Published on 01.06.16 in Vol 2, No 1 (2016): Jan-Jun
Works citing "Utilizing Nontraditional Data Sources for Near Real-Time Estimation of Transmission Dynamics During the 2015-2016 Colombian Zika Virus Disease Outbreak"
According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.5814):
(note that this is only a small subset of citations)
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Agarwal V, Zhang L, Zhu J, Fang S, Cheng T, Hong C, Shah NH. Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis. Journal of Medical Internet Research 2016;18(9):e251
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Li J, Xu Q, Cuomo R, Purushothaman V, Mackey T. Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study. JMIR Public Health and Surveillance 2020;6(2):e18700
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Gong X, Han Y, Hou M, Guo R. Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index. JMIR Public Health and Surveillance 2020;6(4):e23098
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Gianfredi V, Bragazzi NL, Nucci D, Martini M, Rosselli R, Minelli L, Moretti M. Harnessing Big Data for Communicable Tropical and Sub-Tropical Disorders: Implications From a Systematic Review of the Literature. Frontiers in Public Health 2018;6
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Liu Y, Lillepold K, Semenza JC, Tozan Y, Quam MB, Rocklöv J. Reviewing estimates of the basic reproduction number for dengue, Zika and chikungunya across global climate zones. Environmental Research 2020;182:109114
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Li C, Chen LJ, Chen X, Zhang M, Pang CP, Chen H. Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020. Eurosurveillance 2020;25(10)
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McGough SF, Brownstein JS, Hawkins JB, Santillana M, Althouse B. Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease Surveillance with Search, Social Media, and News Report Data. PLOS Neglected Tropical Diseases 2017;11(1):e0005295
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. Temporal patterns and geographic heterogeneity of Zika virus (ZIKV) outbreaks in French Polynesia and Central America. PeerJ 2017;5:e3015
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Alzahrani EO, Ahmad W, Altaf Khan M, Malebary SJ. Optimal Control Strategies of Zika Virus Model with Mutant. Communications in Nonlinear Science and Numerical Simulation 2021;93:105532
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L. DFA, González-Parra G, Benincasa T. Mathematical modeling and numerical simulations of Zika in Colombia considering mutation. Mathematics and Computers in Simulation 2019;163:1
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Kobres P, Chretien J, Johansson MA, Morgan JJ, Whung P, Mukundan H, Del Valle SY, Forshey BM, Quandelacy TM, Biggerstaff M, Viboud C, Pollett S, Pimenta PFP. A systematic review and evaluation of Zika virus forecasting and prediction research during a public health emergency of international concern. PLOS Neglected Tropical Diseases 2019;13(10):e0007451
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. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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Manore CA, Ostfeld RS, Agusto FB, Gaff H, LaDeau SL, Scarpino SV. Defining the Risk of Zika and Chikungunya Virus Transmission in Human Population Centers of the Eastern United States. PLOS Neglected Tropical Diseases 2017;11(1):e0005255
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Miller M, Banerjee T, Muppalla R, Romine W, Sheth A. What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, and Prevention. JMIR Public Health and Surveillance 2017;3(2):e38
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Moon H, Lee GH. Evaluation of Korean-Language COVID-19–Related Medical Information on YouTube: Cross-Sectional Infodemiology Study. Journal of Medical Internet Research 2020;22(8):e20775
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Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Suen J, Chen Y. Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan. BMJ Open 2020;10(7):e034156
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Aiken EL, McGough SF, Majumder MS, Wachtel G, Nguyen AT, Viboud C, Santillana M, Pulliam JR. Real-time estimation of disease activity in emerging outbreaks using internet search information. PLOS Computational Biology 2020;16(8):e1008117
