Incorporating Real-World Data and Mathematical Modeling to Estimate the Undiagnosed Chronic Hepatitis B Population
Author(s)
William WL Wong, PhD.
School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.
School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.
OBJECTIVES: Chronic hepatitis B (CHB) remains a significant public health concern globally, particularly in the Asia-Pacific region, where most infections are asymptomatic. Understanding geographic and demographic trends in CHB prevalence and undiagnosed cases is crucial for developing equitable healthcare strategies and resource allocation to eliminate the disease. The study's aim is to estimate the CHB prevalence and undiagnosed proportion in Canada’s largest province, Ontario, using a mathematical modeling informed by population-level health administrative data
METHODS: We conducted a population-based retrospective analysis of health administrative data for Ontario from 1999 to 2018 to generate CHB drug utilization, the annual incidence of patients with newly diagnosed hepatocellular carcinoma, decompensated cirrhosis and CHB for three birth cohorts: individuals born before 1945, born between 1945 and 1965, and born after 1965. We developed a back-calculation framework to estimate the historical prevalence of CHB for each cohort. We used a Bayesian Markov Chain Monte Carlo algorithm to back-calculate the historical CHB prevalence and the undiagnosed proportion through a calibration process. The algorithm constructs the probability distribution of the historical CHB prevalence and the undiagnosed proportion by comparing the model-generated predictions of the annual number of CHB health events against observed data.
RESULTS: In 2018, CHB prevalence was estimated at 0.52% (95%CI: 0.49%-0.54%) for individuals born before 1945, 0.48% (95%CI: 0.46%-0.52%) for those born between 1945-1965, and 0.35% (95%CI: 0.31%-0.36%) for those born after 1965. The overall prevalence across all cohorts was 0.44% (95%CI: 0.41%-0.46%). The overall undiagnosed CHB proportions were 31.7% (95%CI: 29.5%-33.4%) with 64.0% (95%CI: 61.5%-66.1%), 22.8% (95%CI: 20.7%-25.1%), and 29.0% (95%CI: 24.9%-31.3%) for each cohort, respectively.
CONCLUSIONS: This study is the first to estimate CHB prevalence and undiagnosed cases using mathematical modeling and real-world provincial health data. These findings provide critical evidence to guide CHB screening strategies and help achieve disease elimination goals.
METHODS: We conducted a population-based retrospective analysis of health administrative data for Ontario from 1999 to 2018 to generate CHB drug utilization, the annual incidence of patients with newly diagnosed hepatocellular carcinoma, decompensated cirrhosis and CHB for three birth cohorts: individuals born before 1945, born between 1945 and 1965, and born after 1965. We developed a back-calculation framework to estimate the historical prevalence of CHB for each cohort. We used a Bayesian Markov Chain Monte Carlo algorithm to back-calculate the historical CHB prevalence and the undiagnosed proportion through a calibration process. The algorithm constructs the probability distribution of the historical CHB prevalence and the undiagnosed proportion by comparing the model-generated predictions of the annual number of CHB health events against observed data.
RESULTS: In 2018, CHB prevalence was estimated at 0.52% (95%CI: 0.49%-0.54%) for individuals born before 1945, 0.48% (95%CI: 0.46%-0.52%) for those born between 1945-1965, and 0.35% (95%CI: 0.31%-0.36%) for those born after 1965. The overall prevalence across all cohorts was 0.44% (95%CI: 0.41%-0.46%). The overall undiagnosed CHB proportions were 31.7% (95%CI: 29.5%-33.4%) with 64.0% (95%CI: 61.5%-66.1%), 22.8% (95%CI: 20.7%-25.1%), and 29.0% (95%CI: 24.9%-31.3%) for each cohort, respectively.
CONCLUSIONS: This study is the first to estimate CHB prevalence and undiagnosed cases using mathematical modeling and real-world provincial health data. These findings provide critical evidence to guide CHB screening strategies and help achieve disease elimination goals.
Conference/Value in Health Info
2025-09, ISPOR Real-World Evidence Summit 2025, Tokyo, Japan
Value in Health Regional, Volume 49S (September 2025)
Code
RWD128
Topic Subcategory
Health & Insurance Records Systems
Disease
SDC: Infectious Disease (non-vaccine)