Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China
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 use...
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Nature Portfolio
2018
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oai:doaj.org-article:13f665f387304887857321e13c07c7be2021-12-02T15:09:02ZUsing the Baidu Search Index to Predict the Incidence of HIV/AIDS in China10.1038/s41598-018-27413-12045-2322https://doaj.org/article/13f665f387304887857321e13c07c7be2018-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-27413-1https://doaj.org/toc/2045-2322Abstract 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.Guangye HeYunsong ChenBuwei ChenHao WangLi ShenLiu LiuDeji SuolangBoyang ZhangGuodong JuLiangliang ZhangSijia DuXiangxue JiangYu PanZuntao MinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-10 (2018) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Guangye He Yunsong Chen Buwei Chen Hao Wang Li Shen Liu Liu Deji Suolang Boyang Zhang Guodong Ju Liangliang Zhang Sijia Du Xiangxue Jiang Yu Pan Zuntao Min Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China |
| description |
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. |
| format |
article |
| author |
Guangye He Yunsong Chen Buwei Chen Hao Wang Li Shen Liu Liu Deji Suolang Boyang Zhang Guodong Ju Liangliang Zhang Sijia Du Xiangxue Jiang Yu Pan Zuntao Min |
| author_facet |
Guangye He Yunsong Chen Buwei Chen Hao Wang Li Shen Liu Liu Deji Suolang Boyang Zhang Guodong Ju Liangliang Zhang Sijia Du Xiangxue Jiang Yu Pan Zuntao Min |
| author_sort |
Guangye He |
| title |
Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China |
| title_short |
Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China |
| title_full |
Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China |
| title_fullStr |
Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China |
| title_full_unstemmed |
Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China |
| title_sort |
using the baidu search index to predict the incidence of hiv/aids in china |
| publisher |
Nature Portfolio |
| publishDate |
2018 |
| url |
https://doaj.org/article/13f665f387304887857321e13c07c7be |
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