Harnessing Big Data for Communicable Tropical and Sub-Tropical Disorders: Implications From a Systematic Review of the Literature
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Nicola Luigi Bragazzi | Liliana Minelli | Vincenza Gianfredi | Daniele Nucci | Mariano Martini | Massimo Moretti | Roberto Rosselli | N. Bragazzi | M. Martini | V. Gianfredi | R. Rosselli | M. Moretti | D. Nucci | L. Minelli
[1] J. Tait,et al. Challenges and opportunities. , 1996, Journal of psychiatric and mental health nursing.
[2] Mark Dredze,et al. Could behavioral medicine lead the web data revolution? , 2014, JAMA.
[3] D. Moher,et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. , 2010, International journal of surgery.
[4] A. Chamberlain,et al. Use of Obstetric Practice Web Sites to Distribute Zika Virus Information to Pregnant Women During a Zika Virus Outbreak , 2017, Journal of public health management and practice : JPHMP.
[5] Amit P. Sheth,et al. What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention , 2017, JMIR public health and surveillance.
[6] Alessandro Lovari,et al. Communicating the Ontological Narrative of Ebola: An Emerging Disease in the Time of “Epidemic 2.0” , 2017, Health communication.
[7] R. Merchant,et al. Public sentiment and discourse about Zika virus on Instagram. , 2017, Public health.
[8] G. Eysenbach. Infodemiology: The epidemiology of (mis)information. , 2002, The American journal of medicine.
[9] Jay M Bernhardt,et al. Identifying the public's concerns and the Centers for Disease Control and Prevention's reactions during a health crisis: An analysis of a Zika live Twitter chat. , 2016, American journal of infection control.
[10] Eugen Trinka,et al. Global reaction to the recent outbreaks of Zika virus: Insights from a Big Data analysis , 2017, PloS one.
[11] Sands A. Fish,et al. Digital Health Communication and Global Public Influence: A Study of the Ebola Epidemic , 2017, Journal of health communication.
[12] Pedagógia,et al. Cross Sectional Study , 2019 .
[13] Zion Tsz Ho Tse,et al. How people react to Zika virus outbreaks on Twitter? A computational content analysis. , 2016, American journal of infection control.
[14] E. Gould,et al. Emerging arboviruses: Why today? , 2017, One health.
[15] Gail M. Williams,et al. Status of soil-transmitted helminth infections in schoolchildren in Laguna Province, the Philippines: Determined by parasitological and molecular diagnostic techniques , 2017, PLoS neglected tropical diseases.
[16] R. Peeling,et al. Re-imagining the future of diagnosis of Neglected Tropical Diseases , 2017, Computational and Structural Biotechnology Journal.
[17] Jay M Bernhardt,et al. Local Health Departments Tweeting About Ebola: Characteristics and Messaging , 2017, Journal of public health management and practice : JPHMP.
[18] D. Moher,et al. Nonalcoholic Fatty Liver Disease and Acute Ischemic Stroke , 2010 .
[19] Virginia Murray,et al. Developing the Philippines as a Global Hub for Disaster Risk Reduction - A Health Research Initiative as Presented at the 10th Philippine National Health Research System Week Celebration , 2016, PLoS currents.
[20] G. Eysenbach. Infodemiology and Infoveillance: Framework for an Emerging Set of Public Health Informatics Methods to Analyze Search, Communication and Publication Behavior on the Internet , 2009, Journal of medical Internet research.
[21] C. Basch,et al. Zika Virus on YouTube: An Analysis of English-language Video Content by Source , 2017, Journal of preventive medicine and public health = Yebang Uihakhoe chi.
[22] Zhuangbo Feng,et al. Study on spatiotemporal distribution of airborne ozone pollution in subtropical region considering socioeconomic driving impacts: A case study in Guangzhou, China , 2020 .
[23] Kimberly C. Brouwer,et al. Emerging and Reemerging Neglected Tropical Diseases: a Review of Key Characteristics, Risk Factors, and the Policy and Innovation Environment , 2014, Clinical Microbiology Reviews.
[24] P. Hotez. The poverty-related neglected diseases: Why basic research matters , 2017, PLoS biology.
[25] Anthony A. Donato,et al. YouTube as a Source of Information on Ebola Virus Disease , 2015, North American journal of medical sciences.
[26] D. Lazer,et al. The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.
[27] Claudia Pagliari,et al. What’s buzzing on your feed? Health authorities’ use of Facebook to combat Zika in Singapore , 2017, J. Am. Medical Informatics Assoc..
[28] Sunmoo Yoon,et al. What can we learn about the Ebola outbreak from tweets? , 2015, American journal of infection control.
[29] Yong Huang,et al. Dynamic Forecasting of Zika Epidemics Using Google Trends , 2016, bioRxiv.
[30] N. Nii-Trebi. Emerging and Neglected Infectious Diseases: Insights, Advances, and Challenges , 2017, BioMed research international.
[31] C. Dolea,et al. World Health Organization , 1949, International Organization.
[32] Zion Tsz Ho Tse,et al. Zika-Virus-Related Photo Sharing on Pinterest and Instagram , 2017, Disaster Medicine and Public Health Preparedness.