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Vayena E, Dzenowagis J, Brownstein JS, Sheikh A. Policy implications of big data in the health sector. Bulletin of the World Health Organization 2018;96(1):66
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Anaya J, Rodríguez Y, Monsalve DM, Vega D, Ojeda E, González-Bravo D, Rodríguez-Jiménez M, Pinto-Díaz CA, Chaparro P, Gunturiz ML, Ansari AA, Gershwin ME, Molano-González N, Ramírez-Santana C, Acosta-Ampudia Y. A comprehensive analysis and immunobiology of autoimmune neurological syndromes during the Zika virus outbreak in Cúcuta, Colombia. Journal of Autoimmunity 2017;77:123
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Fitzgibbon WE, Morgan JJ, Webb GF. An outbreak vector-host epidemic model with spatial structure: the 2015–2016 Zika outbreak in Rio De Janeiro. Theoretical Biology and Medical Modelling 2017;14(1)
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Mavragani A, Ochoa G, Tsagarakis KP. Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review. Journal of Medical Internet Research 2018;20(11):e270
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Masri S, Jia J, Li C, Zhou G, Lee M, Yan G, Wu J. Use of Twitter data to improve Zika virus surveillance in the United States during the 2016 epidemic. BMC Public Health 2019;19(1)
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Teng Y, Bi D, Xie G, Jin Y, Huang Y, Lin B, An X, Feng D, Tong Y, Paul R. Dynamic Forecasting of Zika Epidemics Using Google Trends. PLOS ONE 2017;12(1):e0165085
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Barros JM, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. Journal of Medical Internet Research 2020;22(3):e13680
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Wang L, Zhao H, Oliva SM, Zhu H. Modeling the transmission and control of Zika in Brazil. Scientific Reports 2017;7(1)
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Ling R, Lee J. Disease Monitoring and Health Campaign Evaluation Using Google Search Activities for HIV and AIDS, Stroke, Colorectal Cancer, and Marijuana Use in Canada: A Retrospective Observational Study. JMIR Public Health and Surveillance 2016;2(2):e156
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Keegan LT, Lessler J, Johansson MA. Quantifying Zika: Advancing the Epidemiology of Zika With Quantitative Models. The Journal of Infectious Diseases 2017;216(suppl_10):S884
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Ospina J, Hincapie‐Palacio D, Ochoa J, Molina A, Rúa G, Pájaro D, Arrubla M, Almanza R, Paredes M, Mubayi A. Stratifying the potential local transmission of Zika in municipalities of Antioquia, Colombia. Tropical Medicine & International Health 2017;22(10):1249
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Bragazzi NL, Alicino C, Trucchi C, Paganino C, Barberis I, Martini M, Sticchi L, Trinka E, Brigo F, Ansaldi F, Icardi G, Orsi A, Olson DR. Global reaction to the recent outbreaks of Zika virus: Insights from a Big Data analysis. PLOS ONE 2017;12(9):e0185263
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Ayyoubzadeh SM, Ayyoubzadeh SM, Zahedi H, Ahmadi M, R Niakan Kalhori S. Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study. JMIR Public Health and Surveillance 2020;6(2):e18828
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Gardy JL, Loman NJ. Towards a genomics-informed, real-time, global pathogen surveillance system. Nature Reviews Genetics 2018;19(1):9
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Chesnut M, Muñoz LS, Harris G, Freeman D, Gama L, Pardo CA, Pamies D. In vitro and in silico Models to Study Mosquito-Borne Flavivirus Neuropathogenesis, Prevention, and Treatment. Frontiers in Cellular and Infection Microbiology 2019;9
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Arora N, Banerjee AK, Narasu ML. Zika outbreak aftermath: status, progress, concerns and new insights. Future Virology 2018;13(8):539
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Jones R, Kulkarni MA, Davidson TMV, Talbot B, Samy AM. Arbovirus vectors of epidemiological concern in the Americas: A scoping review of entomological studies on Zika, dengue and chikungunya virus vectors. PLOS ONE 2020;15(2):e0220753
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Higgins TS, Wu AW, Sharma D, Illing EA, Rubel K, Ting JY. Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study. JMIR Public Health and Surveillance 2020;6(2):e19702
