Capturing Rural Risk Network Structures from Continuous-time Interaction Data (RISC)

项目摘要

PROJECT ABSTRACT Rural drug use in the Central Plains is a large and growing public health problem. Recent substance abuse data show that Nebraska, Iowa, and Missouri are all in the top 10 states for methamphetamine-related hospital admissions. The high level of substance abuse is coupled with a severe lack of treatment facilities in these rural areas, as well as restrictive syringe access laws. These conditions (high substance use, few treatment facilities, and lack of access to clean needles) combine to create a vulnerable population, one particularly at risk for the spread of infectious diseases, like HIV and hepatitis C virus (HCV). For example, a well-publicized HIV outbreak in southern Indiana occurred in 2015, revealing widespread rural drug use. Outbreaks like this demonstrate that even populations with low rates of HIV (for example) may be structurally at risk for an epidemic. Despite the urgency of the rural drug use problem, relatively little is known about the network and behavioral risk factors of rural drug users. Most of the data on illicit drugs come from urban settings, even while rural drug use and related health outcomes have increased over the last few decades. The lessons learned from urban drug users are unlikely to hold in rural areas, where conditions and experiences can be quite different; for example, rural drug users tend to have small social circles, limited chances for social or economic mobility, high availability of drugs, and few drug treatment venues. This project, as part of the larger Rural Drug Addiction Research Center, will fill in crucial gaps in the knowledge of rural drug use and associated health risks while investigating the potential efficacy of different interventions. In particular, the social network dynamics and behavioral contexts that contribute to the risk of HCV and HIV infection will be investigated in three rural areas surrounding communities in Nebraska, Iowa, and Missouri. Behavioral risks associated with HIV and HCV spread, as well as the structure of the drug use network, will be measured as important risk factors for disease spread (Aim 1). Using these data, an empirically-grounded, epidemiological simulation will be developed. The simulation approach makes it possible to pinpoint the conditions under which an epidemic is possible and describe the possible efficacy of different interventions in limiting a potential outbreak. Previous network models will be extended by combining traditional survey data with innovative, continuous-time interaction data, resulting in an epidemiological framework that measures factors like relationship timing, context, and geography (Aim 2), factors that are known to affect disease spread but have previously been difficult to quantify. This simulation will then be used to characterize the risk of HIV/HCV spread in this drug user population (Aim 3). Overall, the project will offer timely, crucial information about a rural, at-risk population. The broad, long-term objective is to establish an empirically- validated, epidemiological model with clear public policy applications, such as the monitoring of disease spread in rural, at-risk populations and the development of interventions to combat addiction related harms.