Surveillance efforts for substance use are failing us. They rely on outdated risk prediction tools yet risk factors for HIV and overdose are context-specific and are impacted by the interplay between patient-, provider-, and system-level factors as well as epidemiologic realities in a community. They rely on direct estimation methods for measuring prevalence yet barriers such as lack of access to medications for opioid use disorder (MOUD) and harm reduction services, stigma, criminalization of drug use, and unaffordable housing prevent people who use drugs (PWUD) from being counted. Additionally, they rarely involve community engagement and surveillance data are not disseminated effectively to communities to achieve maximum benefit. In the context of the ongoing overdose crisis and recent outbreaks of HIV among PWUD in Indiana, Massachusetts, Kentucky, and West Virginia, the failures of this basic tool of public health take on a new urgency. The number of efficacious programs and interventions to prevent and treat substance use and HIV continues to grow, but without accurate estimates of the size of the pool of people at risk of overdose and for acquiring HIV and knowledge of their specific risk factors, these interventions cannot reach their full potential. We cannot reach people who we do not know exist and are at risk. We, therefore, need to immediately modernize and upgrade our surveillance capacity to understand the size and composition of drug-using populations. I am proposing an innovative, interdisciplinary research program that integrates epidemiology, community engagement, biostatistics, econometrics, and information dissemination to create a novel community-based, high- performance surveillance network for PWUD. I will do this by (1) creating a community engaged research (CEnR) process around big data for PWUD; (2) building community-specific risk prediction algorithms for HIV acquisition, disease progression, and loss to follow up among PWUD; (3) using enhanced indirect estimation methods to determine the size of populations of PWUD and to evaluate the impact of interventions; and (4) disseminating findings and translating research into action. The data centerpiece of this program will be the Public Health Data Warehouse, an individually-linked database from more than 15 Massachusetts government agencies, which includes more than 97% of the Massachusetts population. Preliminary analyses with this database are underway and will be made accessible to communities in real-time. This project represents an approach that is entirely divergent from traditional surveillance techniques by using a combination of complex methodologies with the community always at the center of the process?from initiation to final output. This novel Massachusetts cOMmunity-bAsed Drug use surveillANCE (?Moma Dance?) Network will begin in Massachusetts, but will serve as a model for other states and jurisdictions as they contend with the failures of their own surveillance systems for PWUD. These efforts will translate research into action at the community level and have an immediate and sustained public health impact on the drug use and HIV epidemics.
This project will create a novel community-based, high-performance surveillance network for people who use drugs (PWUD) through an interdisciplinary approach that combines community engaged research, machine learning, indirect estimation, and dissemination science. Through this process, communities will gain a more complete understanding of context- and community-specific risk factors and the true scope of the problem. This network will facilitate rapid knowledge transfer to communities, directly informing clinical care and local policy decisions regarding service planning and resource allocation, as they seek to respond to the ongoing drug epidemic in the U.S.
