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. 2018 Jun 13;8(1):9038.
doi: 10.1038/s41598-018-27413-1.

Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China

Guangye He  1 , Yunsong Chen  2   3 , Buwei Chen  4 , Hao Wang  5 , Li Shen  6 , Liu Liu  7 , Deji Suolang  7 , Boyang Zhang  7 , Guodong Ju  7 , Liangliang Zhang  7 , Sijia Du  7 , Xiangxue Jiang  7 , Yu Pan  7 , Zuntao Min  7
Affiliations

Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China

Guangye He et al. Sci Rep. .

Abstract

Based on a panel of 30 provinces and a timeframe from January 2009 to December 2013, we estimate the association between monthly human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) incidence and the relevant Internet search query volumes in Baidu, the most widely used search engine among the Chinese. The pooled mean group (PMG) model show that the Baidu search index (BSI) positively predicts the increase in HIV/AIDS incidence, with a 1% increase in BSI associated with a 2.1% increase in HIV/AIDS incidence on average. This study proposes a promising method to estimate and forecast the incidence of HIV/AIDS, a type of infectious disease that is culturally sensitive and highly unevenly distributed in China; the method can be taken as a complement to a traditional HIV/AIDS surveillance system.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Yearly HIV/AIDS incidence in China by province in 2009 and 2013. The yearly incidence data is calculated by summing up the monthly incidence in 2009 and 2013 from the CDC-reported incidence records for each province. To show the trend of provincial HIV/AIDS incidence from 2009 to 2013, we use the “spmap” command in STATA14.0 to draw the map.
Figure 2
Figure 2
Standardized monthly HIV/AIDS incidence and BSI by province, January 2009–December 2013.
Figure 3
Figure 3
Standard error for the PMG model.
Figure 4
Figure 4
True and predicted logCDC in six provinces with high HIV/AIDS concentration, using the PMG model.
Figure 5
Figure 5
Forecasted log CDC. The forecasting is conducted in low and high HIV/AIDS prevalence areas respectively; high prevalence areas include Anhui, Jiangxi, Henan, Hubei, Hunan, Guangdong, Guangxi, Chongqing, Sichuan, Guizhou and Yunnan.
Figure 6
Figure 6
Forecasted error by province.
See this image and copyright information in PMC

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