HIV and Hepatitis C Mortality in Massachusetts, 2002–2011: Spatial Cluster and Trend Analysis of HIV and HCV Using Multiple Cause of Death

Background: Infectious diseases, while associated with a much smaller proportion of deaths than they were 50 years ago, still play a significant role in mortality across the state of Massachusetts. Most analysis of infectious disease mortality in the state only take into account the underlying cause of death, rather than contributing causes of death, which may not capture the full extent of mortality trends for infectious diseases such as HIV and the Hepatitis C virus (HCV). Methods: In this study we sought to evaluate current trends in infectious disease mortality across the state using a multiple cause of death methodology. We performed a mortality trend analysis, identified spatial clusters of disease using a 5-step geoprocessing approach and examined spatial-temporal clustering trends in infectious disease mortality in Massachusetts from 2002–2011, with a focus on HIV/AIDS and HCV. Results: Significant clusters of high infectious disease mortality in space and time throughout the state were detected through both spatial and space time cluster analysis. The most significant clusters occurred in Springfield, Worcester, South Boston, the Merrimack Valley, and New Bedford with other smaller clusters detected across the state. Multiple cause of death mortality rates were much higher than underlying cause mortality alone, and significant disparities existed across race and age groups. Conclusions: We found that our multi-method analyses, which focused on contributing causes of death, were more robust than analyses that focused on underlying cause of death alone. Our results may be used to inform public health resource allocation for infectious disease prevention and treatment programs, provide novel insight into the current state of infectious disease mortality throughout the state, and benefited from approaches that may more accurately document mortality trends

Spatial Epidemiology: an Empirical Framework For Syndemics Research

Syndemics framework describes two or more co-occurring epidemics that synergistically interact with each other and the complex structural social forces that sustain them leading to excess disease burden. The term syndemic was first used to describe the interaction between substance abuse, violence, and AIDS by Merrill Singer. A broader range of syndemic studies has since emerged describing the framework\u27s applicability to other public health scenarios. With syndemic theory garnering significant attention, the focus is shifting towards developing robust empirical analytical approaches. Unfortunately, the complex nature of the disease-disease interactions nested within several social contexts complicates empirical analyses. In answering the call to analyze syndemics at the population level, we propose the use of spatial epidemiology as an empirical framework for syndemics research. Spatial epidemiology, which typically relies on geographic information systems (GIS) and statistics, is a discipline that studies spatial variations to understand the geographic landscape and the risk environment within which disease epidemics occur. GIS maps provide visualization aids to investigate the spatial distribution of disease outcomes, the associated social factors, and environmental exposures. Analytical inference, such as estimation of disease risks and identification of spatial disease clusters, can provide a detailed statistical view of spatial distributions of diseases. Spatial and spatiotemporal models can help us to understand, measure, and analyze disease syndemics as well as the social, biological, and structural factors associated with them in space and time. In this paper, we present a background on syndemics and spatial epidemiological theory and practice. We then present a case study focused on the HIV and HCV syndemic in West Virginia to provide an example of the use of GIS and spatial analytical methods. The concepts described in this paper can be considered to enhance understanding and analysis of other syndemics for which space-time data are available

