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Spanish Town where can I buy cocaine
In this paper, we examine the socioeconomic factors that determine cocaine consumption in adults aged over 18 years in Spain. For data from household alcohol and drug surveys for the period — EDADES , , , we used, first, a decision tree to identify the main predictors of cocaine use and high-risk profiles of cocaine consumers and, next, a multinomial logistic regression model to explain cocaine consumption in terms of sex, age, marital status, employment status, education level, income, household size and perceived health status. The results indicate that the main predictors of cocaine use are marital status, sex, employment status, age, education level and household size. The main cocaine user propensity profile is a young single man with a low level of education and unemployed, who should, therefore, be the main target of campaigns for preventing illicit drug use.. It is estimated that between 3. Illicit drug use annually results in about , deaths worldwide and causes distress and suffering in many more millions. Illicit drug use also undermines economic and social development, promotes crime, instability and insecurity and spreads diseases such as HIV UNODC, Cocaine consumption trends vary between countries. Spain, in fact, consistently has the highest prevalence of cocaine use worldwide. Cocaine use represents a major health and socioeconomic problem in Spain. Analysing causes can shed light on the population segments more prone to using drugs and help to design suitable targeted prevention strategies. What are the socioeconomic circumstances that place an adult in Spain at higher risk of becoming a cocaine user than adults in other similar countries? Studies on the socioeconomic determinants of cocaine use in Spain are relatively recent. To illustrate, Royo-Bordonada et al. On the other hand, and using data collected between and , Pulido et al. Cocaine consumption is very costly for society as noted for a number of studies. For the region of Galicia NW Spain by Oliva and Rivera estimated—for data for addicts attending drug dependency centres in the Galician healthcare network—a cost associated with illegal drug use of around million euros in In this paper, we tried to find an explanation for the high level of cocaine consumption in Spain with respect to other countries. In particular, bearing in mind that the average age of onset in Spain is 21 years for powder cocaine and The second objective was to determine the weight of different factors in the decision to consume. Achieving both goals we expected to be able to predict cocaine use in Spain by classifying and applying rules and by evaluating influential factors. The surveys collected data between November and March , between November and March , and between November and April To identify predictors of cocaine use consumption patterns and population groups at risk, we used a decision tree model that graphically represented relationships between variables. This enabled us to describe cocaine user profiles and to identify complex structural relationships and so, in turn, identify combinations of predictors. Combinations of socioeconomic variables, which, in isolation, might not represent determining factors, identified propensities for cocaine use. As for the second objective, we used a multinomial regression model to isolate the socioeconomic factors that had the greatest bearing on the prevalence of cocaine use in Spanish adults. Our results indicate that the most important predictors are marital status, sex, employment status, age, education level and household size. Specifically, profiles of Spanish adult population most likely to consume cocaine are single inactive men aged 25—50 years with an income in the third decile and single men under 36 years old, with only a basic education level, and employed or unemployed. The regression model calculated weights for the factors selected in the decision trees as the best predictors of cocaine use. Our results indicated that living with a partner increases the probability of being a non-user by 1. The model also points to the statistically significant influence of other variables such as household size, health perception, employment status, education level and income level. The results allow us to conclude that cocaine prevention and education policies in Spain should be reoriented to especially target single middle-aged inactive men with a low level of education, bearing in mind that this target is particularly difficult to reach because these individuals have no fixed points of contact or support in universities or companies. The rest of the paper is organized as follows. In Section 2 we describe the decision tree and multinomial regression models used to explain cocaine use in socioeconomic terms; we also describe how data was collected and descriptively analyzed. In Section 3 the main results are presented and, finally, in Section 4 we discuss those most relevant from the point of view of the adoption of targeted policies aimed at preventing or reducing cocaine use in individuals at risk. To measure consumption of cocaine we counted the number of days cocaine was used in the 12 months before the interview. This resulted in four cocaine user categories, namely, non-users, occasional, regular and frequent users. A non-user Y 0 has never consumed cocaine or has not done so in the last 12 months, whereas an occasional, regular