Balancing progression and regression: A mechanistic model for hypertension progression and management in China

Objective: This study aims to investigate the mechanisms underlying the progression of hypertension and to evaluate the effectiveness of various intervention strategies. Methods: A four-state dynamic model was developed to describe the natural progression of hypertension, considering clinical variations in blood pressure, disease trajectory, and the patient's life course. Hypertension prevalence data in China from 2002 to 2018 were utilized to calibrate the model and estimate parameters using a Metropolis-Hastings Markov Chain Monte Carlo (MCMC) algorithm. The equilibrium and stability of the system were analyzed mathematically. The model was then employed to forecast future epidemiological trends in hypertension prevalence in China. Sensitivity analyses and numerical simulations were conducted to evaluate the effectiveness of diverse intervention strategies by examining changes in prevalence and disease states. Results: The model demonstrated a strong fit to the observed data (R 2 =99%). Projections indicate a concerning upward trend, with hypertension prevalence in China forecast to rise from 30.2% in 2022 to over 40% by 2045. Simulation of interventions, however, shows that reducing disease progression and enhancing regression could lower prevalence to approximately 23-29% by 2030. An integrated strategy, featuring a 60% reduction in both prehypertension and hypertension progression rates coupled with a 45% increase in prehypertension regression, would align with WHO management targets. Conclusion: The increasing prevalence of hypertension in China can be effectively mitigated by reducing disease progression rates and strengthening prehypertension management. Attaining the WHO's 2010-2030 control objectives, however, necessitates a comprehensive and coordinated set of interventions.