortable arranging online transactions on the dark web, one needs to be familiar with customer reviews and judge seller and product reliability through social ties and a centralized reputation scoring system see Diekmann et al. These skills and familiarization with sellers and market conditions, as well as developing the necessary levels of trust in the marketplace, requires time and money, conditions that individuals with unstable labor conditions, low paying jobs, and inadequate financial backgrounds may not be able to afford. Thus, it is predicable that the relatively affluent are more likely to use online drug markets. Our research has policy implications. As we see an increase in illegal online drug purchases, one may ask what authorities can possibly do about it. Although the pandemic-induced market adaptation led to the increase of online drug markets, this increase may not be clear evidence for greater policing of online drug markets. We should learn from the research on the policing of traditional drug markets that highlights the symbolic nature of these approaches and the harms associated with them. Targeted venues either moved to other locations or reopened shortly after they had temporarily closed. Second, hot spot and zero tolerance policing can lead to riskier behavior by those involved in drug dealing and using. Similarly, disrupting cryptomarkets that are mostly involved in the selling of cannabis products can lead to adaptations that lead buyers and users to more dangerous online behaviors or more dangerous drugs. As noted above, the growth of online drug transactions appears to have been driven by the greater purchasing of relatively small quantities of marijuana. Thus, just as hot spot zero tolerance policing disproportionately affects small-scale dealers and users, heightened policing of online transactions is likely to affect users rather than large-scale dealers. While we are likely to achieve some highly visible disruptions, such as the shutting down of the original Silk Road drug market in , these tactics are unlikely to produce lasting effects. Thus, we should learn from traditional law enforcement efforts to control street-level drug sales and pursue policies that are evidence driven and take advantage of the unique features of cryptomarkets. By understanding this crime script, we can tailor law enforcement interventions to effectively target each stage see Jardine, Although online non-probability samples are generally found to be similar to random probability-based samples MacInnis et al. Second, the observed odds ratios relating our independent variables and drug purchasing are high in the sample Table 5. However, since buying illegal drugs is a low base-rate behavior only 7. Meaning, while the odds ratios are high, they only result in a few percentage points increase in behavior. Although the increase in those purchasing drugs illegal online is significant in the last data collection wave, cautions in drawing dramatic conclusions from this are warranted. Next, while we know from the sample that males with higher education and higher financial well-being are the most likely to purchase illegal drugs online, the survey did not ask about and could not investigate the reasons why. There is evidence Daniel, ; EMCDDA, b that the drug market is evolving, but we cannot be sure what circumstances are responsible for some individuals buying drugs online rather than using street markets Giommoni, It could be certainty, security, trust, computer skills, access to internet, being comfortable using cryptocurrency, avoiding street violence or the combination of those; unfortunately, our data do not allow us to say if this is the case for sure. There is evidence that more people turned to the Internet as the pandemic wore on, and the evidence suggests this was likely due to market adaptations rather than how people dealt with the strains of the pandemic. While our findings are telling and point to possible changes in drug transactions that may outlive the pandemic, we need to better understand the characteristics of the drug market realignment and what it means for law enforcement and policymakers. However, one thing appears likely: engaging in symbolic policing and band-aid solutions will disproportionately affect small-scale drug users and dealers and not lead to significant reductions in drug use. A number of scholars have discussed online drug markets prior to the pandemic e. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. As a library, NLM provides access to scientific literature. Am J Crim Justice. Find articles by James Hawdon. Find articles by Katalin Parti. Find articles by Thomas Dearden. Received Mar 1; Accepted Oct 25; Issue date Open in a new tab. In the past 12 months have you… Yes Percent Been treated unfairly 1, Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel. Had a death or hospitalization of a close friend or family member.

Hamilton Island buying Heroin