and frequent user has consumed cocaine on 1—9 days Y 1 , 10—29 days Y 2 , and more than 30 days Y 3 in the past 12 months, respectively. We studied user profiles and the influence of socioeconomic variables using decision trees and logistic regression. To analyze the predictive value of variables that may influence cocaine use we used a recursive partitioning model of decision tree. This nonparametric technique, which treats all variables as categorical variables, takes into account interactions between the data. We identify the most important predictive variables from the set of explanatory variables and classify individuals into risk groups. Because cocaine use is a categorical variable we used decision trees to graphically represent a set of decision rules. Starting from a root node which includes all the individuals , the tree branches out into different child nodes contain subgroups of individuals. It uses a recursive algorithm that successively partitions the original data in other smaller and more homogeneous subgroups using binary partition sequences. CHAID Chi-squared Automatic Interaction Detection Kass, , a recursive non-binary classification algorithm, applies the chi-square test as a criterion for partitioning and uses the threshold above statistical significance as the stopping rule. The estimated parameters of the model are obtained using the maximum likelihood method, which determines the estimate that maximizes the probability of non-consumption and of occasional, regular, and frequent consumption of cocaine, given the vector of explanatory variables. Finally, statistical significance is tested using the likelihood ratio test that follows a chi-square distribution, whereas goodness-of-fit is tested using the likelihood ratio index. As a measure of an individual's economic circumstances we used the net monthly income of their household. In the EDADES surveys, household income is recorded as a categorical variable with eight possible responses referring to income intervals. However, since we needed a continuous measure of income, we applied an interval regression model of information provided by the respondent regarding overall household data. We thus could estimate the numerical income value from the boundaries of the intervals where the quantities are located. We took into account sex, age, educational level no education, primary, secondary, and university , employment status employed, unemployed, and inactive and region of residence. Using records for 44, individuals from the , and surveys, we generated predictions for the individual net monthly income variable. To examine the determinants of cocaine consumption and user profiles, we first used a decision tree model and then a multinomial logit regression model with four types of explanatory variables, namely, individual characteristics, household characteristics, employment characteristics, and socioeconomic characteristics. The variables used in the regression model were as follows: sex female omitted , age, marital status single, partnered , household size, health perception good, fair, and poor , educational level no education omitted to avoid collinearity , primary, secondary, and university , net monthly household income, and employment status. For the polytomous cocaine use variable, we jointly considered powder cocaine and freebase cocaine use, categorized in terms of four possible values, namely, non-consumption, occasional, regular and frequent consumption. An occasional, regular, and frequent user has consumed cocaine on 1—9 days Y 1 , 10—29 days Y 2 , and more than 30 days Y 3 in the past 12 months, respectively. Our data—for individuals aged 15—64 years and for the period ——were taken from the EDADES household surveys for , and Galicia et al. EDADES surveys are two-yearly surveys administered to a representative national sample stratified according to a multistage sampling procedure. The surveys collect data on alcohol and drug use and also compile information on socioeconomic, sociodemographic and geographic characteristics, and on overall health and occupation. Our final sample was obtained as follows. Table 1 below summarizes descriptive statistics referring to the prevalence of cocaine use in Spain. In addition, Fig. Note : Omitted categories: females, basic education, good health. Cocaine use frequency distribution. Of the population aged over 18 years living in Spain, 3. Prevalence rates are To analyze the socioeconomic circumstances, we first estimated the continuous variable of monthly net household income by applying an interval-regression model to income intervals as described in EDADES, , and the dependent variable and age, age squared, sex, education level, employment status, and region of residence explanatory variables. The limit values of the household income intervals were reflected in the survey. Table 2 below shows the regression estimates for household income intervals for 44, individuals. Interval-regression model coefficients for income estimation purposes. Notes : Inference based on robust standard errors, without weights. Reference categories: Female, no education, inactive, and Region 1 Andalusia. Statistical significance p 0. The model is statistically significant according to the Wald test and chi-square likelihood ratio LR Chi 2. Given the net monthly household income for each, we obtain the distribution of cocaine use by income categories summarized in Table 3. Cocaine use rates by income categories. The