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Hou Z, Du F, Zhou X, Jiang H, Martin S, Larson H, Lin L. Cross-Country Comparison of Public Awareness, Rumors, and Behavioral Responses to the COVID-19 Epidemic: Infodemiology Study. Journal of Medical Internet Research 2020;22(8):e21143
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Mavragani A, Ochoa G. Infoveillance of infectious diseases in USA: STDs, tuberculosis, and hepatitis. Journal of Big Data 2018;5(1)
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Mendivelso Duarte FO, Robayo García A, Rodríguez Bedoya M, Suárez Rángel G. Notificación de defectos congénitos por brote del virus del Zika en Colombia, 2015-2017. Revista Panamericana de Salud Pública 2019;43:1
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Akhtar M, Kraemer MUG, Gardner LM. A dynamic neural network model for predicting risk of Zika in real time. BMC Medicine 2019;17(1)
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He D, Gao D, Lou Y, Zhao S, Ruan S. A comparison study of Zika virus outbreaks in French Polynesia, Colombia and the State of Bahia in Brazil. Scientific Reports 2017;7(1)
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Majumder M, Rose S. Vaccine Deployment and Ebola Transmission Dynamics Estimation in Eastern DR Congo. SSRN Electronic Journal 2018;
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Majumder MS, Nguyen CM, Cohn EL, Hswen Y, Mekaru SR, Brownstein JS. Vaccine compliance and the 2016 Arkansas mumps outbreak. The Lancet Infectious Diseases 2017;17(4):361
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Nasrinpour HR, Reimer AA, Friesen MR, McLeod RD. Data Preparation for West Nile Virus Agent-Based Modelling: Protocol for Processing Bird Population Estimates and Incorporating ArcMap in AnyLogic. JMIR Research Protocols 2017;6(7):e138
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. A novel IDEA: The impact of serial interval on a modified-Incidence Decay and Exponential Adjustment (m-IDEA) model for projections of daily COVID-19 cases. Infectious Disease Modelling 2020;5:346
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Peng Y, Li C, Rong Y, Chen X, Chen H. Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning. Journal of Global Health 2020;10(2)
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. Big Data Technology in Museum Exhibition Digitization. Journal of Physics: Conference Series 2020;1648(4):042044
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Kurian SJ, Bhatti AUR, Alvi MA, Ting HH, Storlie C, Wilson PM, Shah ND, Liu H, Bydon M. Correlations Between COVID-19 Cases and Google Trends Data in the United States: A State-by-State Analysis. Mayo Clinic Proceedings 2020;95(11):2370
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Kogan NE, Clemente L, Liautaud P, Kaashoek J, Link NB, Nguyen AT, Lu FS, Huybers P, Resch B, Havas C, Petutschnig A, Davis J, Chinazzi M, Mustafa B, Hanage WP, Vespignani A, Santillana M. An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time. Science Advances 2021;7(10)
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R Niakan Kalhori S, Bahaadinbeigy K, Deldar K, Gholamzadeh M, Hajesmaeel-Gohari S, Ayyoubzadeh SM. Digital Health Solutions to Control the COVID-19 Pandemic in Countries With High Disease Prevalence: Literature Review. Journal of Medical Internet Research 2021;23(3):e19473
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Smith BA, Bancej C, Fazil A, Mullah M, Yan P, Zhang S. The performance of phenomenological models in providing near-term Canadian case projections in the midst of the COVID-19 pandemic: March – April, 2020. Epidemics 2021;35:100457
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Nsoesie EO, Oladeji O, Abah ASA, Ndeffo-Mbah ML. Forecasting influenza-like illness trends in Cameroon using Google Search Data. Scientific Reports 2021;11(1)
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de Freitas C, Amorim M, Machado H, Leão Teles E, Baptista MJ, Renedo A, Provoost V, Silva S. Public and patient involvement in health data governance (DATAGov): protocol of a people-centred, mixed-methods study on data use and sharing for rare diseases care and research. BMJ Open 2021;11(3):e044289
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Lima Y, Pinheiro W, Barbosa CE, Magalhães M, Chaves M, de Souza JM, Rodrigues S, Xexéo G. Development of an Index for the Inspection of Aedes aegypti Breeding Sites in Brazil: Multi-criteria Analysis. JMIR Public Health and Surveillance 2021;7(5):e19502
