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BACKGROUND: Xylazine, an adulterant in local drug supplies, has been detected in approximately 30% of opioid samples submitted for testing in Massachusetts. A better understanding of local risks, harms, and use preferences is needed to combat xylazine-related impacts on local communities. METHODS: Through the STOP-OD Lowell study, we aimed to assess local xylazine awareness through in-depth interviews with local community stakeholders (n = 15) and local people who use drugs (PWUD; n = 15) and surveys with local PWUD (n = 94). The qualitative interviews focused on the current drug landscape and knowledge of adulterants in Lowell, and the results informed subsequent survey design. Through our survey, we examined whether PWUD were aware of xylazine and their willingness to use xylazine test strips. RESULTS: Most community stakeholders and PWUD had limited awareness about the presence and impact of xylazine as an adulterant. Forty-seven (50%) survey respondents were aware of xylazine. When provided with more information about xylazine, 65% of all respondents expressed a willingness to use xylazine test strips. PWUD who had received naloxone training, reported using with others, and using tester shots were more willing to use xylazine test strips. CONCLUSION: Our findings are congruent with existing literature that indicates that there is limited awareness of xylazine among PWUD, and they consider xylazine an unwanted adulterant. We also found that PWUD who use other harm reduction measures are more willing to use xylazine test strips. The increase in xylazine warrants additional community-level interventions such as wound management and local testing infrastructure. Further research is needed to understand better the impacts associated with xylazine use, effective harm reduction techniques, and perceptions of xylazine test strips.
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BACKGROUND: Fatal opioid-related overdoses (OOD) continue to be a leading cause of preventable death across the US. Opioid Overdose Education and Naloxone Distribution programs (OENDs) play a vital role in addressing morbidity and mortality associated with opioid use, but access to such services is often inequitable. We utilized a geographic information system (GIS) and spatial analytical methods to inform prioritized placement of OEND services in Massachusetts. METHODS: We obtained addresses for OEND sites from the Massachusetts Department of Public Health and address-level fatal OOD data for January 2019 to December 2021 from the Massachusetts Registry of Vital Records and Statistics. Using location-allocation approaches in ArcGIS Pro, we created p-median models using locations of existing OEND sites and fatal OOD counts to identify areas that should be prioritized for future OEND placement. Variables included in our analysis were transportation mode, distance from public schools, race and ethnicity, and location feasibility. RESULTS: Three Massachusetts communities - Athol, Dorchester, and Fitchburg - were identified as priority sites for new OEND locations using location-allocation models based on capacity to maximize OOD prevention. Communities identified by the models for OEND placement had similar demographics and overdose rates (42.8 per 100,000 vs 40.1 per 100,000 population) to communities with existing OEND programs but lower naloxone kit distribution rates (2589 doses per 100,000 vs 3704 doses per 100,000). Further models demonstrated differential access based on location and transportation. CONCLUSION: Our analyses identified key areas of Massachusetts with greatest need for OEND services. Further, these results demonstrate the utility of using spatial epidemiological methods to inform public health recommendations.
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BACKGROUND: Fatal opioid-involved overdose rates increased precipitously from 5.0 per 100,000 population to 33.5 in Massachusetts between 1999 and 2022. METHODS: We used spatial rate smoothing techniques to identify persistent opioid overdose-involved fatality clusters at the ZIP Code Tabulation Area (ZCTA) level. Rate smoothing techniques were employed to identify locations of high fatal opioid overdose rates where population counts were low. In Massachusetts, this included areas with both sparse data and low population density. We used Local Indicators of Spatial Association (LISA) cluster analyses with the raw incidence rates, and the Empirical Bayes smoothed rates to identify clusters from 2011 to 2021. We also estimated Empirical Bayes LISA cluster estimates to identify clusters during the same period. We constructed measures of the socio-built environment and potentially inappropriate prescribing using principal components analysis. The resulting measures were used as covariates in Conditional Autoregressive Bayesian models that acknowledge spatial autocorrelation to predict both, if a ZCTA was part of an opioid-involved cluster for fatal overdose rates, as well as the number of times that it was part of a cluster of high incidence rates. RESULTS: LISA clusters for smoothed data were able to identify whether a ZCTA was part of a opioid involved fatality incidence cluster earlier in the study period, when compared to LISA clusters based on raw rates. PCA helped in identifying unique socio-environmental factors, such as minoritized populations and poverty, potentially inappropriate prescribing, access to amenities, and rurality by combining socioeconomic, built environment and prescription variables that were highly correlated with each other. In all models except for those that used raw rates to estimate whether a ZCTA was part of a high fatality cluster, opioid overdose fatality clusters in Massachusetts had high percentages of Black and Hispanic residents, and households experiencing poverty. The models that were fitted on Empirical Bayes LISA identified this phenomenon earlier in the study period than the raw rate LISA. However, all the models identified minoritized populations and poverty as significant factors in predicting the persistence of a ZCTA being part of a high opioid overdose cluster during this time period. CONCLUSION: Conducting spatially robust analyses may help inform policies to identify community-level risks for opioid-involved overdose deaths sooner than depending on raw incidence rates alone. The results can help inform policy makers and planners about locations of persistent risk.