prevalence of cocaine use irrespective of consumption level among adults in Spain ranges between 2. For all the income categories except the first decile, cocaine use increases with income level to peak at 4. From this point, prevalence decreases as income rises. Prevalence of cocaine consumption by sex and by income categories is shown in Table 4. Cocaine use rates by sex and by income categories. Table 4 confirms a higher rate for men, irrespective of income level. Among individuals aged over 18 years in Spain, rates of cocaine use whether occasional, regular or frequent are strikingly different between the sexes, at 3. Here we analyzed which variables or groups of variables sex, age, marital status, educational level, health perception, employment status, household size and income could be good predictors of cocaine use for persons aged over 18 in Spain. We examined decision tree rule sets and flows so as to classify and determine risk profiles see Fig. CHAID decision tree: root, node 2 and two child nodes 7 and 8. The first branch of the decision tree indicated marital status to be the main predictor variable; this resulted in two nodes, referring to individuals living with a partner node 1 and single individuals node 2. Referring to node 2, of the single individuals Node 2 branches into two nodes representing the sex variable, with men node 8 indicated as having higher use rates—4. Node 8 branches into the nodes representing employment status nodes 18, 19 and 20 , where prevalence of use is higher for single men who are unemployed node 20 , at 5. The next strongest predictor for cocaine risk is the age variable nodes 32, 33 and 34 , which branches into nodes representing the age groups 18—36 years, 36—44 years and 44—65 years nodes 32, 33 and 34, respectively. The highest rates of cocaine use—5. For age groups over 44 years nodes 33 and 34 , use rates fall significantly maximum 2. Node 32 branches into nodes representing education level nodes 46, 47 and node 47 is no education, node 48 university education and node 46 other , where the highest use rate for single men, aged under 36 years and employed, is when they have basic education levels node Finally, node 48 university education branches into nodes representing the household size variable, where the smallest household size node 55 is associated with a high use rate. The best predictor for cocaine use is marital status. The highest rate of frequent cocaine use 7. Finally, with respect to accuracy, the model correctly classifies approximately The decision tree classifies all the individuals in cocaine risk profiles by combining and grouping the explanatory variables. For all levels of consumption occasional, regular and frequent , we obtain the following three high-risk profiles for cocaine use: 1 Single men, 25—50 years old, inactive, and with an income of around euros per month 0. The prevalence of cocaine use is Single men, employed, under 36 years old, and with a low education level 1. Single men, unemployed, and with a low education level 0. To measure the impact of socioeconomic and demographic determinants of cocaine use in individuals aged over 18 years for each level of use, we calculated multinomial logit regression model coefficients see Table 5. Logit regression model coefficients. Notes : Reference categories: Female, inactive, good health, no education. The marital status, sex, age, employment status, and household size variables exert a statistically significant influence on cocaine use in individuals aged over 18 years in Spain. For certain cocaine use categories, furthermore, education, income, and health are also significant. The sex variable exerts a statistically significant positive influence on occasional, regular, and frequent cocaine use and a statistically significant negative influence on non-use. Men are far more likely than women to be cocaine users; in particular, being female reduces prevalence of use by 1. This result agrees with those reported by Merline et al. Age exercises a statistically significant positive influence on non-use and a statistically significant negative influence on the use categories. The older the individual the less likely they are to use cocaine. One explanation for this pattern is that cocaine is typically consumed in social and leisure settings that tend to be frequented by younger people and younger people are more likely to be drawn to new experiences. Each additional year older increases the likelihood of being a non-consumer by 0. Individuals with a partner are less likely to use cocaine than those without a partner. Living with a partner has a statistically significant negative influence on cocaine use occasional, regular or frequent , increasing the probability of being a non-user by 1. The explanation may be the fact that the negative consequences of cocaine use also affect an individual's partner. Also, if the partner is not a consumer, consumption is likely to be lower, since the partner would have to be excluded. Being unemployed has a statistically significant positive influence on occasional, regular, and frequent cocaine use. The weight of this variable is highest for the occasional use category and corroborates the results of Royo-Bordonada et al. By contrast, the influence of unemployment is significant and negative in the case of non-use. This result corroborates those of Green et al. Being inactive or unemployed means an individual with more leisure hours and, with more opportunities to