Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.

IF 4 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Environmental Health and Preventive Medicine Pub Date : 2023-01-01 DOI:10.1265/ehpm.23-00141

Jing Yang, Jie Zhou, Tingyan Luo, Yulan Xie, Yiru Wei, Huanzhuo Mai, Yuecong Yang, Ping Cui, Li Ye, Hao Liang, Jiegang Huang

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引用次数: 0

Abstract

Background: Existing researches have established a correlation between internet search data and the epidemics of numerous infectious diseases. This study aims to develop a prediction model to explore the relationship between the Pulmonary Tuberculosis (PTB) epidemic trend in China and the Baidu search index.

Methods: Collect the number of new cases of PTB in China from January 2011 to August 2022. Use Spearman rank correlation and interaction analysis to identify Baidu keywords related to PTB and construct a PTB comprehensive search index. Evaluate the predictive performance of autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models for the number of PTB cases.

Results: Incidence of PTB had shown a fluctuating downward trend. The Spearman rank correlation coefficient between the PTB comprehensive search index and its incidence was 0.834 (P < 0.001). The ARIMA model had an AIC value of 2804.41, and the MAPE value was 13.19%. The ARIMAX model incorporating the Baidu index demonstrated an AIC value of 2761.58 and a MAPE value of 5.33%.

Conclusions: The ARIMAX model is superior to ARIMA in terms of fitting and predicting accuracy. Additionally, the use of Baidu Index has proven to be effective in predicting cases of PTB.

查看原文本刊更多论文

使用百度搜索指数预测中国肺结核发病率：ARIMAX模型方法。

背景：现有研究已经建立了互联网搜索数据与多种传染病流行之间的相关性。本研究旨在建立一个预测模型，探讨中国肺结核（PTB）流行趋势与百度搜索指数之间的关系。方法：收集2011年1月至2022年8月中国PTB新增病例数。利用Spearman秩相关和交互分析方法，识别出与PTB相关的百度关键词，构建PTB综合搜索指数。评估自回归综合移动平均（ARIMA）和ARIMA与解释变量（ARIMAX）模型对PTB病例数的预测性能。结果：PTB的发病率呈波动性下降趋势。PTB综合搜索指数与发病率的Spearman秩相关系数为0.834（P＜0.001）。ARIMA模型的AIC值为2804.41，结合百度指数的ARIMAX模型的AIC值为2761.58，MAPE值为5.33%。结论：ARIMAX模型在拟合和预测精度方面优于ARIMA。此外，百度指数的使用已被证明在预测PTB病例方面是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Environmental Health and Preventive Medicine PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -

CiteScore

7.90

自引率

2.10%

发文量

审稿时长

10 weeks

期刊介绍： The official journal of the Japanese Society for Hygiene, Environmental Health and Preventive Medicine (EHPM) brings a comprehensive approach to prevention and environmental health related to medical, biological, molecular biological, genetic, physical, psychosocial, chemical, and other environmental factors. Environmental Health and Preventive Medicine features definitive studies on human health sciences and provides comprehensive and unique information to a worldwide readership.