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Teorema de Bayes , Overdose de Opiáceos , Fatores Socioeconômicos , Análise Espacial , Humanos , Massachusetts/epidemiologia , Fatores de Risco , Overdose de Opiáceos/mortalidade , Overdose de Opiáceos/epidemiologia , Análise por Conglomerados , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Analgésicos Opioides/intoxicação , Feminino , Adulto , Masculino , Overdose de Drogas/mortalidade , Overdose de Drogas/epidemiologiaRESUMO
BACKGROUND: Death certificate data provide powerful and sobering records of the opioid overdose crisis. In Massachusetts, where address-level decedent data are publicly available upon request, mapping and spatial analysis of fatal overdoses can provide valuable insights to inform prevention interventions. We describe how we used this approach to support a community-level intervention to reduce opioid-involved overdose mortality. METHODS: We developed a method to clean and geocode decedent data that substituted injury locations (the likely location of fatal overdoses) for deaths recorded in hospitals. After geomasking for greater privacy protection, we created maps to visualize the spatial distribution of decedent residence addresses, alone and juxtaposed with drive and walk-time distances to opioid treatment programs (OTPs), and place of death by overdose address. We used spatial statistical analyses to identify locations with significant clusters of overdoses. RESULTS: In the 8 intervention communities, 785 individuals died from opioid-involved overdoses between 2017 and 2020. We found that 19.7% of fatal overdoses were recorded in hospitals, 50.2% occurred at the decedent's residence, and 30.1% at another location. We identified overdose hotspots in study communities. By juxtaposing decedent residence data with drive- and walk-time analyses, we highlighted actionable spatial gaps in access to OTP treatment. CONCLUSION: To better understand local fatal opioid overdose risk environments and inform the development of community-level prevention interventions, we used publicly available address-level decedent data to conduct nuanced spatial analyses. Our approach can be replicated in other jurisdictions to inform overdose prevention responses.
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INTRODUCTION: The opioid overdose epidemic continues to impact a large swath of the population in the US. Medications for opioid use disorders (MOUD) are an effective resource to combat the epidemic; however, there is limited research on MOUD treatment access that accounts for both supply of and demand for services. We aimed to examine access to buprenorphine prescribers in the HEALing Communities Study (HCS) Wave 2 communities in Massachusetts, Ohio, and Kentucky during 2021, and the association between buprenorphine access and opioid-related incidents, specifically fatal overdoses and opioid-related responses by emergency medical services (EMS). METHODS: We calculated Enhanced 2-Step Floating Catchment Area (E2SFCA) accessibility indices for each state, as well as Wave 2 communities in each state, based on the location of providers (buprenorphine-waivered clinicians from the US Drug Enforcement Agency Active Registrants database), population-weighted centroids at the census block group level, and catchment areas defined by the state or community's average commute time. In advance of intervention initiation, we quantified the opioid-related risk environment of communities. We assessed gaps in services by using bivariate Local Moran's I analysis, incorporating accessibility indices and opioid-related incident data. RESULTS: Massachusetts Wave 2 HCS communities had the highest rates of buprenorphine prescribers per 1000 patients (median: 165.8) compared to Kentucky (38.8) and Ohio (40.1). While urban centers in all three states had higher E2SFCA index scores compared to rural communities, we observed that suburban communities often had limited access. Through bivariate Local Moran's I analysis, we identified numerous locations with low buprenorphine access surrounded by high opioid-related incidents, particularly in communities that surrounded Boston, Massachusetts; Columbus, Ohio; and Louisville, Kentucky. CONCLUSION: Rural communities demonstrated a great need for additional access to buprenorphine prescribers. However, policymakers should also direct attention toward suburban communities that have experienced significant increases in opioid-related incidents.