be alone, he or she has more opportunities to consume drugs. The probability of consuming cocaine—most especially on an occasional basis—is reduced in larger households. Normally, households are typically composed of members of different generations and probably include any or all of a partner, siblings, parents or children, so cocaine use may be difficult to share. Living with other people also reduces the risk for cocaine use because individuals may wish to avoid harming the people close to them. Education level is statistically significant for the frequent use category, with better educated individuals less likely to be frequent users. This result is consistent with results reported for U. The explanation is that educated individuals typically are more knowledgeable and aware of the repercussions of drug use. Education level has no significant influence on the other use categories, however. Whereas frequent consumption may be interpreted as causing physical and mental deterioration, occasional or regular use may be interpreted as diversion. Better educated individuals usually have more intellectual resources and are more likely to exercise the self-control necessary to avoid becoming addicted to cocaine. Net monthly household income has a statistically significant positive influence on non-use Fig. Cocaine non-use is more likely at higher incomes and occasional cocaine use falls as income levels grow. Indeed, a positive correlation between cocaine use and GNP per capita for 62 countries is reported Saiz, ; UNODC, , confirming greater cocaine use in wealthier countries. For a sample of men aged 18—45 years resident in five U. States, a statistically significant negative relationship between daily drug use and income level was confirmed Buchmueller and Zuvekas, We conclude that once cocaine use becomes regular or frequent, the income variable is no longer statistically significant, as the addicted individual will consume cocaine irrespective of their income. Impact of household income on non-use of cocaine. Impact of household income on occasional use of cocaine. For individuals who perceive their health to be fair, the probability of being a non-user is lower by 0. Individuals who perceive their health to be good tend not to be cocaine users, as they are probably fully aware of the implications for health. Similarly, if health is perceived to be poor, then frequent cocaine use is higher, probably for the same reasons. In this paper we analyzed the socioeconomic determinants of cocaine use by adults aged over 18 years in Spain in order to profile the population segments at greatest risk. We report a prevalence of cocaine use whether occasional, regular or frequent in Spain of 3. Decision tree analysis yielded information on factors with greater predictive power and enabled us to classify high-risk cocaine use profiles. A CHAID-type classification tree indicated the main predictors to be marital status, sex, employment status, age, education level, and household size. The individuals at greatest risk were indicated to be 1 single men, inactive, 25—50 years old, and with an income of around 1, euros per month; 2 single men, employed, under 36 years old, and with a basic education; and 3 single men, unemployed, under 36 years old, and owning a basic education. Prevalence rates for these profiles were These three groups accounted for 1. Multinomial logistic regression indicated the determinants for occasional, regular, and frequent cocaine use to be sex positive for men , marital status negative for having a partner , employment status positive for unemployment , household size negative for a larger household , and age negative for older age groups, with prevalence falling in line with increasing age. In addition, higher education levels are associated with lower levels of frequent use. Finally, individuals who perceive their health to be poor have a higher rate of frequent cocaine use. Monthly net household income has a statistically significant effect on non-use and occasional use. The higher the income level, the higher the probability of non-use and the lower the probability of occasional use. No significant differences were observed according to income levels, however, for regular and frequent use. When consumption acquires a certain frequency and the individual becomes addicted, it would appear that income is no longer a determining factor. Globally, our results would suggest that cocaine prevention and education campaigns in Spain should be reoriented to focus on single men aged under 36 years with a low education level living in small, low-income households. Understanding fully the consequences of cocaine use for an individual's own health and for their family may be decisive in the choice to use cocaine. Antelo and J. The subpopulation which consumes freebase cocaine has lower education levels, higher unemployment rates, more problems with justice, larger consumption levels of cocaine, and higher prevalence in the use of other illegal drugs.. The sample of 44, individuals refers all individuals with socio-demographic information that we can use to calculate their income level. Of these, 43, individuals have all the information about consumption of cocaine.. The difference is explained by the fact that we measure use of powder and freebase cocaine in the last 12 months for individuals aged 18—65 years, whereas EDADES refers only to powder cocaine consumed by individuals aged 15—65 years.. ISSN: Exportar