[33] Enny Das,et al. Too Far to Care? Measuring Public Attention and Fear for Ebola Using Twitter , 2017, Journal of medical Internet research.
[34] Steven H. Hinrichs,et al. Forecasting the Spread of Mosquito-Borne Disease using Publicly Accessible Data: A Case Study in Chikungunya , 2016, AMIA.
[35] Tao Liu,et al. Developing a dengue forecast model using machine learning: A case study in China , 2017, PLoS neglected tropical diseases.
[36] John S. Brownstein,et al. Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease Surveillance with Search, Social Media, and News Report Data , 2017, PLoS neglected tropical diseases.
[37] Zion Tsz Ho Tse,et al. Ebola and the social media , 2014, The Lancet.
[38] Chang-Tien Lu,et al. Misinformation Propagation in the Age of Twitter , 2014, Computer.
[39] Mowafa Said Househ,et al. Communicating Ebola through social media and electronic news media outlets: A cross-sectional study , 2016, Health Informatics J..
[40] Adyasha Maharana,et al. Social Media as a Sentinel for Disease Surveillance: What Does Sociodemographic Status Have to Do with It? , 2016, PLoS currents.
[41] David A. Broniatowski,et al. Zika vaccine misconceptions: A social media analysis. , 2016, Vaccine.
[42] J. Brownstein,et al. Early detection of disease outbreaks using the Internet , 2009, Canadian Medical Association Journal.
[43] J. Brownstein,et al. Digital disease detection--harnessing the Web for public health surveillance. , 2009, The New England journal of medicine.
[44] Didier Fontenille,et al. An ecological and digital epidemiology analysis on the role of human behavior on the 2014 Chikungunya outbreak in Martinique , 2017, Scientific Reports.
[45] Zion Tsz Ho Tse,et al. Social Media's Initial Reaction to Information and Misinformation on Ebola , 2016 .
[46] Nicola Luigi Bragazzi,et al. Infodemiological data of West-Nile virus disease in Italy in the study period 2004–2015 , 2016, Data in brief.
[47] Hai Liang,et al. #Globalhealth Twitter Conversations on #Malaria, #HIV, #TB, #NCDS, and #NTDS: a Cross-Sectional Analysis. , 2017, Annals of global health.
[48] Wagner Meira,et al. Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level , 2017, PLoS neglected tropical diseases.
[49] Y. Strekalova. Health Risk Information Engagement and Amplification on Social Media , 2017, Health education & behavior : the official publication of the Society for Public Health Education.
[50] Brian G. Southwell,et al. Zika Virus–Related News Coverage and Online Behavior, United States, Guatemala, and Brazil , 2016, Emerging infectious diseases.
[51] Jay M Bernhardt,et al. Detecting themes of public concern: a text mining analysis of the Centers for Disease Control and Prevention's Ebola live Twitter chat. , 2015, American journal of infection control.
[52] 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.
[53] Zion Tsz Ho Tse,et al. Social Media's Initial Reaction to Information and Misinformation on Ebola, August 2014: Facts and Rumors , 2016, Public health reports.
[54] Naren Ramakrishnan,et al. Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks , 2016, Scientific Reports.
[55] Kelly V. Ruggles,et al. Coverage of the Ebola Virus Disease Epidemic on YouTube , 2015, Disaster Medicine and Public Health Preparedness.
[56] Li Li,et al. Chinese Public Attention to the Outbreak of Ebola in West Africa: Evidence from the Online Big Data Platform , 2016, International journal of environmental research and public health.
[57] J. Brownstein,et al. Using search queries for malaria surveillance, Thailand , 2013, Malaria Journal.
[58] D. Mohan,et al. YouTube videos as a source of medical information during the Ebola hemorrhagic fever epidemic , 2015, SpringerPlus.
[59] F. Islami,et al. Multimorbidity: Epidemiology and Risk Factors in the Golestan Cohort Study, Iran , 2016, Medicine.
[60] Laurent Hébert-Dufresne,et al. Enhancing disease surveillance with novel data streams: challenges and opportunities , 2015, EPJ Data Science.
[61] Virgílio A. F. Almeida,et al. Dengue surveillance based on a computational model of spatio-temporal locality of Twitter , 2011, WebSci '11.
[62] N. Bragazzi,et al. Discrepancies Between Classic and Digital Epidemiology in Searching for the Mayaro Virus: Preliminary Qualitative and Quantitative Analysis of Google Trends , 2017, JMIR public health and surveillance.
[63] Carlos Castillo-Chavez,et al. Mass Media and the Contagion of Fear: The Case of Ebola in America , 2015, PloS one.
[64] Dieter Pfoser,et al. Zika in Twitter: Temporal Variations of Locations, Actors, and Concepts , 2017, JMIR public health and surveillance.
[65] Mauricio Santillana,et al. Utilizing Nontraditional Data Sources for Near Real-Time Estimation of Transmission Dynamics During the 2015-2016 Colombian Zika Virus Disease Outbreak , 2016, JMIR public health and surveillance.
[66] Daniela Amicizia,et al. Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes , 2015 .
[67] K. Ferdinand,et al. Zika virus pandemic—analysis of Facebook as a social media health information platform , 2017, American journal of infection control.
[68] F Kooti,et al. Social Media Analysis , 2017, Encyclopedia of GIS.