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Using Baidu Search Engine to Monitor AIDS Epidemics Inform for Targeted intervention of HIV/AIDS in China by Kang Li; Meiliang Liu; Yi Feng; Chuanyi Ning; Weidong Ou; Jia Sun; Wudi Wei; Hao Liang; Yiming Shao is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract China’s reported cases of Human Immunodeficiency Virus (HIV) and AIDS increased from over 50000 in 2011 to more than 130000 in 2017, while AIDS related search indices on Baidu from 2.1 million to 3.7 million in the same time periods. In China, people seek AIDS related knowledge from Baidu which one of the world’s largest search engine. We study the relationship of national HIV surveillance data with the Baidu index (BDI) and use it to monitor AIDS epidemic and inform targeted intervention. After screening keywords and making index composition, we used seasonal autoregressive integrated moving average (ARIMA) modeling. The most correlated search engine query data was obtained by using ARIMA with external variables (ARIMAX) model for epidemic prediction. A significant correlation between monthly HIV/AIDS report cases and Baidu Composite Index (__r__ = 0.845, __P__ < 0.001) was observed using time series plot. Compared with the ARIMA model based on AIDS surveillance data, the ARIMAX model with Baidu Composite Index had the minimal an Akaike information criterion (AIC, 839.42) and the most exact prediction (MAPE of 6.11%). We showed that there are close correlations of the

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Author

Kang Li; Meiliang Liu; Yi Feng; Chuanyi Ning; Weidong Ou; Jia Sun; Wudi Wei; Hao Liang; Yiming Shao

Publisher

Springer Science and Business Media LLC

Published

2019

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)