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Official websites use. Share sensitive information only on official, secure websites. The rapid increase of fatal opioid overdoses over the past two decades is a major U. The crisis has transitioned from pharmaceuticals to illicit synthetic opioids and street mixtures, especially in urban areas. We identify three distinct epidemics prescription opioids, heroin, and prescription-synthetic opioid mixtures and one syndemic involving all opioids. These communities are less populated and more remote, older and mostly white, have a history of drug abuse, and are former farm and factory communities that have been in decline since the s. By contrast, heroin and opioid syndemic counties tend to be more urban, connected to interstates, ethnically diverse, and in general more economically secure. The urban opioid crisis follows the path of previous drug epidemics, affecting a disadvantaged subpopulation that has been left behind rather than the entire community. County data on opioid epidemic class membership are provided. Over the last two decades, fatal opioid overdoses have increased dramatically to become a major public health crisis in the United States Jalal et al. Two-thirds of all overdose deaths involve opioids, killing roughly 47, people in and close to , since CDC Unlike previous drug epidemics that have proliferated in inner cities, the opioid crisis has affected smaller communities. Fatal overdoses from opioids have increased by over percent in both micropolitan and rural non-core counties, and by nearly percent in metropolitan ones CDC However, metro deaths have risen rapidly since due to fentanyl overdoses, and will soon eclipse non-metro opioid fatalities CDC The opioid epidemic has placed heavy burdens on hospitals and emergency rooms Weiss et al. The opioid crisis has also rapidly evolved from a prescription problem to one involving a myriad of opioid substances CDC ; Ciccarone ; Scholl et al. In this sense, the crisis is like the multiple-headed Hydra of ancient Greek mythology, involving heroin, prescription, and synthetic opioids. As communities sever one head of the opioid problem, a new drug appears to take its place. For example, regulation of prescription opioids in many states has not slowed the crisis, as heroin and synthetic opioids from abroad have rapidly filled the void DEA ; Monnat Although the opioid crisis is covered extensively in the media and popular press, rigorous academic research on its social, structural, and spatial determinants is still emerging Dasgupta, Beletsky, and Ciccarone ; Monnat and Rigg ; Spencer et al. There are several unanswered questions limiting our understanding of this public health and social problem, hence limiting community and policy responses. Is there a single opioid overdose epidemic or a series of multiple epidemics? Are opioid epidemics linked to drug risk factors like persistent drug overdoses, over-prescribing, and work disability; or driven by socioeconomic disorganization from job losses, poverty, and general community decline? Are there differences across rural and urban contexts? To address these questions, our exploratory analysis has three objectives. First, we document trends in drug overdose mortality by opioid type across the rural-urban continuum. Second, we identify distinct opioid overdose mortality epidemics termed classes at the county-level over time using latent profile analysis LPA. Third, we describe the demographic, drug risk, social disorganization, and economic characteristics of communities affected by different opioid overdose epidemics. Our analysis contributes to the rural health and community development literatures by speaking to place-based drug problems, their distribution, and dynamics. The public health burden may fall more heavily on smaller communities as they have limited health, social, and criminal justice resources to respond to drug crises Rigg, Monnat, and Chavez Moreover, rural communities are not monolithic, having diverse socioeconomic and drug risk conditions Monnat Evidence shows that drug addiction epidemics undermine the social and economic vitality of a community, the same vitality that is key to preventing drug epidemics, leading the community into a downward spiral Rigg and Monnat ; Weisburd et al. This has led many state and local officials to see opioid abuse as the most pressing problem in rural America Haegerich et al. The geography of the U. Rural opioid overdose mortality exhibits high spatial heterogeneity, as shown in Figure 1. Large swathes of the upper Midwest and Great Plains have some of the lowest rates of fatal overdoses. At the same time, Appalachia and parts of the Ohio River valley post some of the highest fatality rates in the nation, and have for some time Jalal et al. Even rural places with a minor drug problem a decade ago are now experiencing high opioid overdose fatalities, in particular states in the Southwest, Eastern Great Lakes, and New England. Recent literature on the opioid overdose epidemic points to both compositional and contextual features of communities that are associated with spatial variation in fatal drug overdose rates. Compositional risk factors contributing to higher overdose rates include high rates of poverty, unemployment, disability, single parent families, divorce, and lower educational attainment Monnat et al. This work also finds that certain vulnerable demographic groups tend to have higher overdose rates, such as the elderly, military veterans, and Native Americans Monnat Extant research identifies several contextual factors that influence drug use risk, including social norms, neighborhood disadvantage, social capital, the physical environment, availability of health and social resources, and policy and regulation Dasgupta et al. Monnat finds that higher rates of opioid prescribing, fentanyl exposure, economic distress, reliance on mining and service sector employment, and persistent population loss are associated with higher fatal drug overdose rates among non-Hispanic whites. There appear to be strong linkages between macroeconomic conditions and fatal drug overdose rates. Case and Deaton suggest that the rise in fatal drug overdose rates over the past two decades is largely attributable to long-term changes, including progressively worsening labor market opportunities for individuals without a four-year college degree, marital disintegration and single-parenting, and reduced attachment to religious and other social capital promoting institutions. A large body of evidence shows that job loss and wage decline increase risk of depression and substance abuse Galea et al. For example, one study estimates that a one-percentage point increase in unemployment rates raises opioid mortality rates by 3. However, recent work questions the role of macroeconomic conditions on rising drug overdose rates. Ruhm finds that unemployment rates since the early s are only minimally associated with increase in drug overdose mortality rates at the county level. An emerging body of research has begun to examine the relationship between