This study presents a cluster-based Bayesian SIRD model to analyze the epidemiology of chickenpox (varicella) in India, utilizing data from 1990 to 2021. We employed an age-structured approach, dividing the population into juvenile, adult, and elderly groups, to capture the disease's transmission dynamics across diverse demographic groups. The model incorporates a Holling-type incidence function, which accounts for the saturation effect of transmission at high prevalence levels, and applies Bayesian inference to estimate key epidemiological parameters, including transmission rates, recovery rates, and mortality rates. The study further explores cluster analysis to identify regional clusters within India based on the similarities in chickenpox transmission dynamics, using criteria like incidence, prevalence, and mortality rates. We perform K-means clustering to uncover three distinct epidemiological regimes, which vary in terms of outbreak potential and age-specific dynamics. The findings highlight juveniles as the primary drivers of transmission, while the elderly face a disproportionately high mortality burden. Our results underscore the importance of age-targeted interventions and suggest that regional heterogeneity should be considered in public health strategies for disease control. The model offers a transparent, reproducible framework for understanding long-term transmission dynamics and supports evidence-based planning for chickenpox control in India. The practical utility of the model is further validated through a simulation study.

翻译：本研究提出一种基于聚类的贝叶斯SIRD模型，利用1990年至2021年的数据分析印度水痘（varicella）的流行病学特征。我们采用年龄分层方法，将人口划分为青少年、成人和老年群体，以捕捉疾病在不同人口群体中的传播动态。该模型引入Holling型发病率函数，用于解释高流行水平下传播的饱和效应，并应用贝叶斯推断来估计关键流行病学参数，包括传播率、康复率和死亡率。研究进一步通过聚类分析，基于水痘传播动态的相似性（如发病率、流行率和死亡率等指标）识别印度境内的区域聚类。我们采用K-means聚类方法揭示了三种不同的流行病学模式，这些模式在暴发潜力和年龄特异性动态方面存在差异。研究结果突显青少年是传播的主要驱动群体，而老年人则承受着不成比例的高死亡率负担。我们的发现强调了针对特定年龄层干预措施的重要性，并建议在疾病控制的公共卫生策略中应考虑区域异质性。该模型为理解长期传播动态提供了透明、可复现的分析框架，支持印度水痘防控工作的循证规划。通过模拟研究进一步验证了该模型的实际应用价值。