Small area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling approach

BACKGROUND: Opioid-related overdose mortality has remained at crisis levels across the United States, increasing 5-fold and worsened during the COVID-19 pandemic. The ability to provide forecasts of opioid-related mortality at granular geographical and temporal scales may help guide preemptive public health responses. Current forecasting models focus on prediction on a large geographical scale, such as states or counties, lacking the spatial granularity that local public health officials desire to guide policy decisions and resource allocation. OBJECTIVE: The overarching objective of our study was to develop Bayesian spatiotemporal dynamic models to predict opioid-related mortality counts and rates at temporally and geographically granular scales (ie, ZIP Code Tabulation Areas [ZCTAs]) for Massachusetts. METHODS: We obtained decedent data from the Massachusetts Registry of Vital Records and Statistics for 2005 through 2019. We developed Bayesian spatiotemporal dynamic models to predict opioid-related mortality across Massachusetts\u27 537 ZCTAs. We evaluated the prediction performance of our models using the one-year ahead approach. We investigated the potential improvement of prediction accuracy by incorporating ZCTA-level demographic and socioeconomic determinants. We identified ZCTAs with the highest predicted opioid-related mortality in terms of rates and counts and stratified them by rural and urban areas. RESULTS: Bayesian dynamic models with the full spatial and temporal dependency performed best. Inclusion of the ZCTA-level demographic and socioeconomic variables as predictors improved the prediction accuracy, but only in the model that did not account for the neighborhood-level spatial dependency of the ZCTAs. Predictions were better for urban areas than for rural areas, which were more sparsely populated. Using the best performing model and the Massachusetts opioid-related mortality data from 2005 through 2019, our models suggested a stabilizing pattern in opioid-related overdose mortality in 2020 and 2021 if there were no disruptive changes to the trends observed for 2005-2019. CONCLUSIONS: Our Bayesian spatiotemporal models focused on opioid-related overdose mortality data facilitated prediction approaches that can inform preemptive public health decision-making and resource allocation. While sparse data from rural and less populated locales typically pose special challenges in small area predictions, our dynamic Bayesian models, which maximized information borrowing across geographic areas and time points, were used to provide more accurate predictions for small areas. Such approaches can be replicated in other jurisdictions and at varying temporal and geographical levels. We encourage the formation of a modeling consortium for fatal opioid-related overdose predictions, where different modeling techniques could be ensembled to inform public health policy

Opioid initiation and injection transition in rural northern New England: A mixed-methods approach

BACKGROUND: In rural northern New England, located in the northeastern United States, the overdose epidemic has accelerated with the introduction of fentanyl. Opioid initiation and transition to opioid injection have been studied in urban settings. Little is known about opioid initiation and transition to injection drug use in rural northern New England. METHODS: This mixed-methods study characterized opioid use and drug injection in 11 rural counties in Massachusetts, Vermont, and New Hampshire between 2018 and 2019. People who use drugs completed audio computer-assisted self-interview surveys on substance use and risk behaviors (n = 589) and shared personal narratives through in-depth interviews (n = 22). The objective of the current study is to describe initiation of opioid use and drug injection in rural northern New England. RESULTS: Median age of first injection was 22 years (interquartile range 18-28 years). Key themes from in-depth interviews that led to initiating drug injection included normalization of drug use in families and communities, experiencing trauma, and abrupt discontinuation of an opioid prescription. Other factors that led to a transition to injecting included lower cost, increased effect/ rush, greater availability of heroin/ fentanyl, and faster relief of withdrawal symptoms with injection. CONCLUSIONS: Trauma, normalization of drug use, over-prescribing of opioids, and abrupt discontinuation challenge people who use drugs in rural northern New England communities. Inadequate opioid tapering may increase transition to non-prescribed drug use. The extent and severity of traumatic experiences described highlights the importance of enhancing trauma-informed care in rural areas

Opioid overdose deaths and potentially inappropriate opioid prescribing practices (PIP): A spatial epidemiological study

INTRODUCTION: Opioid overdose deaths quintupled in Massachusetts between 2000 and 2016. Potentially inappropriate opioid prescribing practices (PIP) are associated with increases in overdoses. The purpose of this study was to conduct spatial epidemiological analyses of novel comprehensively linked data to identify overdose and PIP hotspots. METHODS: Sixteen administrative datasets, including prescription monitoring, medical claims, vital statistics, and medical examiner data, covering \u3e98% of Massachusetts residents between 2011-2015, were linked in 2017 to better investigate the opioid epidemic. PIP was defined by six measures: \u3e /=100 morphine milligram equivalents (MMEs), co-prescription of benzodiazepines and opioids, cash purchases of opioid prescriptions, opioid prescriptions without a recorded pain diagnosis, and opioid prescriptions through multiple prescribers or pharmacies. Using spatial autocorrelation and cluster analyses, overdose and PIP hotspots were identified among 538 ZIP codes. RESULTS: More than half of the adult population (n = 3,143,817, ages 18 and older) were prescribed opioids. Nearly all ZIP codes showed increasing rates of overdose over time. Overdose clusters were identified in Worcester, Northampton, Lee/Tyringham, Wareham/Bourne, Lynn, and Revere/Chelsea (Getis-Ord Gi*; p \u3c 0.05). Large PIP clusters for \u3e /=100 MMEs and prescription without pain diagnosis were identified in Western Massachusetts; and smaller clusters for multiple prescribers in Nantucket, Berkshire, and Hampden Counties (p \u3c 0.05). Co-prescriptions and cash payment clusters were localized and nearly identical (p \u3c 0.05). Overlap in PIP and overdose clusters was identified in Cape Cod and Berkshire County. However, we also found contradictory patterns in overdose and PIP hotspots. CONCLUSIONS: Overdose and PIP hotspots were identified, as well as regions where the two overlapped, and where they diverged. Results indicate that PIP clustering alone does not explain overdose clustering patterns. Our findings can inform public health policy decisions at the local level, which include a focus on PIP and misuse of heroin and fentanyl that aim to curb opioid overdoses