drug mortality and employment in specific economic sectors. Betz and Jones find that both job and wage declines in lower skilled industries are associated with higher opioid overdose mortality rates, especially for rural white men in goods-producing sectors, but also for African Americans and women who work in the service sector. They also find that wage growth is an important protective factor, which suggests job quality e. The twin forces of industrial decline and farm concentration have eliminated many middle-skill and middle-wage jobs and replaced them with low-skill and low-wage ones in leisure and personal services, especially in non-metropolitan areas, resulting in growing poverty and inequality David and Dorn ; Lobao and Stofferahn ; Moller, Alderson, and Nielson ; Peters Economic restructuring has not been uniform across the United States, leading to poverty in some places and prosperity in others Peters For example, shocks to manufacturing labor demand have disproportionately negative impacts on male employment and wages, leading to a disproportionate increase in male mortality from drug and alcohol poisoning Autor, Dorn, and Hanson Economic decline alone is insufficient to account for the rise in opioid and other drug problems. Criminologists view social disorganization as a key linkage between community economic disadvantage and local crime-related and deviance outcomes. Disorganization theory is an umbrella term for a number of related conceptual models linking social order to crime, with the three most common outlined below Bruinsma et al. The classical model of social disorganization, grounded in Chicago school sociology, links crime and social problems in a community to lower socioeconomic status, high residential mobility, and ethnic heterogeneity, and has been expanded to include population density, urbanization, and family disruption Bursik and Webb In short, disadvantaged communities have more structural barriers that limit prosocial behavior of residents. The social capital model of disorganization incorporates concepts of social trust, social networks, and organizational participation into the expanded classical model Sampson and Groves These elements are thought to create shared norms and values in the community, which in turn reduces crime and social problems. A later iteration of social disorganization theory, the collective efficacy model, builds on the social capital model to include informal social control and shared community understandings Sampson, Raudenbush, and Earls The model links how residents work together to keep and maintain order; and how accompanying ties formed by community investment enable the co-production of public safety by police and the community Bursik and Grasmick ; Weisburd, Feucht, and Bruinsma Specifically, communities affected by acute economic distress tend to turn inward, causing local social networks to atrophy which leads to weakened informal control Berg and Rengifo ; Hochstetler, DeLisi, and Peters Decades of research in criminology supports the various models of disorganization theory Sampson et al. This body of work finds increased crime to be positively associated with greater poverty and inequality, residential mobility, and ethnic heterogeneity. Together, these structural factors undermine informal social controls among residents, weaken trust in the criminal justice system, and give rise to disruptive community norms, all of which are associated with higher rates of crime and deviance Hochstetler, Peters, and Copes ; Weisburd et al. Evidence indicates that drug markets, as indicated by accidental overdose deaths, are spatially linked to disorganization in large cities Martinez, Rosenfeld, and Marez Further, self-reported community disorganization helps predict substance use and dependence Berg and Lauritsen ; McLean However, relatively little is known about the effects of disorganization on drug-related outcomes in rural areas Weisburd et al. We disaggregate four opioid mortality measures : heroin or opium overdoses; prescription opioid overdoses including methadone; overdoses from synthetic opioids or unknown narcotics; and multiple-cause deaths that include two or more opioid drugs or opioid-related behavioral disorders. Opioid mortality rates per , population based on Census are by residence of the decedent and are pooled over three-year periods between and to reduce annual fluctuations in small counties, as is standard in public health research Rothman, Lash, and Greenland One limitation is a recognized opioid overdose undercount on death certificate data, where synthetic opioid analogs go undetected in toxicology reports Ruhm Since there is no agreed upon method to correct this problem, our measures represent a lower-bound estimate of opioid mortality. For our second objective, LPA is used to identify opioid overdose epidemics by classifying counties into classes based on mortality rates per , across four opioid types heroin, prescription, synthetic, and multiple opioids in three time periods —, —, and — Mortality rates are normalized using z -scores to facilitate comparisons across opioid types. Like all classification techniques, LPA is sensitive to extreme score, so data are Winsorized at the 0. LPA is part of a broader technique called finite mixture models. The procedure assumes observed data from a multivariate mixture collected from a number of mutually exclusive profiles, each with its own distribution Lanza, Tan, and Bray We refer to the profiles as classes as this term is more common across disciplines. LPA offers some advantages over more common classification techniques like hierarchical cluster analysis Morgan The LPA is identified by having positive degrees of freedom, an information matrix that is positive definite, and uncorrelated indicators Abar and Loken ; McLachlEin and Peel Our third objective is to describe the demographic, drug risk, social disorganization, and economic characteristics of counties affected by different opioid overdose epidemics, and compare these across metropolitan and non-metropolitan contexts. A multivariate general linear model traditionally MANOVA is used to explore unconditional mean differences across a number of Variables using the Games-Howell test, which is robust to unequal group sizes and Variances Johnson and Wichern Current indicators and change from are primarily obtained from the U. We use the terms non-metropolitan, non-metro, and rural interchangeably. A number of locational factors are also explored. Natural amenities have been found to either help or hinder economic development Pender et al. Density of interstate road lengths per square mile is calculated using ESRI files to model transportation access and drug trafficking corridors DEA Drug risk factors are selected based on extant research Monnat ; Rigg et al. Adjacent opioid overdose mortality captures spillover across neighboring counties, using queen contiguity spatial lags. Fatal non-opioid drug overdoses measure not only general drug abuse in the county, but also underreporting of unidentified opioid overdoses on death certificates. Prescription