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Yiu C, Macon-Cooney B, Fingerhut H. A research and policy agenda for the post-pandemic world. Future Healthcare Journal 2021;8(2):e198
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Kiang MV, Chen JT, Krieger N, Buckee CO, Alexander MJ, Baker JT, Buckner RL, Coombs G, Rich-Edwards JW, Carlson KW, Onnela J. Sociodemographic characteristics of missing data in digital phenotyping. Scientific Reports 2021;11(1)
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Majumder MS, Rose S. A generalizable data assembly algorithm for infectious disease outbreaks. JAMIA Open 2021;4(3)
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Saegner T, Austys D. Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review. International Journal of Environmental Research and Public Health 2022;19(19):12394
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Lan H, Sha D, Malarvizhi AS, Liu Y, Li Y, Meister N, Liu Q, Wang Z, Yang J, Yang CP. COVID-Scraper: An Open-Source Toolset for Automatically Scraping and Processing Global Multi-Scale Spatiotemporal COVID-19 Records. IEEE Access 2021;9:84783
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Ganser I, Thiébaut R, Buckeridge DL. Global Variations in Event-Based Surveillance for Disease Outbreak Detection: Time Series Analysis. JMIR Public Health and Surveillance 2022;8(10):e36211
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Satpathy P, Kumar S, Prasad P. Suitability of Google Trends™ for Digital Surveillance During Ongoing COVID-19 Epidemic: A Case Study from India. Disaster Medicine and Public Health Preparedness 2023;17
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Majumder MS, Cusick M, Rose S. Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis. BMJ Open 2023;13(2):e065751
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TİRGİL M, ÇULHA E, DEMİRCİ . Google arama motoru Türkiye’de Covid-19 salgınının yayılımının izlenmesinde ve tahmininde kullanılabilir mi?. Mersin Üniversitesi Sağlık Bilimleri Dergisi 2021;14(3):520
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Ben S, Xin J, Chen S, Jiang Y, Yuan Q, Su L, Christiani DC, Zhang Z, Du M, Wang M. Global internet search trends related to gastrointestinal symptoms predict regional COVID-19 outbreaks. Journal of Infection 2022;84(1):56
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MacIntyre CR, Chen X, Kunasekaran M, Quigley A, Lim S, Stone H, Paik H, Yao L, Heslop D, Wei W, Sarmiento I, Gurdasani D. Artificial intelligence in public health: the potential of epidemic early warning systems. Journal of International Medical Research 2023;51(3):030006052311593
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Zafar ZUA, Khan MA, Inc M, Akgül A, Asiri M, Riaz MB. The analysis of a new fractional model to the Zika virus infection with mutant. Heliyon 2024;10(1):e23390
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wei S, Lin S, wenjing Z, Shaoxia S, Yuejie Y, Yujie H, Shu Z, Zhong L, Ti L. The prediction of influenza-like illness using national influenza surveillance data and Baidu query data. BMC Public Health 2024;24(1)
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According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.5814):
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da Silva DA, Goncalves GS, dos Santos SC, Pugliese VU, Navas J, de Barros Santana RM, Queiroz FS, Dias LAV, da Cunha AM, Tasinaffo PM. Information Technology – New Generations. 2018. Chapter 34:233
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Morley M, Majumder MS, Gallanis T, Wilson J. Leveraging Data Science for Global Health. 2020. Chapter 28:443
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Waring OM, Majumder MS. Leveraging Data Science for Global Health. 2020. Chapter 15:251
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Saifullah M, Adnan M, Arshad M, Waqas M, Mehmood A. Challenges in Agro-Climate and Ecosystem. 2022. Chapter 1
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Gilbert J, Niu J, de Montigny S, Ng V, Rees E. AI for Disease Surveillance and Pandemic Intelligence. 2022. Chapter 9:101
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Birthare P, Raja M, Ramachandran G, Hargreaves CA, Birthare S. Structural and Functional Aspects of Biocomputing Systems for Data Processing. 2023. chapter 2:28
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