Monitoring hand, foot and mouth disease by combining search engine query data and meteorological factors.

Hand, foot and mouth disease (HFMD) has been recognized as a significant public health threat and poses a tremendous challenge to disease control departments. To date, the relationship between meteorological factors and HFMD has been documented, and public interest of disease has been proven to be trackable from the Internet. However, no study has explored the combination of these two factors in the monitoring of HFMD. Therefore, the main aim of this study was to develop an effective monitoring model of HFMD in Guangzhou, China by utilizing historical HFMD cases, Internet-based search engine query data and meteorological factors. To this end, a case study was conducted in Guangzhou, using a network-based generalized additive model (GAM) including all factors related to HFMD. Three other models were also constructed using some of the variables for comparison. The results suggested that the model showed the best estimating ability when considering all of the related factors.

[1]  Taha Kass-Hout,et al.  A New Approach to Monitoring Dengue Activity , 2011, PLoS neglected tropical diseases.

[2]  S. Chuang,et al.  Is hand, foot and mouth disease associated with meteorological parameters? , 2010, Epidemiology and Infection.

[3]  Cheng-Dong Xu,et al.  Spatial dynamic patterns of hand-foot-mouth disease in the People's Republic of China. , 2013, Geospatial health.

[4]  Junzhi Wang,et al.  EV71 vaccine, an invaluable gift for children , 2014, Clinical & translational immunology.

[5]  Dennis KM Ip,et al.  A profile of the online dissemination of national influenza surveillance data , 2009, BMC public health.

[6]  E. Nsoesie,et al.  Monitoring Influenza Epidemics in China with Search Query from Baidu , 2013, PloS one.

[7]  N. Okabe,et al.  Hand, Foot, and Mouth Disease Caused by Coxsackievirus A6, Japan, 2011 , 2012, Emerging infectious diseases.

[8]  S. Groseclose,et al.  Completeness of notifiable infectious disease reporting in the United States: an analytical literature review. , 2002, American journal of epidemiology.

[9]  Declan Butler,et al.  When Google got flu wrong , 2013, Nature.

[10]  K. Goh,et al.  Epidemic Hand, Foot and Mouth Disease Caused by Human Enterovirus 71, Singapore , 2003, Emerging infectious diseases.

[11]  Michael J Kerin,et al.  The effect of breast cancer awareness month on internet search activity - a comparison with awareness campaigns for lung and prostate cancer , 2011, BMC Cancer.

[12]  Tao Liu,et al.  Early detection of an epidemic erythromelalgia outbreak using Baidu search data , 2015, Scientific Reports.

[13]  C. Goss,et al.  Monitoring Influenza Activity in the United States: A Comparison of Traditional Surveillance Systems with Google Flu Trends , 2011, PloS one.

[14]  P. Liu,et al.  Comparative epidemiology and virology of fatal and nonfatal cases of hand, foot and mouth disease in mainland China from 2008 to 2014 , 2015, Reviews in medical virology.

[15]  J. O'Loughlin,et al.  Influence of weather conditions and season on physical activity in adolescents. , 2009, Annals of epidemiology.

[16]  M. Phoon,et al.  The largest outbreak of hand; foot and mouth disease in Singapore in 2008: the role of enterovirus 71 and coxsackievirus A strains. , 2010, International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases.

[17]  Nawi Ng,et al.  Short-term Effects of Weather on Hand, Foot, and Mouth Disease , 2011 .

[18]  Hongyan Zhang,et al.  Towards Identifying and Reducing the Bias of Disease Information Extracted from Search Engine Data , 2016, PLoS Comput. Biol..

[19]  Qiyong Liu,et al.  The Effect of Meteorological Variables on the Transmission of Hand, Foot and Mouth Disease in Four Major Cities of Shanxi Province, China: A Time Series Data Analysis (2009-2013) , 2015, PLoS neglected tropical diseases.

[20]  Nanping Wu,et al.  Correlation between reported human infection with avian influenza A H7N9 virus and cyber user awareness: what can we learn from digital epidemiology? , 2014, International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases.

[21]  W. Goggins,et al.  Seasonal modeling of hand, foot, and mouth disease as a function of meteorological variations in Chongqing, China , 2017, International Journal of Biometeorology.

[22]  D. Cummings,et al.  Prediction of Dengue Incidence Using Search Query Surveillance , 2011, PLoS neglected tropical diseases.

[23]  I. Youngster,et al.  Hand, Foot, and Mouth Disease Caused by Coxsackievirus A6 , 2012 .

[24]  Wenjun Ma,et al.  Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China , 2017, PLoS neglected tropical diseases.