opioid dispensing rates per people are used to measure supply, taken from QuintilesIMS Transactional Data Warehouse with modifications. We use the social capital model of social disorganization to identify economic, community, and crime correlates Bruinsma et al. From the U. Census, we include the person poverty rate, the income gap to measure inequality quotient of income shares owned by the top and bottom 20th percentiles , and the percentage of housing units that are vacant to measure physical disorganization. Although single-headed families are found to be a significant predictor of drug overdoses in previous studies, we drop it from consideration due to its high correlation with poverty. Social capital measuring organizational capacity includes the number of civic, work, and non-profit groups per 10, Social capital measuring engagement and participation includes voting and Census response rates. Items for both measures are converted to z -scores and summed, using data from the Northeast Regional Center for Rural Development. Lastly, employment and economic restructuring is measured using current employment shares from the — ACS and change from the Census. We include change over two decades to capture long-term consequences of economic restructuring on opioid overdose mortality. Census employment is defined as employed persons 16 years and older by place of residence in two-digit NAICS industry codes. Some service sectors are aggregated for comparability to data Peters Our use of place-of-residence person employment is unique from existing studies that use place-of-work job counts. The former is preferable since it is consistent with CDC mortality data that are also reported by residence. Blue-collar employment sectors, with NAICS codes in parentheses, include: agriculture, forestry, and fishing 11 ; mining 21 ; construction 23 ; manufacturing 31—33 ; and transportation and warehousing 48— Lower skilled jobs characteristic of the post-industrial economy is measured by retail trade and leisure services 44—45, 71—72, Healthcare and social assistance 62 employment is used to control the presence of these services in the county. Our first objective describes the opioid overdose crisis and how it has changed across the rural-urban continuum, which is summarized by four charts in Figure 2. Deaths from prescription opioid overdoses rose sharply during the s, rising from around one death per , in to a peak of four to seven deaths by — One reason for their widespread overdose is that prescription opioids have a legal distribution network in nearly every community, namely clinics of health professionals and retail pharmacies. Quinones was among the first to describe a tripartite system of aggressive yet false marketing of so-called non-addictive opioids by pharmaceutical firms; overprescribing by either unknowing or unethical physicians; and lax oversight by government officials, especially state Medicaid and professional licensing. In recent years, prescription deaths have fallen or remained stable, likely due to more strict prescribing rules and greater availability of cheaper illicit opioids like heroin DEA , However, prescription drugs still account for most opioid deaths, except in the largest cities. The prescription overdose crisis hits rural areas hardest, with rates peaking at 7. Semi-rural and micropolitan areas follow a similar trend, but with slightly lower base rates. In short, the prescription drug crisis seems to be waning and deaths will most likely continue to fall. Synthetic Opioids Include Unknown Narcotics. The second wave substituted heroin, white powder in the east and black tar in the west, for prescription opioids. Heroin is considered an illicit drug under federal law because it has no accepted medical use, unlike prescription pain-killers. Heroin overdoses were low and stable until , when deaths began to rise rapidly in more urbanized places. Heroin is an attractive alternative for individuals addicted to prescription opioids because it is cheaper and more readily available, but it is unclear if limited supply due to pharmacy regulation drove heroin usage. Heroin overdose fatalities are a problem in larger metros, but are relatively rare in rural communities. Death rates peaked in — at 3. Most heroin enter through the southern border, as Mexican drug trafficking organizations DTOs now dominate the wholesale distribution of heroin in the U. DEA However, the heroin wave was soon supplanted, some say exacerbated, by synthetic opioids. The third wave is often called the synthetic opioid overdose crisis by CDC and others Ciccarone , but in reality it is a multiple opioid crisis. Synthetic opioids are manufactured entirely from inorganic chemicals, with the most common being fentanyl analogs e. According to federal drug enforcement data, prescription synthetics are tightly controlled and very little of it is diverted to illegal drug markets DEA Instead, most street synthetics are non-prescription analogs produced abroad. China is the primary source of synthetic analogs in the United States, shipped either in small quantities through the postal system, or in larger amounts to Mexico for distribution in the north. It comes across the southern border and through U. Most synthetics are powerful narcotics, with pure fentanyl times more potent and pure carfentanil 10, times more potent than morphine, with lethal doses as small as one milligram DEA Synthetic analogs are inexpensive to produce, and DTOs are replacing prescription opioids with synthetics to create counterfeit pills, unbeknown to the user, who Can easily overdose on these highly potent mixtures with unpredictable dosage. Synthetics are also used to replace more expensive heroin, often mixed with inert ingredients or other powered drugs like cocaine. Overdose deaths from synthetic and multiple-opioids have increased exponentially in urban areas since Synthetic death rates are highest in large metros and micropolitans about 4. In summary, the current opioid overdose crisis in the United States is driven by highly potent synthetic opioid mixtures due to their lower cost and greater availability. Our second objective is to identify opioid overdose mortality epidemics at the county level using LPA. The procedure classified 3, counties into six latent classes, each having a distinct distribution of opioid overdose mortality. Each latent class represents a distinct opioid epidemic. The initial LPA estimated five classes, but examination of class means indicated that the heroin class had two distinct subpopulations, with similar shapes but different elevations. For substantive interpretation, we split the heroin class into an above average group and a high group, resulting is six classes. Detailed results of the LPA are presented in the appendix. To ensure high internal consistency, we exclude any county not having a posterior probability i. Means of standardized opioid mortality rates in — and change from to across the six latent classes are presented in Figure 3 and Table 1. The spatial distribution of the opioid overdose mortality classes is shown in Figure 