Using Google Trends and ambient temperature to predict seasonal influenza outbreaks

Environment International

Volumn 117, Issue , 2018, Pages 284-291

  Zhang, Yuzhou ^a   Bambrick, Hilary ^a   Mengersen, Kerrie ^a   Tong, Shilu ^a,b,c   Hu, Wenbiao ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b ANHUI MEDICAL UNIVERSITY   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Early warning; Prediction; Search terms; Seasonal influenza; Temperature

Indexed keywords

CLIMATE MODELS; EPIDEMIOLOGY; FORECASTING; NETWORK SECURITY; REGRESSION ANALYSIS; RISK ANALYSIS; RISK ASSESSMENT; TEMPERATURE; TIME SERIES ANALYSIS; TREES (MATHEMATICS);

CROSS-CORRELATION ANALYSIS; EARLY WARNING; EARLY WARNING SYSTEM; PREDICTIVE PERFORMANCE; REGRESSION TREE MODELS; SEARCH TERMS; SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGES; SEASONAL INFLUENZA;

SEARCH ENGINES;

EARLY WARNING SYSTEM; EPIDEMIOLOGY; INFLUENZA; INTERNET; PREDICTION; SEASONALITY; TEMPERATURE;

ARTICLE; CLIMATE; CONTROLLED STUDY; ENVIRONMENTAL TEMPERATURE; INFLUENZA A; INFLUENZA B; INTERNET; PREDICTION; PRIORITY JOURNAL; RISK ASSESSMENT; SEASONAL INFLUENZA; TIME SERIES ANALYSIS; UNITED KINGDOM; HUMAN; INFLUENZA; SEASON; STATISTICAL MODEL; TEMPERATURE;

AUSTRALIA; BRISBANE; GOLD COAST; QUEENSLAND;

CLIMATE; HUMANS; INFLUENZA, HUMAN; INTERNET; MODELS, STATISTICAL; SEASONS; TEMPERATURE;

EID: 85047070411     PISSN: 01604120     EISSN: 18736750     Source Type: Journal    
DOI: 10.1016/j.envint.2018.05.016     Document Type: Article

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