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Citing this Article

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Published on 01.06.16 in Vol 2, No 1 (2016): Jan-Jun

This paper is in the following e-collection/theme issue:

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)

  1. 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
    CrossRef
  2. 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
    CrossRef
  3. Smith BA. 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
    CrossRef
  4. 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
    CrossRef
  5. 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
    CrossRef
  6. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  7. 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
    CrossRef
  8. 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)
    CrossRef
  9. 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
    CrossRef
  10. 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
    CrossRef
  11. 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
    CrossRef
  12. 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
    CrossRef
  13. 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)
    CrossRef
  14. 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
    CrossRef
  15. 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
    CrossRef
  16. 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
    CrossRef
  17. Akhtar M, Kraemer MUG, Gardner LM. A dynamic neural network model for predicting risk of Zika in real time. BMC Medicine 2019;17(1)
    CrossRef
  18. Gardy JL, Loman NJ. Towards a genomics-informed, real-time, global pathogen surveillance system. Nature Reviews Genetics 2018;19(1):9
    CrossRef
  19. 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
    CrossRef
  20. Majumder M, Rose S. Vaccine Deployment and Ebola Transmission Dynamics Estimation in Eastern DR Congo. SSRN Electronic Journal 2018;
    CrossRef
  21. 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
    CrossRef
  22. 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
    CrossRef
  23. Arora N, Banerjee AK, Narasu ML. Zika outbreak aftermath: status, progress, concerns and new insights. Future Virology 2018;13(8):539
    CrossRef
  24. Mavragani A, Ochoa G. Infoveillance of infectious diseases in USA: STDs, tuberculosis, and hepatitis. Journal of Big Data 2018;5(1)
    CrossRef
  25. 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
    CrossRef
  26. 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
    CrossRef
  27. 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
    CrossRef
  28. 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
    CrossRef
  29. Hsieh Y. Temporal patterns and geographic heterogeneity of Zika virus (ZIKV) outbreaks in French Polynesia and Central America. PeerJ 2017;5:e3015
    CrossRef
  30. 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)
    CrossRef
  31. 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
    CrossRef
  32. 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
    CrossRef
  33. 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
    CrossRef
  34. 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
    CrossRef
  35. 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)
    CrossRef
  36. 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
    CrossRef
  37. 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
    CrossRef
  38. Wang L, Zhao H, Oliva SM, Zhu H. Modeling the transmission and control of Zika in Brazil. Scientific Reports 2017;7(1)
    CrossRef
  39. 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
    CrossRef
  40. 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
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.5814)

:
  1. Waring OM, Majumder MS. Leveraging Data Science for Global Health. 2020. Chapter 15:251
    CrossRef
  2. Morley M, Majumder MS, Gallanis T, Wilson J. Leveraging Data Science for Global Health. 2020. Chapter 28:443
    CrossRef
  3. 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
    CrossRef