4. Unclassified Counties Not Reported. The remaining counties are classified into specific opioid mortality classes. More than half of high heroin counties are classified as non-metro Both the emerging and high heroin classes are widespread across the country, tending to follow interstates and known drug trafficking corridors DEA Deaths are also concentrated in two corridors following interstates, with one running from central Missouri through St. Louis to Chicago and the other running from El Paso north to Denver. The prescription opioid epidemic class of counties reflects the public narrative of the opioid crisis, with three-quarters of the counties in this class being non-metro Prescription overdose deaths in these places have grown steadily over the past decade and a half, with prescription mortality in — being 1. There is a noticeable absence of heroin in these places, likely reflecting remote locations away from drug trafficking corridors. Over one-third of counties in Tennessee, Oklahoma, Nevada, and Utah fall into this epidemic. Unlike heroin, prescription overdose deaths seem to follow state boundaries, indicating that different state regulations may be a factor. For the By contrast, in metro areas, synthetics play a much larger role. The preceding classes can be termed epidemics, as only one or two opioids are responsible for most overdose fatalities. However, our analysis finds a group of counties with co-occurring epidemics that overlap and reinforce each other, what public health research terms syndemics Ciccarone ; Singer et al. The counties in the opioid syndemic class have coinciding epidemics involving prescriptions, heroin, synthetics, and mixes of the three. Non-metro syndemics also have above average rates of overdose fatalities from non-opioid drugs, potentially indicating an undercount of unidentified opioid substances on death certificates. As a share of counties, the opioid syndemic has hit the eastern one-third of the nation hardest. The northeast syndemic cluster includes Connecticut, Maryland, and Massachusetts. Another syndemic cluster is located in the greater Appalachia region, concentrated in Ohio, West Virginia, northern Kentucky, Maryland, and western Pennsylvania. This cluster also extends into eastern Indiana and southeastern Michigan. The southwest syndemic cluster is located in New Mexico, centered around Santa Fe. Distribution of opioid overdose classes varies across the rural-urban continuum as shown in Figure 5. The share of low opioid overdose counties increases as one moves from large metros to completely rural counties, accounting for over 60 percent of non-metropolitan non-adjacent counties. The emerging and high heroin classes together account for over 33 percent of metropolitan counties with over , people, and also in larger non-metro counties that are adjacent to metropolitans. The prescription opioid class becomes more common as counties become more rural, with the largest shares in non-metro counties under 20, people. Lastly, opioid syndemic counties trend with greater urbanization, with 10 percent of metros over one million people experiencing a syndemic. By contrast, syndemic counties are relatively rare in rural areas. Adjacent Denotes Metropolitan Adjacency. To understand the characteristics of rural and micropolitan counties affected by the current opioid overdose crisis, we conduct mean difference tests across a number of demographic, drug risk, social disorganization, and economic conditions identified in the literature. The non-metro results are presented in Table 2. Starting with demographics , non-metro opioid epidemic classes are more densely populated compared to the low overdose group, with the syndemic class having the highest population densities in , and the prescription epidemic class having the lowest. Most opioid epidemic places are older and less diverse than their low overdose counterparts having fewer shares of younger people under age 25, faster gains in elders over age 65, smaller shares of African Americans, and slow growing minority populations, notably Hispanics. However, rural prescription epidemic counties stand out by having more people of other races, in particular Native Americans. For locational factors, rural syndemic and heroin-related classes are more likely to be adjacent to metropolitan areas. Drug risk factors play an important role in distinguishing between places impacted by opioids from those that are not. Non-metro counties affected by the opioid crisis are located near each other geographically, evidenced by high adjacent mortality. In addition, drug overdose fatalities are high for other non-narcotic drugs, compounding the opioid problem in rural communities. Non-opioid fatalities are especially high in opioid syndemic and prescription-related classes, killing roughly 10 people per , versus 7 per , in the low overdose group. However, dispensing rates have been falling, suggesting more stringent regulation by government and less generous prescribing practices by healthcare providers. Worryingly, dispending rates are growing in emerging heroin communities, which may indicate a future heroin-prescription epidemic in the coming years. Pain prescriptions and work disability are found to be strongly correlated with opioid mortality in the literature Monnat We find evidence of this in multiple-opioid and prescription-opioid class counties, where disability rates are high and growing over time. Conversely, disability rates are lower in heroin-related counties, indicating that the opioid-disability linkage does not generally apply to heroin. In short, we find rural opioid epidemic counties to be spatially clustered, over-prescribed, work disabled, and have a growing fatal drug overdose problem, indicating that unknown opioid-like substances are circulating in the community. Social disorganization only affects the rural prescription opioid epidemic, not other classes. Prescription opioid counties are economically distressed with low labor force participation and high poverty rates. They possess lower social capital in the form of fewer civic, social, and non-profit organizations. Limited financial and social resources likely hinder the ability of these communities to effectively respond to the rural prescription problem. This finding is consistent with previous research implicating industrial decline for the rise in opioid deaths Monnat et al. More generally, non-metro counties impacted by opioid overdoses have falling labor force participation rates, indicating general economic distress as jobs have disappeared or people have stopped looking for work. We next turn our attention to metropolitan counties, where socioeconomic differences are presented in Table 3. Demographically , most metro opioid epidemic classes are similar in population density, the exception being prescription opioid counties that have very low densities for an urban area Syndemic and prescription-related opioid epidemic classes tend to have fewer youth, fewer Hispanics, and slower growing minority populations compared to the low overdose group and heroin-related classes. In