referencia. DOI: On cocaine consumption: Some lessons from Spain. Descargar PDF. Manel Antelo a ,. Autor para correspondencia. Table 1. Table 2. Interval-regression model coefficients for income estimation purposes.. The main cocaine user propensity profile is a young single man with a low level of education and unemployed, who should, therefore, be the main target of campaigns for preventing illicit drug use. Palabras clave:. JEL classification:. Texto completo. Variable Definition Mean Std. Figure 1. Variables Coefficient Std. Table 3. Table 4. Figure 2. Table 5. Figure 3. Figure 4. Buchmueller, S. Drug use, drug abuse, and labour market outcomes. Health Econ. Galicia, S. Ten years of emergency attendances for cocaine-users in Spain. Med Clin. Gill, R. Green, E. Doherty, H. Reisinger, H. Chilcoat, M. Social integration in young adulthood and the subsequent onset of substance use and disorders among a Community population of urban African Americans. Addiction, , pp. Harder, H. Cocaine use and educational achievement: understanding a changing association over the past 2 decades. Public Health. An explanatory technique for investigating large quantities of categorical data. Merline, P. Schulenberg, J. Bachman, L. Substance use among adults 35 years of age: prevalence, adulthood predictors, and impact of adolescent substance use. Public Health, 94 , pp. Oliva, B. Los costes sociales del consume de drogas ilegales en la Comunidad de Galicia. Pulido, M. Brugal, L. Ballesta, G. Barrio, M. Bravo, et al. Gac Sanit. Royo-Bordonada, J. Cid-Ruzafa, J. Drug and alcohol use in Spain: consumption habits, attitudes and opinions. Public Health, , pp. Saffer, F. Front Health Policy Res. Adicciones, 19 , pp. Santonja, R. Secades, G. Psychosocial predictors of relapse in cocaine-dependent patients in treatment. Sonquist, E. Baker, J. Searching for Structure, Institute for Social Research. University of Michigan, ,. The subpopulation which consumes freebase cocaine has lower education levels, higher unemployment rates, more problems with justice, larger consumption levels of cocaine, and higher prevalence in the use of other illegal drugs. Of these, 43, individuals have all the information about consumption of cocaine. The difference is explained by the fact that we measure use of powder and freebase cocaine in the last 12 months for individuals aged 18—65 years, whereas EDADES refers only to powder cocaine consumed by individuals aged 15—65 years. Dependent variables DV. Occasional use. DV: 1 only occasional use; 0 otherwise. Regular use. Frequent use. Explanatory variables. Ln income. Logarithm of total monthly net equivalent income. No education. Primary education. DV: 1 only primary education; 0 otherwise. Secondary education. DV: 1 only secondary education; 0 otherwise. University education. DV: 1 only university education; 0 otherwise. Good health. Fair health. Poor health. Marital status. Household size. Wald Chi 2
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Spanish Town where can I buy cocaine
None of the villagers had ever seen a boat of this size floating so close to that part of the coast, where the sea was shallow, the tides strong and the rocks razor-sharp. They supposed it was an amateur sailor who had got lost. In fact, the man sailing the boat was a skilled seaman. Two Italian passports, a Spanish passport and a Spanish national ID card were later found in his possession, all of which showed the same year-old with weathered skin and dark curly hair. But each of the four documents listed a different name. Although he was under orders to take the yacht to mainland Spain, his return crossing had been rough. Big lumps of Atlantic swell had pummelled the boat, damaging the rudder and leaving him floundering. He had to get rid of his freight temporarily, and so he began scouring the coast for a place to hide the drugs. The sailor navigated the yacht to a cave near Pilar da Bretanha and began offloading the cocaine, which was bound with plastic and rubber in hundreds of packages the size of building bricks. According to the police investigation that followed, he secured the contraband with fishing nets and chains, submerging it beneath the water with an anchor. The island has , inhabitants, most of whom are separated by only one or two acquaintances. Although the island has the mix of intimacy and claustrophobia that marks many small communities, the predictability of life here creates a sense of security that is reinforced by the vast Atlantic Ocean, which barricades Azoreans within a subtropical paradise. Earlier this year, I visited the island to speak to people who were affected by the influx of the cocaine, or were involved in trying to track down the smuggler. The stories they told of how the drugs changed the island were by turns bizarre, thrilling and tragic. No one expected in early June that they would still be talking about the effects of the cocaine nearly two decades later. On 7 June, the day after the yacht was first sighted, a man from Pilar da Bretanha climbed down a steep path to the small cove where he often fished. On the shore, flapping in the surf like a beached jellyfish, was a large mound covered in black plastic. Beneath the plastic, the fisherman found scores of the small packages. Leaking from some of them was a substance he thought looked very much like flour. He decided to call the police. Within hours, local officers had registered some packages of uncut cocaine, weighing kg. It was only the