Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China

PLoS Neglected Tropical Diseases

Volumn 11, Issue 3, 2017, Pages

  Li, Zhihao ^a   Liu, Tao ^a   Zhu, Guanghu ^a,b   Lin, Hualiang ^a   Zhang, Yonghui ^a   He, Jianfeng ^a   Deng, Aiping ^a   Peng, Zhiqiang ^a   Xiao, Jianpeng ^a   Rutherford, Shannon ^c   Xie, Runsheng ^a   Zeng, Weilin ^a   Li, Xing ^a   Ma, Wenjun ^a  

^a GUANGZHOU CENTER FOR DISEASE CONTROL AND PREVENTION   (China)

^b GUILIN UNIVERSITY OF ELECTRONIC TECHNOLOGY   (China)

^c GRIFFITH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

RAIN;

ARTICLE; CASE STUDY; CLIMATE; DATA BASE; DENGUE; DENGUE BAIDU SEARCH INDEX; DISEASE SURVEILLANCE; ENVIRONMENTAL FACTOR; EPIDEMIC; GENERALIZED ADDITIVE MODEL; GENERALIZED CROSS VALIDATION; HUMAN; INFORMATION PROCESSING; METEOROLOGICAL PHENOMENA; PREDICTION; ROOT MEAN SQUARED ERROR; SEMANTICS; SENSITIVITY ANALYSIS; STATISTICAL MODEL; TEMPERATURE; CHINA; EPIDEMIOLOGICAL MONITORING; EVALUATION STUDY; INTERNET;

CHINA; DENGUE; EPIDEMICS; EPIDEMIOLOGICAL MONITORING; INTERNET; METEOROLOGICAL CONCEPTS; MODELS, STATISTICAL;

EID: 85016986871     PISSN: 19352727     EISSN: 19352735     Source Type: Journal    
DOI: 10.1371/journal.pntd.0005354     Document Type: Article

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