terms of location , prescription opioid epidemic counties occur in suburban or exurban portions of metropolitan areas, are less likely to contain a principal city, and have lower miles of interstate roads. By contrast, opioid syndemic and heroin-related counties look more like typical metropolitan areas, with high population densities, primary cities, and more interstate highways. Metro drug risk factors are similar to rural and micropolitan counties. Work disability is a problem in the syndemic and prescription opioid classes, but is largely absent in emerging heroin and low opioid overdose metros. The well-established linkage between dispensing rates and work disability is only found to occur in prescription opioid metros. There are no statistical differences in non-opioid drug overdoses across metro epidemic and low opioid counties. Social disorganization is only apparent in metro counties impacted by prescription opioids. These counties have depressed labor markets with low and falling labor force participation rates, stagnant incomes with higher poverty yet slower growing inequality, physical disorder with more vacant housing units, social disorder by gains in property crime burglary, larceny, vehicle theft, and arson , and less social capital with fewer non-profit, civic, and social organizations. All of this points to metro prescription opioid counties being economically and socially disadvantaged. However, one bright spot is growing community engagement since , suggesting that residents have become more active in local affairs. Despite the severity of opioid overdose deaths, other metro opioid classes show few signs of economic distress. For example, metro syndemic and heroin-related class counties have high rates of labor force participation, and exhibit no differences in poverty, crime, or social capital. There are also few major differences in employment structure. Manufacturing is in decline in most high opioid metro counties, similar to what is observed in non-metros. In particular, metro counties in the prescription opioid class are more manufacturing dependent compared to other groups, having the largest manufacturing job share yet also experiencing the fastest decline since The objectives of our exploratory analysis are to describe fatal opioid overdose trends, identify opioid mortality epidemics at the county level, and to describe characteristics of opioid overdose epidemics across the rural-urban continuum. We summarize our key findings and discuss their implications below. To begin, the opioid crisis is no longer a prescription crisis , or even a heroin crisis, but has transitioned to synthetic opioids and multiple-opioid mixtures. This transition began in and has continued apace, resulting in higher fatal overdose rates in urban areas. Next, there is not a single opioid overdose epidemic, rather multiple and overlapping ones. About 25 percent of counties nationally is severely impacted by opioid overdose fatalities, but not in the same manner as we identify distinct epidemics. The prescription opioid epidemic is the most common 8. A number of counties have transitioned to a synthetic-prescription mixture epidemic 6. Lastly, a small share of counties 4. Many central Appalachia counties suffer from an opioid syndemic, where the crisis began in the s and has only worsened since. Some common characteristics connect counties impacted by opioid overdose deaths across the rural-urban continuum. First, non-metropolitan opioid overdose epidemics also have a non-opioid drug overdose problem. While it is possible that fatal overdoses Can be linked to actual non-opioid drugs such as cocaine, methamphetamine, or prescription sedatives , it is more likely such deaths are attributable to unknown opioid-like substances that escape detection by rural medical examiners, who may not have the resources to run more detailed toxicology tests. Ruhm argues that the official CDC opioid overdose count is underreported due to these undetected opioids. Our work only partially supports this argument and only in non-metropolitan counties. Second, places affected by opioid overdose epidemics tend to be older, less diverse in terms of race and ethnicity, and have a declining industrial base. These two findings are consistent with existing public health research Monnat ; Rigg et al. Prescription opioid and synthetic-prescription opioid mixture epidemics tend to occur in smaller and more remote counties. These include suburban and exurban portions of metropolitan areas, as well as sparsely populated rural counties distant from urban centers. They are also less connected to interstate highways and are located in regions with low mountainous, making these places more remote and isolated. Remoteness can hinder economic development and result in local economies dominated by resource-based industries that have high rates of workplace injury and disability BLS ; Pender et al. However, remoteness also limits the presence of DTOs that supply illicit opioids like heroin and synthetics, leaving narcotics supplied by local pharmacies as the primary source DEA By contrast, opioid syndemic counties are more densely populated and more connected to transportation infrastructure , allowing DTOs based in larger cities to supply a wide array of illicit opioids, other drugs, and multiple-drug street mixtures. The linkage between drug networks and urbanization is well supported in criminology Berg and Lauritsen However, we find the disability-dispensing-ouerdose pathway only holds for rural and micropolitan counties, and not for metropolitan ones. Rural industrial decline left a legacy of unemployed and underemployed people with some form of work disability. It is a plausible treatment for work-related pain, likely involving opioids prescribed by a health provider, helped start the cycle of opioid addiction that would culminate in the current opioid overdose crisis in rural America Frasquilho et al. Reasons why we fail to detect this linkage in metropolitan counties may be due to greater availability of non-drug pain management options in larger cities, stricter prescribing and dispensing practices in urban areas with a history of drug crimes, and a larger and more diversified job base in less injury-prone sectors. More research is needed to address this inconsistency between our findings and extant literature. Further, evidence for this narrative is stronger in metropolitan than in rural and micropolitan counties. For example, metro counties in the prescription opioid class show the greatest signs of drug risk high dispensing and disability , economic distress high poverty and low labor participation , injury-prone blue-collar job losses especially mining and manufacturing, see BLS , and social disorganization vacant homes, low social capital, and growing property crime. Non-metro counties score high on economic distress, but not on social disorganization. These communities are sparsely populated, remote, older and mostly white, have a history of drug abuse, and are former farm and factory communities that have been in decline since the s. Opioids cure likely