first of many such discoveries. Two days later, a school teacher named Francisco Negalha alerted the police after finding 15kg on a beach on the other side of the island. Not everyone who found packages reported it to authorities. A number of islanders became small-time dealers and began transporting cocaine across the island in milk churns, paint tins and socks. One such report suggested that two fishermen had seen the man on the yacht dumping some of his cocaine. I heard that one of these men was selling so much of the stuff from his car that his seats were white with powder. The same man had apparently paid a friend g of cocaine just to charge his phone. Before the yacht arrived, locals had seen little cocaine on the island. It was more common to find heroin or hashish. The other was in yellowish crystals. Most users snorted the powder, but dissolved the crystals in water and then injected it into their veins. Both methods were potent. A police officer told me the story of a man nicknamed Joaninha, or Ladybird, who had hooked himself up to a drip of cocaine and water and sat in his house getting high for days. A product so valuable in the rest of the world was rendered almost worthless through abundance. There were rumours that housewives were frying mackerel in cocaine, thinking it was flour, and that old fishermen were pouring it into their coffees like sugar. No one knew how much of the stuff was still out there. Jose Lopes, the judicial police inspector, had been chosen as one of the leaders of the investigation. At the time, he was 34 years old and had worked eight years as a policeman, seven of them on the Azores. He was very familiar with the local drug trade and had a reputation for his encyclopaedic memory. He knew that the cocaine had almost certainly arrived by boat. Thanks to the testimonies of villagers, who had described the vessel, and records of the coming and goings of boats kept by the maritime police, Lopes and his team were able to track down the yacht within a matter of hours. Then they began to stake it out. At around 1am on 8 June, police watched as a Nissan Micra parked up beside the yacht. They later found out that the car had been rented at the airport by a man named Vito Rosario Quinci, who had arrived by plane the previous day. Vito Rosario turned out to be the nephew of the smuggler, a Sicilian whose real name was Antonino Quinci. Spanish prosecutors would later claim that Vito Rosario was the link between Quinci and the unnamed Spanish organisation running the cocaine operation. Two more boats, each carrying more than half a tonne of cocaine, were destined for different ports in Spain. Vito was later found guilty of involvement in this drug smuggling operation and sentenced to 17 years in jail in Spain. However, in , the conviction was overturned after an appeal found that the police had used illegal wiretapping to gather evidence. He denied knowledge of the drug-smuggling operation. Vito met his uncle in the cramped living quarters of the yacht. Later that morning, the two men sailed out of the harbour. Police tailed them to Pilar da Bretanha, the location where Quinci had attempted to stash the cocaine two days earlier. The pair drifted there for 35 minutes, presumably long enough to establish that the cargo was missing. They seemed to do little except make occasional trips on a rubber dinghy, sometimes to buy fuel and other supplies, sometimes to places where police could not track them. On a shelf in the cabin, wrapped up in a plastic bag, investigators also found a brick of cocaine weighing g and a film canister containing another three grams. The arrest went smoothly. The inspector spoke decent Italian, having lived in the country for a short time before he had become a police officer. He and Quinci were able to converse informally. But in an official interrogation on the following day, Quinci suddenly stopped cooperating. He denied having trafficked the cocaine, and said the bricks the police seized from the boat were things he had chanced upon at sea. Or perhaps he thought he could avoid prosecution. What soon became clear, however, was that he had not given up hope of escaping the island. The flow of drugs was usually small and predictable. Often when the police made a seizure, they would make such a dent in the drug supply that local prices would skyrocket. But now police faced an unprecedented situation. As well as the kg of cocaine they had seized in the previous two weeks, Lopes thought that at least another kg were still unaccounted for. Rabo de Peixe, the fishing village where Quinci had first moored his boat, is one of the poorest towns in Portugal, and locals told me that it was a place where even other islanders can feel like outsiders. But that summer, it became a hub for the sale of the missing cocaine. From the town square, perched atop a promontory, narrow streets lined with pastel-coloured houses snake down to the harbour. In these streets, where fishermen hunch over dominos in grotty bars, slurping from small glasses of red wine, kilos and kilos of cocaine exchanged hands. The results were catastrophic. A month after Quinci had arrived on the island, the cocaine was still wreaking havoc. The article reported a spike in the number of overdoses and the death of a young man. Local television networks began broadcasting health warnings to the islanders advising them not to try the cocaine. But it was too late for some. T he prison at Ponta Delgada, where Quinci was