[25]  Alex R. Cook,et al.  Internet Search Limitations and Pandemic Influenza, Singapore , 2010, Emerging infectious diseases.

[26]  D. Lazer,et al.  The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.

[27]  K. Goh,et al.  Epidemiology and control of hand, foot and mouth disease in Singapore, 2001-2007. , 2009, Annals of the Academy of Medicine, Singapore.

[28]  George Christakos,et al.  Hand, foot and mouth disease: spatiotemporal transmission and climate , 2011, International journal of health geographics.

[29]  M. Hashizume,et al.  The influence of temperature and humidity on the incidence of hand, foot, and mouth disease in Japan. , 2011, The Science of the total environment.

[30]  Yiqun Liu,et al.  Predicting Epidemic Tendency through Search Behavior Analysis , 2011, IJCAI.

[31]  Y. Liao,et al.  A study of spatiotemporal delay in hand, foot and mouth disease in response to weather variations based on SVD: a case study in Shandong Province, China , 2015, BMC Public Health.

[32]  R. Ostfeld,et al.  Climate Change and Infectious Diseases: From Evidence to a Predictive Framework , 2013, Science.

[33]  Dong Seok Lee,et al.  Transmission of Seasonal Outbreak of Childhood Enteroviral Aseptic Meningitis and Hand-foot-mouth Disease , 2010, Journal of Korean medical science.

[34]  Dotan A. Haim,et al.  Using Networks to Combine “Big Data” and Traditional Surveillance to Improve Influenza Predictions , 2015, Scientific Reports.

[35]  Zhenglun Liang,et al.  EV71 vaccine, a new tool to control outbreaks of hand, foot and mouth disease (HFMD) , 2016, Expert review of vaccines.

[36]  P. Hosseini,et al.  Seasonality and the dynamics of infectious diseases. , 2006, Ecology letters.

[37]  Y. Liao,et al.  Determinants of the Incidence of Hand, Foot and Mouth Disease in China Using Geographically Weighted Regression Models , 2012, PloS one.

[38]  Y. Hao,et al.  Effect of meteorological variables on the incidence of hand, foot, and mouth disease in children: a time-series analysis in Guangzhou, China , 2013, BMC Infectious Diseases.

[39]  Paul R. Bergstresser,et al.  Google Technology in the Surveillance of Hand Foot Mouth Disease in Asia , 2014 .

[40]  T. Louis,et al.  Model choice in time series studies of air pollution and mortality , 2006 .

[41]  Gail M Williams,et al.  Internet-based surveillance systems for monitoring emerging infectious diseases , 2013, The Lancet Infectious Diseases.

[42]  Y. Poovorawan,et al.  Clinical and molecular characterization of hand-foot-and-mouth disease in Thailand, 2008-2009. , 2010, Japanese journal of infectious diseases.

[43]  S. Rutherford,et al.  Using Google Trends for Influenza Surveillance in South China , 2013, PloS one.

[44]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[45]  Cécile Viboud,et al.  Hand, foot, and mouth disease in China, 2008-12: an epidemiological study. , 2014, The Lancet. Infectious diseases.

[46]  Xiuhua Guo,et al.  Different effects of meteorological factors on hand, foot and mouth disease in various climates: a spatial panel data model analysis , 2016, BMC Infectious Diseases.

[47]  John S. Brownstein,et al.  Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends , 2014, PLoS neglected tropical diseases.

[48]  Mauricio Santillana,et al.  Accurate estimation of influenza epidemics using Google search data via ARGO , 2015, Proceedings of the National Academy of Sciences.

[49]  Stephen S Morse,et al.  Public health surveillance and infectious disease detection. , 2012, Biosecurity and bioterrorism : biodefense strategy, practice, and science.

[50]  Sandra Smole,et al.  Hand, Foot, and Mouth Disease Caused by Coxsackievirus A6 , 2012, Emerging infectious diseases.

[51]  Yang Yang,et al.  Using Baidu Search Index to Predict Dengue Outbreak in China , 2016, Scientific Reports.

[52]  Patrick Market,et al.  Meteorological conditions are associated with physical activities performed in open-air settings , 2008, International journal of biometeorology.

[53]  Kow-Tong Chen,et al.  An epidemic of enterovirus 71 infection in Taiwan. Taiwan Enterovirus Epidemic Working Group. , 1999, The New England journal of medicine.

[54]  J. Brownstein,et al.  Influenza A (H7N9) and the importance of digital epidemiology. , 2013, The New England journal of medicine.

[55]  N. Tien,et al.  Epidemiologic and Virologic Investigation of Hand, Foot, and Mouth Disease, Southern Vietnam, 2005 , 2007, Emerging infectious diseases.