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Buprenorfina , Humanos , Buprenorfina/uso terapêutico , Analgésicos Opioides/uso terapêutico , Ohio/epidemiologia , Kentucky/epidemiologia , Tratamento de Substituição de Opiáceos , Massachusetts/epidemiologiaRESUMO
BACKGROUND: Prescription opioids (POs) have had a devastating effect on people and public health systems in the U.S. Due to the urgency and complexity of the opioid crisis, there is a need to expand qualitative research on the medical community's perspectives on opioid prescribing practices and the role that prescription drug monitoring programs (PDMPs) have played in mitigating this crisis. METHODS: We conducted qualitative interviews with clinicians (n = 23) across specialties and a range of overdose hotspot and coldspot locations in Massachusetts during 2019. We aimed to capture their perspectives on the opioid crisis, changes in clinical practice, and experiences with opioid prescribing and PDMPs. RESULTS: Respondents consistently recognized the role clinicians played in the opioid crisis and reported reductions in their opioid prescribing, which were motivated by the crisis itself. The limitations of opioids in pain management were frequently discussed. While clinicians appreciated having greater awareness of their opioid prescribing and increased access to patient prescription histories, they also expressed concerns about surveillance of their prescribing and other unintended consequences. We observed that clinicians in opioid prescribing hotspots had more detailed and specific reflections on their experiences with the Massachusetts PDMP, MassPAT. CONCLUSION: Clinician perceptions of the severity of the opioid crisis in Massachusetts and thoughts on their role as prescribers were consistent across specialty, prescribing level, and practice location. Many clinicians in our sample cited use of the PDMP as an influence on their prescribing. Those practicing in opioid overdose hotspots had the most nuanced reflections about the system.
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Overdose de Drogas , Programas de Monitoramento de Prescrição de Medicamentos , Humanos , Analgésicos Opioides/uso terapêutico , Padrões de Prática Médica , Overdose de Drogas/epidemiologia , MassachusettsRESUMO
In 2020, an estimated 2.7 million people in the US had opioid use disorder, increasing their risk of opioid-related morbidity and mortality. While jurisdictional vulnerability assessments (JVA) of opioid-related outcomes have been conducted previously in the US, there has been no unifying methodological framework. Between 2019 and 2021, we prepared ten JVAs, in collaboration with the Council of State and Territorial Epidemiologists, the Centers for Disease Control and Prevention, and state public health agencies, to evaluate the risk for opioid-involved overdose (OOD) fatalities and related consequences. Our aim is to share the framework we developed for these ten JVAs, based on our study of the work of Van Handel et al. from 2016, as well as a summary of 18 publicly available assessments of OOD or associated hepatitis C virus infection vulnerability. We developed a three-tiered framework that can be applied by jurisdictions based on the number of units of analysis (e.g., counties, ZIP Codes, census tracts): under 10 (Tier 1), 10 to <50 (Tier 2), and 50 or more (Tier 3). We calculated OOD vulnerability indices based on variable ranks, weighted variable ranks, or multivariable regressions, respectively, for the three tiers. We developed thematic maps, conducted spatial analyses, and visualized service provider locations, drive-time service areas, and service accessibility relative to OOD risk. The methodological framework and examples of our findings from several jurisdictions can be used as a foundation for future assessments and help inform policies to mitigate the impact of the opioid overdose crisis.
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Overdose de Drogas , Hepatite C , Transtornos Relacionados ao Uso de Opioides , Humanos , Analgésicos Opioides/efeitos adversos , Transtornos Relacionados ao Uso de Opioides/epidemiologia , Epidemia de Opioides , Overdose de Drogas/tratamento farmacológicoRESUMO
Understanding the factors associated with where people who use opioids live, where their fatal overdoses occur, and where deaths are recorded can improve our knowledge of local risk environments and inform intervention planning. Through geospatial analyses of death certificate data between 2015 and 2017, we found that a majority of opioid-involved fatal overdoses in Massachusetts occurred at home. Age (adjusted odds ratio [AOR], 1.03; 95% confidence interval [CI], 1.02-1.04), living in a census tract with a higher percentage of crowded households (AOR, 1.04; 95% CI, 1.01-1.08), households without vehicles (AOR, 1.01; 95% CI, 1.00-1.02), and Hispanic ethnicity (AOR, 0.56; 95% CI, 0.42-0.74) were independently associated with fatal overdose at home. Using geographically weighted regression, we identified locations where these associations were stronger and could benefit most from home-based and culturally sensitive overdose prevention efforts, including expanded overdose education and naloxone distribution.
