EXPO 2026: "No-verdose: Using SEIRP and Optimal Control Theory to Model the Opioid Epidemic..." скачать в хорошем качестве

EXPO 2026: "No-verdose: Using SEIRP and Optimal Control Theory to Model the Opioid Epidemic..."

Sat | 1:00 PM–1:30 PM ET Angela Ho; Adlai E. Stevenson High School, Lincolnshire, IL USA Abstract: The opioid epidemic, declared a public health emergency in 2017, continues to harm communities and cause hundreds of thousands of deaths annually. We model opioid addiction using a variation of the SIR model called the SEIRP model and introduce a digital education and prevention campaign as an intervention. We implement optimal control theory using Pontryagin’s Maximum Principle and the Forward-Backward Sweep Algorithm, and use literate programming to enhance communication of our research. Our study differs from the literature in two aspects. First, the SEIRP model accounts for individuals who avoid opioids for life due to prevention efforts. Second, we compare results of quadratic and linear controls. We found that for both quadratic and linear controls, the optimal intervention intensity remained at its maximum from t = 0 to t = 7.40 years. After t = 7.40 years, the optimal quadratic control decreased continuously, and the optimal linear control dropped discontinuously to its minimum. Implementing the education campaign, as a quadratic or linear control, reduced opioid addictions and costs for over 98% of the 10-year span. Using a quadratic control yielded lower costs than using a linear control for over 96% of the 10-year span. This paper informs cost-effective opioid epidemic mitigation strategies under different policy objectives. Our research contributes to the United Nations’ Sustainable Development Goal #3: Good Health and Well-Being. Mentored by: Dia Bonsu; University of Maryland, College Park, MD USA Alonso Ogueda; George Mason University, Fairfax, VA USA Padmanabhan Seshaiyer; George Mason University, Fairfax, VA USA For more information, visit https://qubeshub.org/community/groups...