obtained from local pharmacies and illegally traded among drug users, separate from DTOs. By contrast, high heroin and opioid syndemic counties tend to be more urban, connected, diverse, and in general more economically secure. The urban opioid crisis likely follows the path of previous drug epidemics, where DTOs sell illicit drugs to certain segments of the population, typically existing drug users or the urban underclass. It is disadvantaged subpopulations in the community, not the urban community itself, that has been left behind and vulnerable to opioid addiction. In conclusion, our findings point to several policy recommendations, despite some methodological limitations. Second, tighter regulation of opioid prescribing and dispensing practices will have little effect on the current overdose crisis, now dominated by illicit drugs like heroin and synthetic opioids. Further, greater drug interdiction efforts to stop the flow of illicit opioids will also meet with limited success. Previous supply-side initiatives have not stopped drug usage in the United States. Instead, we argue that policy should reduce the demand for drugs domestically. For example, the PROSPER program links adolescents and parents within local organizations in particular schools to promote prosocial interactions to reduce substance abuse and other social problems. However, such initiatives require long-term investments that are unlikely to have an immediate effect on overdose fatalities. In summary, multiple opioid epidemics require multiple intervention strategies. Our analysis provides needed information to communities allowing them to better understand their local opioid problem and the socioeconomic conditions linked to it. To this end, we have provided a data file listing the opioid epidemic classes for every county in the conterminous U. We thank the reviewers for their constructive comments that focused and improved our manuscript. Expectation-maximization is used to obtain maximum likelihood a posterior estimates using 10, starting values Marsh et al. The sample size adjusted Bayesian information criterion BIC is a relative fit index based on log-likelihoods, adjusted for parameters and sample size, with lower values indicating better fit. The rate of decrease in BICs slows between classes six and eight, indicating a range of ideal solutions. All classes exhibit good separation based on relative entropy scores, where values above 0. Both tests are non-significant at the sixth class stage, indicating the presence of five classes. We decided that the two heroin classes are substantively different and favor the six-class solution based on interpretability. Notes: BIC is the sample size adjusted Bayesian information criterion. First, independent cities in Virginia with populations under 65, are merged back into their respective counties, resulting in 29 fewer county-level equivalents. Second, Broomfield County in Colorado, newly created in , is disaggregated back into its four original counties based on population-weighted geographic shares. The above modifications result in a time series of 3, counties back to , down from the original 3, counties, but with no loss of information as data are merged and not dropped. All data used in this study conform to these spatial units. International Classification of Diseases ICD codes defining opioid overdose and use mortality include: drug poisonings X40—44, X60—64, X85, or Y10—14 plus the presence of one or more opioids T Mortality is disaggregated by heroin or opium T By including behavioral deaths, we expand upon the CDC opioid overdose definition, but this raises mortality counts by just under one percent or around 1, additional deaths nationally between and LPA provides hypothesis tests of class structure and model fit statistics, whereas cluster analysis relies on subjective heuristics. Cluster analysis can result in very different solutions depending on the type of distance metrics and linkage rules used, whereas LPA relies on a single estimation technique. More importantly, LPA estimates classification uncertainty using posterior probabilities obtained using Bayes theorem. By contrast, cluster analysis incorrectly assumes perfect certainty in classification, failing to recognize that cases may fit into multiple clusters. ACS estimates for most counties exhibit relatively low error, even in counties with small populations, with most coefficients of variation around 25 percent and only a few nearing 50 percent. Variables with larger errors include agriculture and mining employment. We drop two counties Kenedy and Loving counties in Texas due to large errors on many variables. QuintilesiMS data only include prescriptions obtained from retail pharmacies and exclude high-volume prescribing pain clinics. Missing cells are imputed using a Markov Chain Monte Carlo model with multiple imputations Carpenter and Kenward All imputed values exhibit high consistency, with coefficients of variation below 33 percent. First, data were just released in January after a long delay, and data have yet to be released. To address this issue, we mean substitute data as the average of and Second, missing cells due to non-reporting to FBI are addressed in a number of ways. Dlinois and Florida did not report any crime data to FBI for a number of years, so crime counts are taken from state agencies. State reports generally adhere to FBI guidelines for index crimes e. Next, attempts were made to impute other missing cells using Markov Chain Monte Carlo models, but this failed to provide consistent values coefficients of variation were typically over percent. Finally, missing cells are substituted with state averages disaggregated by urban influence code. One major limitation is a recognized opioid overdose death undercount, where official CDC tallies are estimated to be underreported by 20 percent Ruhm There is no agreed upon method to correct this problem, thus official CDC counts used in our analysis should be considered as a conservative estimate of opioid overdose mortality. A second limitation is relatively poor classification of counties into the high heroin class. We urge caution in drawing broad conclusions from our analysis on the correlates of the heroin epidemic. Future research should explore ways to address these two issues. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. Rural Sociol. Published in final edited form as: Rural Sociol. Find articles by David J Peters. Find articles by Shannon M Monnat. Find articles by Andrew L Hochstetler. Find articles by Mark T Berg. Issue date Sep. 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Hydra market’s servers, $25M in bitcoin seized by German police in dark web sting

Hydra buy Heroin