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Overdose de Drogas , Overdose de Opiáceos , Humanos , Razão de Chances , Projetos de Pesquisa , Overdose de Drogas/epidemiologia , Massachusetts/epidemiologiaRESUMO
BACKGROUND: Between 2009 and 2019 opioid-involved fatal overdose rates increased by 45% and the average opioid dispensing rate in Wyoming was higher than the national average. The opioid crisis is shaped by a complex set of socioeconomic, geopolitical, and health-related variables. We conducted a vulnerability assessment to identify Wyoming counties at higher risk of opioid-related harm, factors associated with this risk, and areas in need of overdose treatment access to inform priority responses. METHODS: We compiled 2016 to 2018 county-level aggregated and de-identified data. We created risk maps and ran spatial analyses in a geographic information system to depict the spatial distribution of overdose-related measures. We used addresses of opioid treatment programs and buprenorphine providers to develop drive-time maps and ran 2-step floating catchment area analyses to measure accessibility to treatment. We used a straightforward and replicable weighted ranks approach to calculate final county vulnerability scores and rankings from most to least vulnerable. FINDINGS: We found Hot Springs, Carbon, Natrona, Fremont, and Sweetwater Counties to be most vulnerable to opioid-involved overdose fatalities. Opioid prescribing rates were highest in Hot Springs County (97 per 100 persons), almost two times the national average (51 per 100 persons). Statewide, there were over 90 buprenorphine-waivered providers, however accessibility to these clinicians was limited to urban centers. Most individuals lived further than a four-hour round-trip drive to the nearest methadone treatment program. CONCLUSIONS: Identifying Wyoming counties with high opioid overdose vulnerabilities and limited access to overdose treatment can inform public health and harm reduction responses.
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Buprenorfina , Overdose de Drogas , Overdose de Opiáceos , Transtornos Relacionados ao Uso de Opioides , Analgésicos Opioides/uso terapêutico , Buprenorfina/uso terapêutico , Overdose de Drogas/epidemiologia , Humanos , Transtornos Relacionados ao Uso de Opioides/tratamento farmacológico , Padrões de Prática Médica , WyomingRESUMO
Consumers with low income in the United States have higher vulnerability to unhealthy diets compared with the general population. Although some literature speculates that scarcity is an explanation for this disparity, empirical evidence is lacking. We conducted a qualitative study of food choice to explore whether scarcity-related phenomena, such as tunneling and bandwidth tax, may contribute to unhealthy dietary choices. We used participant-driven photo elicitation (n = 18) to investigate the food choice behaviors of individuals living in the greater Boston area who met the federal guidelines for poverty. Participants took photos at the point of food acquisition for 1 month, after which we interviewed them using a semistructured interview guide with the photos as prompts. Thematic coding was used for analysis. Respondents had relative time abundance. Two major themes emerged: participants used a set of strategies to stretch their budgets, and they highly prioritized cost and preference when making food choices. The extreme focus on obtaining food at low cost, which required time and effort, was suggestive of tunneling. We found no evidence of the bandwidth tax. Our findings raise the hypothesis of scarcity as a continuum: when individuals experience multiple resource constraints, they experience scarcity; whereas people with very limited finances and relative time abundance may instead be in a prescarcity condition, with a hyperfocus on a scarce resource that could lead to tunneling as constraints increase. Additional studies are needed to understand whether and how tunneling and bandwidth tax emerge, independently or together, as people face different levels and types of scarcity.
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Preferências Alimentares , Pobreza , Comportamento de Escolha , Dieta , Alimentos , Abastecimento de Alimentos , Humanos , Estados UnidosRESUMO
The objective of this initiative was to conduct a comprehensive opioid overdose vulnerability assessment in Indiana and evaluate spatial accessibility to opioid use disorder treatment, harm reduction services, and opioid response programs. We compiled 2017 county-level (n = 92) data on opioid-related and socioeconomic indicators from publicly available state and federal sources. First, we assessed the spatial distribution of opioid-related indicators in a geographic information system (GIS). Next, we used a novel regression-weighted ranking approach with mean standardized covariates and an opioid-involved overdose mortality outcome to calculate county-level vulnerability scores. Finally, we examined accessibility to opioid use disorder treatment services and opioid response programs at the census tract-level (n = 1511) using two-step floating catchment area analysis. Opioid-related emergency department visit rate, opioid-related arrest rate, chronic hepatitis C virus infection rate, opioid prescription rate, unemployment rate, and percent of female-led households were independently and positively associated with opioid-involved overdose mortality (p < 0.05). We identified high-risk counties across the rural-urban continuum and primarily in east central Indiana. We found that only one of the 19 most vulnerable counties was in the top quintile for treatment services and had naloxone provider accessibility in all of its census tracts. Findings from our vulnerability assessment provide local-level context and evidence to support and inform future public health policies and targeted interventions in Indiana in areas with high opioid overdose vulnerability and low service accessibility. Our approach can be replicated in other state and local public health jurisdictions to assess opioid-involved public health vulnerabilities.