基于集群的贝叶斯SIRD模型用于印度水痘流行病学分析
Cluster-Based Bayesian SIRD Modeling of Chickenpox Epidemiology in India
AI总结：
本研究提出基于集群的贝叶斯SIRD模型，分析印度水痘流行病学，揭示不同年龄群体的传播动态及地区异质性对流行病控制的影响。
摘要：
本研究提出了一种基于集群的贝叶斯SIRD模型，用于分析印度水痘（水痘）的流行病学，利用1990至2021年的数据。我们采用年龄结构方法，将人口分为青少年、成年人和老年人群，以捕捉疾病在不同人口群体中的传播动态。模型采用Holling型发病率函数，考虑高流行率下的传播饱和效应，并应用贝叶斯推断来估计关键流行病学参数，包括传播率、恢复率和死亡率。研究进一步探讨了聚类分析，以根据水痘传播动态的相似性识别印度地区内的集群，使用发病率、流行率和死亡率等标准。我们采用K均值聚类来揭示三种不同的流行病学制度，这些制度在爆发潜力和年龄特异性动态方面有所不同。研究结果强调青少年是传播的主要驱动因素，而老年人面临不成比例的高死亡率负担。我们的结果强调了针对年龄的干预措施的重要性，并建议在疾病控制的公共卫生策略中考虑地区异质性。该模型提供了一个透明、可重复的框架，用于理解长期传播动态，并支持印度水痘控制的证据基础规划。模型的实用价值进一步通过模拟研究得到验证。
英文摘要：
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.
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