sent to await trial, looks like a brutalist castle and looms over the main road heading out of town. According to a witness cited in court documents, while in jail Quinci was often on the phone, talking in Spanish and trying to secure a scooter or rental car. In exchange for help in escaping the prison, Quinci had offered to draw maps for other inmates that would lead them to the cocaine. On the morning of 1 July, about a week and a half after his arrest, Quinci entered a courtyard of the jail for his designated recreation time. His arms were wrapped in ripped bed sheets to protect them from cuts: the yard was surrounded by a long, low wall topped with barbed wire. At around From one of the white hexagonal guard towers, a correctional officer named Antonio Alonso fired a warning shot from his rifle, but Quinci kept climbing. Alonso then aimed his sight directly at the fugitive, and placed his finger on the trigger. Below, prisoners had gathered and were cheering Quinci on. On the other side of the wall, Alonso could see civilians walking up and down a promenade on the main road. He watched as Quinci went over the wall, up the road, on to a small scooter and into the distance. Police were immediately alerted of the escape and moved to seal off the island. Rumours circulated that he was sleeping rough in fields, church lofts and chicken sheds, snorting cocaine to stave off his appetite. Eventually, he ended up in the house of a man named Rui Couto, who lived in a village 26 miles north-east of Ponta Delgada. When I met Couto, who is now in his late 40s and has a tattoo on the left side of his shaved head, he seemed nervous and agitated, and wore clothes that were too big for his skinny frame. Like many islanders, he had moved to the US when he was young. But he was forced to leave after being busted for drug possession. Couto claims Quinci was brought to the house by an acquaintance of his. He also told me he gave Quinci refuge out kindness and that there was no deal or plan with the Italian. The pair would often eat together and talk late into the night. Couto told me that although Quinci was in a sorry state, smoking cocaine in cigarette papers without tobacco, he was always friendly. Couto said that someone Quinci knew came round to give him a fake passport and money. Couto said he had been up late with a friend on the night before the police arrived. Around 7am on 16 July, he heard people shouting outside the house. Couto opened the door in his underpants and a squadron of armed police burst through the front door. According to Lopes, who was part of the raid, they were working off a tip from a police colleague who believed Couto was hiding cocaine at his house. But after checking under beds, sofas, cabinets and in toilet cisterns, the officers found nothing. The inside was covered in hay and smelled strongly of manure. But then, Lopes heard a noise. They found Quinci hiding in a corner, dirty and dishevelled. It was the biggest stroke of luck. But that was just the immediate aftermath of his arrival. Outside Rabo de Peixe, I waited with a group of drug users for the local methadone van, which travels around the island treating people for heroin addiction. That morning, about 20 addicts clustered near a kennel of snarling Azorean cattle dogs. Most of the addicts were gaunt with jaundiced eyes, rotting teeth and grey, wrinkled skin. Small children accompanied a few of the users, while most came alone and spoke to no one, smoking and staring at the tarmac. But the drugs also had more damaging long-term effects. They became addicted to heroin, which was shipped in from the continent, often via the postal service. After he was re-arrested, Quinci was put on trial in Ponta Delgada and given 11 years for drug-trafficking, the use of a false identity and escaping from prison. The decision was appealed and sent to the courts in Lisbon, which reduced the sentence to 10 years. The other two yachts that were part of the smuggling operation, the Lorena and the Julia, were impounded in July in Spain by the Spanish police. According to Europol, the pan-European police agency, the Caribbean-Azores route is now a mainstay of international drug trafficking. Criminals use the islands as a pit stop, where cargo is usually transferred to fishing vessels or speedboats for shipment to mainland Portugal or Spain. Last September, a catamaran sailing under a French flag was impounded near the Azorean island of Faial with kg of cocaine on board. My journey cut through towns of whitewashed buildings with terracotta roofs, past rich green pastures, walled off like squares on a chessboard. Farmers squelched through the soggy fields while portly Holstein-Friesian cows grazed. In the soupy, tropical air, everything seemed settled and staid. But, as I reached the north-eastern tip of the island, I saw the Atlantic stretching out to the horizon like a sheet of rippled slate. And some miles out, a white sail boat was rocking back and forth in the afternoon swell. By Matthew Bremner. Blow up: how half a tonne of cocaine transformed the life of an island — podcast. Read more. View image in fullscreen. Explore more on these topics The long read Drugs Portugal Europe features. Reuse this content. Most viewed.
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Spain's Balearic Islands. He had to get rid of his freight temporarily, and so he began scouring the coast for a place to hide the drugs.
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