HIV Clustering in Mississippi: Spatial Epidemiological Study to Inform Implementation Science in the Deep South

Background: In recent years, more than half of new HIV infections in the United States occur among African Americans in the Southeastern United States. Spatial epidemiological analyses can inform public health responses in the Deep South by identifying HIV hotspots and community-level factors associated with clustering. Objective: The goal of this study was to identify and characterize HIV clusters in Mississippi through analysis of state-level HIV surveillance data. Methods: We used a combination of spatial epidemiology and statistical modeling to identify and characterize HIV hotspots in Mississippi census tracts (n=658) from 2008 to 2014. We conducted spatial analyses of all HIV infections, infections among men who have sex with men (MSM), and infections among African Americans. Multivariable logistic regression analyses identified community-level sociodemographic factors associated with HIV hotspots considering all cases. Results: There were HIV hotspots for the entire population, MSM, and African American MSM identified in the Mississippi Delta region, Southern Mississippi, and in greater Jackson, including surrounding rural counties (P \u3c .05). In multivariable models for all HIV cases, HIV hotspots were significantly more likely to include urban census tracts (adjusted odds ratio [AOR] 2.01, 95% CI 1.20-3.37) and census tracts that had a higher proportion of African Americans (AOR 3.85, 95% CI 2.23-6.65). The HIV hotspots were less likely to include census tracts with residents who had less than a high school education (AOR 0.95, 95% CI 0.92-0.98), census tracts with residents belonging to two or more racial/ethnic groups (AOR 0.46, 95% CI 0.30-0.70), and census tracts that had a higher percentage of the population living below the poverty level (AOR 0.51, 95% CI 0.28-0.92). Conclusions: We used spatial epidemiology and statistical modeling to identify and characterize HIV hotspots for the general population, MSM, and African Americans. HIV clusters concentrated in Jackson and the Mississippi Delta. African American race and urban location were positively associated with clusters, whereas having less than a high school education and having a higher percentage of the population living below the poverty level were negatively associated with clusters. Spatial epidemiological analyses can inform implementation science and public health response strategies, including improved HIV testing, targeted prevention and risk reduction education, and tailored preexposure prophylaxis to address HIV disparities in the South

The opioid epidemic in rural northern New England: An approach to epidemiologic, policy, and legal surveillance

The opioid crisis presents substantial challenges to public health in New England\u27s rural states, where access to pharmacotherapy for opioid use disorder (OUD), harm reduction, HIV and hepatitis C virus (HCV) services vary widely. We present an approach to characterizing the epidemiology, policy and resource environment for OUD and its consequences, with a focus on eleven rural counties in Massachusetts, New Hampshire and Vermont between 2014 and 2018. We developed health policy summaries and logic models to facilitate comparison of opioid epidemic-related polices across the three states that could influence the risk environment and access to services. We assessed sociodemographic factors, rates of overdose and infectious complications tied to OUD, and drive-time access to prevention and treatment resources. We developed GIS maps and conducted spatial analyses to assess the opioid crisis landscape. Through collaborative research, we assessed the potential impact of available resources to address the opioid crisis in rural New England. Vermont\u27s comprehensive set of policies and practices for drug treatment and harm reduction appeared to be associated with the lowest fatal overdose rates. Franklin County, Massachusetts had good access to naloxone, drug treatment and SSPs, but relatively high overdose and HIV rates. New Hampshire had high proportions of uninsured community members, the highest overdose rates, no HCV surveillance data, and no local access to SSPs. This combination of factors appeared to place PWID in rural New Hampshire at elevated risk. Study results facilitated the development of vulnerability indicators, identification of locales for subsequent data collection, and public health interventions

