Dynamic Forecasting of Zika Epidemics Using Google Trends
Publication Date
January 06, 2017
Authors
Yue Teng, Dehua Bi, Guigang Xie, Yuan Jin, et al
Volume
12
Issue
1
Pages
e0165085
DOI
https://dx.plos.org/10.1371/journal.pone.0165085
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0165085
Scopus
85009227815
Mendeley
http://www.mendeley.com/research/dynamic-forecasting-zika-epidemics-using-google-trends
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Mendeley | Further Information

{"title"=>"Dynamic forecasting of zika epidemics using google trends", "type"=>"journal", "authors"=>[{"first_name"=>"Yue", "last_name"=>"Teng", "scopus_author_id"=>"57192934150"}, {"first_name"=>"Dehua", "last_name"=>"Bi", "scopus_author_id"=>"57192927477"}, {"first_name"=>"Guigang", "last_name"=>"Xie", "scopus_author_id"=>"57192927900"}, {"first_name"=>"Yuan", "last_name"=>"Jin", "scopus_author_id"=>"55360676400"}, {"first_name"=>"Yong", "last_name"=>"Huang", "scopus_author_id"=>"56990479000"}, {"first_name"=>"Baihan", "last_name"=>"Lin", "scopus_author_id"=>"56662647100"}, {"first_name"=>"Xiaoping", "last_name"=>"An", "scopus_author_id"=>"7102948557"}, {"first_name"=>"Dan", "last_name"=>"Feng", "scopus_author_id"=>"57192927328"}, {"first_name"=>"Yigang", "last_name"=>"Tong", "scopus_author_id"=>"7202614688"}], "year"=>2017, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-85009227815", "sgr"=>"85009227815", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0165085", "pmid"=>"28060809", "isbn"=>"1111111111", "pui"=>"614015566"}, "id"=>"1437447f-c7a6-3c75-9d94-3580bbc22a7e", "abstract"=>"We developed a dynamic forecasting model for Zika virus (ZIKV), based on real-time online search data from Google Trends (GTs). It was designed to provide Zika virus disease (ZVD) surveillance and detection for Health Departments, and predictive numbers of infection cases, which would allow them sufficient time to implement interventions. In this study, we found a strong correlation between Zika-related GTs and the cumulative numbers of reported cases (confirmed, suspected and total cases; p<0.001). Then, we used the correlation data from Zika-related online search in GTs and ZIKV epidemics between 12 February and 20 October 2016 to construct an autoregressive integrated moving average (ARIMA) model (0, 1, 3) for the dynamic estimation of ZIKV outbreaks. The forecasting results indicated that the predicted data by ARIMA model, which used the online search data as the external regressor to enhance the forecasting model and assist the historical epidemic data in improving the quality of the predictions, are quite similar to the actual data during ZIKV epidemic early November 2016. Integer-valued autoregression provides a useful base predictive model for ZVD cases. This is enhanced by the incorporation of GTs data, confirming the prognostic utility of search query based surveillance. This accessible and flexible dynamic forecast model could be used in the monitoring of ZVD to provide advanced warning of future ZIKV outbreaks.", "link"=>"http://www.mendeley.com/research/dynamic-forecasting-zika-epidemics-using-google-trends", "reader_count"=>38, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Student > Doctoral Student"=>1, "Researcher"=>9, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>2, "Other"=>2, "Student > Master"=>6, "Student > Bachelor"=>2, "Lecturer"=>5, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Student > Doctoral Student"=>1, "Researcher"=>9, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>2, "Other"=>2, "Student > Master"=>6, "Student > Bachelor"=>2, "Lecturer"=>5, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Agricultural and Biological Sciences"=>8, "Veterinary Science and Veterinary Medicine"=>3, "Business, Management and Accounting"=>1, "Computer Science"=>5, "Earth and Planetary Sciences"=>1, "Engineering"=>1, "Nursing and Health Professions"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>8, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Social Sciences"=>4, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Social Sciences"=>{"Social Sciences"=>4}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Engineering"=>{"Engineering"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>8}, "Computer Science"=>{"Computer Science"=>5}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>3}}, "reader_count_by_country"=>{"United Kingdom"=>1}, "group_count"=>9}

Scopus | Further Information

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