On an October morning in , in a town on the outskirts of Moscow, senior police investigator Evgeniya Shishkina was leaving home when she was ambushed by a gunman. Lieutenant Colonel Shishkina took a swing at her assailant. He slipped, but shot her in the stomach. As she lay on the floor he got up and shot her in the neck. Russian police and an investigation by the BBC allege the shooter was hired on an illegal drug trading platform known as Hydra, by a Russian hacker who ran one of its online drug shops. As Russian police continue investigating the murder of their colleague, the sheer size and reach of Hydra, which serves up drugs to Russians and post-Soviet republics, has come under the spotlight. But it is also a dark web drug enterprise like no other. Hydra has a whopping 2. The largest Western dark web market, AlphaBay, which closed in , was thought to have , registered users at its peak. This dwarfs its dark web counterparts in the West. Hydra represents a new kind of dark web marketplace. But there are innovations. Hydra has a strict way of doing business and code of conduct overseen by a central hub. While in other markets vendors pay once to open an account, on Hydra every one of its estimated 5, shops has to pay a monthly rent. Trusted Sellers must have racked up at least 1, transactions and customer disputes should not exceed seven percent of the total number of orders per month. Hydra has its own team of chemists and human guinea pigs to test each product and medics on standby to give safety advice. There is a subforum where these test results are posted, complete with graphs, analysis, and photos. Anyone trying to pass oregano as high-grade chronic will get kicked off the site. No fentanyl is allowed, and neither are weapons, hitmen, viruses or porn, although drugs, fake passports, dodgy SIM cards, and counterfeit cash are sold. On the whole, these rules appear to be obeyed, although the investigation into Lt. Dead drops from Russian drug web marketplaces were first reported in , but under the auspices of Hydra the system has proliferated. These dead drops can be anywhere from tree hollows, street bushes, round the back of apartment blocks or electrical transformer boxes, in crowded public locations, near metro stations or local forests. On completing the online transaction, buyers are sent coordinates, photos, and directions where to find the buried treasure. For example: go to the north entrance of the park and look under the third tree on your left. After going on this little quest, buyers have got 24 hours to confirm they have the goods and leave a review. And with business booming, Hydra has created a whole new profession for young Russians. They in turn get paid via the same anonymous means. Once they have hid 6, rubles worth of treasures, they can start earning. Galina was paid commission depending on the weight and type of drugs on each drop. But there were times she did 30 or At first she worked with hash, MDMA, and amphetamines, then almost exclusively with mephedrone, a drug that has become increasingly popular in Russia over the last decade. Take it home, re-pack it there. This is a very long and boring exercise, but I could decide how many drops of what weight I wanted to do and it was very convenient. Usually I would make 10 drops of one gram, 10 of two grams, and go lay them out, leaving the rest till next time. As soon as someone makes an order, they get the GPS coordinates. The second task of a dropper is taking a photo and writing a description and uploading the goods onto the shop site. Ten packages usually took her 30 minutes. But since then it has been updated and revised. The bible advises droppers to use encrypted phones so police cannot track previous drops and map-downloading tools to mark drops without having to go online. Unsurprisingly it tells grasshopper-level droppers to avoid drawing attention to themselves. It would be weird if someone sees an office manager crawling around the bushes. Bad places are near schools, cemeteries and police stations because they can draw unwanted attention , apartment block courtyards because the gates might be closed when the customer gets there , and even gutters unless packages are waterproofed. You can either go for a walk, looking for places to hide the stuff, making drops and taking photos as you go. The speed at which you do your job is not as important as efficiency. Lawyer Arseny Levinson runs the legal aid service Hand-Help. According to his analysis of Russian Ministry of Justice statistics, more than half of those convicted of drug trafficking in were years old and students. He says this is a lot to do with Hydra droppers. Yandex is a big online food order and delivery service in Russia. He decided to become a dropper after leaving the army and spotted the advert to be a kladman while buying drugs online. At one point he said he was doing 70 drops a day, using the money to fit out his apartment with brand new furniture. Namely adrenaline. That feeling when you balance all the time on the verge of being caught. Because of his love of forests and parks, he used those to bury his drug stashes at night when it was quiet. But all the evidence points to something of an online takeover. Shortis said Hydra is a more multifaceted and harder to contain beast than other online drug market sites. This means that whilst vendors in the West are often thought of as one person or a small group, vendors we see listed on Hydra are much more likely to be representative of a larger network of actors. Shortis said that Hydra is a lot more visible to police, but that does not make it easier to investigate. Petersburg delivering or collecting packages makes the Russian online drug trade much more visible than its western counterpart. This is very different from western cryptomarkets where the privacy of the delivery method mitigates public awareness of online drug markets. With every new shift in the criminal world comes a new bunch of parasites. For droppers who either get tracked by seekers as they make drops around town or whose hiding places are easily found by someone on the lookout for stashes, seekers can mean the sack. Seekers love the long Russian winters, when the snow reveals a myriad of hiding places across towns, cities, parks, and forests. Over the years the group has been accused of kidnapping addicts, chaining them up to make them go cold turkey, mob ties, and racism and xenophobia towards immigrants. But now CWD is refocusing its aim. Before when we were dealing with heroin, of course it was mainly gypsies and Tajiks, and every drug user was a seller as well. Now it can be Russians, anyone. A November police operation which netted nearly half a ton of various substances failed to catch even one store proprietor—just seven couriers. That brings us to another interesting question. Given what we know about Russian hackers and the Russian mafia , not to mention corruption within the DEA in the Silk Road case, could it be Hydra has friends in high places? But such cases are rare. We keep hearing cases about this, for example in Khakassia. After allegedly uncovering the scheme, year-old Yuri Zaitsev was himself charged with taking payoffs from drug dealers. When one of their dealers was caught, they personally intervened to have the charges dropped. For example, last July it was reported that two police chiefs were arrested for running an online drug ring in Moscow. And those are just a few such cases we know about. Russia now has more