Pharmacy Participation in Non-Prescription Syringe Sales in Los Angeles and San Francisco Counties, 2007

Increasing sterile syringe access for injection drug users (IDUs) is one way to prevent HIV and hepatitis C virus (HCV) transmission in this population. In 2005, California Senate Bill 1159 allowed counties to adopt the Disease Prevention Demonstration Project (DPDP). Where enacted, the DPDP allows pharmacies that register with the county to sell up to ten syringes to adults without a prescription. In the current study, we describe pharmacy participation in nonprescription syringe sales (NPSS) in two counties in California and examine factors associated with NPSS. Telephone and in-person interviews were conducted in Los Angeles (LA) and San Francisco (SF) with 238 pharmacies in 2007 (n = 67 in SF; n = 171 in LA). Quantitative survey items captured pharmacy registration with the county, pharmacy policies/practices, episodes and conditions of NPSS and refusals to sell, potential negative consequences of NPSS, and staff attitudes regarding HIV and HCV prevention for IDUs. Overall, 42% of pharmacies reported NPSS (28% in LA and 81% in SF), although only 34% had registered with the county (17% in LA and 76% in SF). Many pharmacies required proof of a medical condition (80% in LA and 30% in SF) and refused NPSS if the customer was a suspected IDU (74% in LA, 33% in SF). Few negative consequences of NPSS were reported. In multivariate logistic regression analysis, we found that the odds of NPSS were significantly higher among pharmacists who thought syringe access was important for preventing HIV among IDUs [adjusted odds ratio (AOR) = 2.95; 95% confidence interval (CI) = 1.10–7.92], were chain pharmacies (AOR = 12.5; 95% CI = 4.55–33.33), and were located in SF (AOR = 4.88; 95% CI = 1.94–12.28). These results suggest that NPSS were influenced by pharmacists’ perception. NPSS might be increased through greater educational efforts directed at pharmacists, particularly those in non-chain pharmacies

Three Years after Legalization of Nonprescription Pharmacy Syringe Sales in California: Where Are We Now?

In January 2005, passage of California Senate Bill 1159 enabled California’s county or city governments to establish disease prevention demonstration projects (DPDPs) through which pharmacies could subsequently register to legally sell up to 10 syringes to adults without a prescription. California’s 61 local health jurisdictions (LHJs) were surveyed annually in 2005–2007 to monitor the progress of DPDP implementation and assess program coverage, facilitators, and barriers. Completed surveys were returned by mail, fax, e-mail, phone, or internet. We analyzed 2007 survey data to describe current DPDP status; data from all years were analyzed for trends in approval and implementation status. By 2007, 17 (27.9%) LHJs approved DPDPs, of which 14 (82.4%) had registered 532 (17.8%) of the 2,987 pharmacies in these 14 LHJs. Although only three LHJs added DPDPs since 2006, the number of registered pharmacies increased 102% from 263 previously reported. Among the LHJs without approved DPDPs in 2007, one (2.3%) was in the approval process, seven (16.3%) planned to seek approval, and 35 (81.4%) reported no plans to seek approval. Of 35 LHJs not planning to seek approval, the top four reasons were: limited health department time (40%) or interest (34%), pharmacy disinterest (31%), and law enforcement opposition (26%). Among eight LHJs pursuing approval, the main barriers were “time management” (13%), educating stakeholders (13%), and enlisting pharmacy participation (13%). The17 LHJs with DPDP represent 52% of California’s residents; they included 62% of persons living with HIV and 59% of IDU-related HIV cases, suggesting that many LHJs with significant numbers of HIV cases have approved DPDPs. Outcome studies are needed to determine whether SB 1159 had the desired impact on increasing syringe access and reducing blood-borne viral infection risk among California IDUs