Kent State University's College of Public Health is teaming up with the Department of Computer Science to develop and implement drug prevention infrastructure in Portage, Geauga and Lake counties.
Deric Kenne, Ph.D., associate professor of health policy and management in Kent State's College of Public Health, and his team have received a five-year, $1.5 million grant from the Substance Abuse and Mental Health Services Administration (SAMHSA) in the U.S. Department of Health and Human Services. The project and associated personnel will be housed in the university's Center for Public Policy and Health and involves a collaboration with Ruoming Jin, Ph.D., professor of computer science, and his team in the Department of Computer Science in the College of Arts and Sciences.
The project, called the Northeast Ohio Tri-County Prevention Infrastructure, will work to prevent the onset and reduce the progression of alcohol and other drug use in youth ages 9 to 20 in Geauga, Lake and Portage counties. Through the creation and utilization of an innovative big data analytics system, the Northeast Ohio Tri-County Prevention Infrastructure will be able to provide comprehensive community assessment data and monitor substance use to identify potential areas of need. Over time, the big data analytics system will be able to predict substance abuse trends and issues with high accuracy using natural language processing models and machine learning.
While substance use monitoring using data from social media and public forums has been demonstrated through academic prototypes, the Northeast Ohio Tri-County Prevention Infrastructure intends to expand the operational capability of this methodology to better understand community-level substance use behavior and monitor trends in real time. This innovative strategy is projected to eliminate reliance on outdated, incomplete data and provide public health professionals with more sophisticated insights.
"We have been working with Dr. Jin over the past year on several grant applications proposing to develop and implement a real-time, big data analytics system for substance use detecting and monitoring," said Kenne, describing his interdisciplinary work with Jin and the Department of Computer Science at Kent State. "Dr. Jin brings a wealth of experience to the table. By collaborating with Dr. Jin and his team, we will be developing and implementing a novel approach to detecting and monitoring substance use, especially in large, mostly rural areas where traditional forms of substance use data are often lacking or incomplete."
Jin has also expressed excitement for this unique collaborative opportunity.
"We are very excited about the grant and look forward to starting to work on the project and building a system that can help with the prevention of drug abuse epidemics," Jin said. "Teaming up with the Division of Mental Health and Substance Use, especially Professor Deric Kenne, provides a unique opportunity for computer science researchers to apply the state-of-the-art big data, social network analysis and machine learning technologies to help fight the drug abuse problem."
Additionally, the Northeast Ohio Tri-County Prevention Infrastructure will work collaboratively with the Alcohol, Drug Addiction and Mental Health Services (ADAMHS) boards, health departments in each county and Ohio's Prevention Action Alliance.
"The main purpose of the project is to establish an infrastructure that can be used to inform and implement drug prevention efforts," Kenne said. "As such, we will be working closely in collaboration with county mental health and drug boards and health departments. We will also be working with community agencies that focus on substance use prevention and treatment. We are excited to have the opportunity to work with so many great and diverse state and local agencies.
"The ultimate goal of the project would be to develop and implement an accurate, sustainable and real-time substance use monitoring system that can detect substance use threats early so that state and community agencies can effectively respond with prevention efforts and significantly reduce substance abuse and related issues," Kenne added. "This novel approach to drug prevention could ultimately become a model for other communities."
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