prisoners serving time for drugs than any other crime , a slot formerly occupied by murder. He got caught, as usual, by one stupid mistake: one day, he forgot to turn on the equivalent of a VPN or Tor on his laptop, so they traced his IP address and slapped handcuffs on him as he was boarding a flight to Kazakhstan. Still, quite enterprising for a year-old. There are two reasons Russia keeps spawning top cybercrooks like Misha. The first is that Russia has a lot of very smart, educated people. Russian universities produce great scientists, engineers, programmers, and mathematicians. The second is that the government actually uses hackers as privateers to do its bidding, which is why the same names pop up in cybercrime and national security investigations. Go, steal for Mother Russia! RAMP the Russian Anonymous Marketplace arrived on the scene in , building a platform where instead of messaging users back and forth you could simply browse the catalogue and press buy. Unlike the libertarian rhetoric bandied around on Silk Road, RAMP refused to support any agenda, knowing what happens to such outspoken parties in Russia. And unlike Silk Road, instead of taking commissions from each sale it charged every prospective drug merchant a flat tax for doing business on its platform. Hydra was born in as a merger of two smaller forums, Legal RC and Way Away, both specializing in synthetics. According to an investigation last year by Moscow-based online newspaper Lenta. Legal RC and Way Away were the last ones standing, and they had to stick together if they wanted to survive. But RAMP had major weaknesses from the outset. One, its refusal to commit to anything political extended to a ban on advertising. Hydra meanwhile had chemists working for its shops cooking up these novel substances, and a direct line to precursor suppliers in China, allowing it to corner the market in poorer areas where synthetics are more popular. Hydra struck back, shutting down the site with a string of DDoS attacks. A classic turf war broke out in cyberspace, except instead of car explosions and drive-bys it was a bunch of nerds hurling botnets at each other. One disloyal store was sold out to the feds as an example to others. Either way, with its main competitor out of the way, Hydra moved to consolidate its gains. It embarked on an aggressive publicity campaign, posting videos on YouTube, buying databases of phone numbers and spamming them with texts, and absorbing existing drug rings, inviting them to join the party. Hydra now has thousands of online drug bazaars catering to every corner of the Russian Federation, from Vladivostok in the Far East to the freshly-annexed Crimea. There are even a few branches and shops operating in Ukraine, Belarus, Kazakhstan and other former Soviet territories. Cocaine has been coming in through St. Petersburg, allegedly protected by powerful figures , since at least the 90s, although its high price has put it out of reach of most Russians. Meanwhile, a heroin pipeline was set up from the poppy fields of Afghanistan through the ex-Soviet republic of Tajikistan: kilos of heroin were hidden onboard military planes, then distributed through the Tajik diaspora. Now, the rise of new synthetic drugs and online drug markets such as Hydra has meant just about anyone can set up shop as a drug dealer. Three years ago Galina decided to progress from dropper to shop owner. But where do the shops get their supplies? Cathinones and other synthetics are now massive in Russia, and Hydra sells do-it-yourself spice and mephedrone making kits, along with the raw ingredients imported from China. The chemists find what they need through their own channels; I only allocate them funds. According to Galina, vendors on Hydra are more likely to collaborate than compete with each other. But people choose not only on the basis of price, but also take into account the convenience of drops, the reputation of the stores and their specific wares. Shops try to occupy their own specific niches. In Moscow for instance, there are quite a few shops that deal with cocaine and expensive mephedrone, and there are shops that basically only sell marijuana. Like any business, the shops have a division of labour: someone runs the stash house, someone does accounting, someone tends to the ganja plants, and so on. But the life of a dark web vendor is a busy one and she rarely gets to unwind. She now employs a team of six young couriers. This is the main problem when finding workers. You can teach anyone how to make good drops over time. I ask Galina about her life outside Hydra. She says she has very little free time. But of course I need to relax. I visit bars and cafes, watch TV shows and documentaries. Sometimes I go visit friends in another city. She may have little spare time, but at least Galina has managed to stay out of jail, unlike the droppers who make up some of the 19, people who were convicted for drug dealing in Russia in He loves writing poetry, music. It all began when Sergey wanted a new iPhone. Turns out Sergey was doing a little more than flunking biology class. On the 26th June he was picked up with two friends trying to make a drop. Dropmen are charged under article of the Russian criminal code drug trafficking and can get slapped with jail terms of up to 20 years, even for relatively small amounts. Sergey was first hit with a seven year sentence, then another court raised it to 13 years. His 18 year old friend also got 13 years and the third teenager, aged 17, got five years. Finally in January of this year, after nearly two years of appeals and taking her case to the media, Oxana and her family managed to bring it back down to six. Like in America, convicts are used for cheap manual labour. Overpacked cells and non-existent healthcare is a great way to catch tuberculosis. Torture is common. Oxana showed me a recent photo where Sergey looks skinny and pale. He works six days a week sewing backpacks. So much grief and tears! New recruits can always be found. In January the MVD announced that a special unit would be formed to fight online drug trafficking. Did taking out Pablo Escobar lead to a drug-free Colombia? Hell no. Could Hydra be the future of drug dealing? Customers must go out into a city or countryside and search for their purchase whilst avoiding raising the suspicions of the police or other members of the public. Some customers may also have to travel great distances just to find their delivery has been stolen by people who are savvy to where their local dropper is making deliveries, or that the police are actively patrolling the area where the drop has been made. While Hydra is very popular in Russia, it is rarely discussed in western cryptomarket forums. In the Middle Ages in Russia, ordinary people brought to despair went to the woods and became outlaws. Now, they are hiding on the dark web to become drug dealers. By Matthew Gault. By Trone Dowd. By Dipo Faloyin. By Tim Hume. Share: X Facebook Share Copied to clipboard. Videos by VICE. Tagged: Crime , dark web , drug-dealing , News , russia. Things Are Going to Get Weird.

Hydra buy Heroin