基于Holt-Winters模型的传染病数据分析

Infectious Disease Data Analysis Based on Holt-Winters Model

摘要: 如何准确预测传染病趋势对于指导公共卫生政策和社会经济活动至关重要。本文应用一种时间序列分析方法Holt-Winters模型，对传染病数据进行分析，以预测其发展和季节性变化，利用Python进行模型建立和参数优化，并给出具体的分析结果。通过比较不同预测模型，进一步探讨了Holt-Winters模型在传染病预测中的优势和局限，并提出了改进模型预测准确性的策略，研究结果不仅为制定有效的传染病防控措施提供了科学依据，也为传染病预测模型的研究提供了新的视角。

Abstract: Accurately predicting infectious disease trends is crucial for guiding public health policies and socio-economic activities. In this paper, a time series analysis method, the Holt-Winters model, is applied to analyze infectious disease data to predict its development and seasonal variations. The study involves model establishment and parameter optimization using Python, and specific analysis results are provided. By comparing different forecasting models, the advantages and limitations of the Holt-Winters model in infectious disease prediction are further discussed. Strategies to improve the accuracy of model predictions are proposed, offering scientific basis for effective infectious disease prevention and control measures and providing a new perspective for research on infectious disease prediction models.