Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level
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DOI: 10.1371/journal.pntd.0005729
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Cited by:
- Fantazzini, Dean, 2020.
"Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
- Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Tiago Peixoto & Tom Steinberg, 2019. "Citizen Engagement," World Bank Publications - Reports 32495, The World Bank Group.
- Prashant Rangarajan & Sandeep K Mody & Madhav Marathe, 2019. "Forecasting dengue and influenza incidences using a sparse representation of Google trends, electronic health records, and time series data," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-24, November.
- Gal Koplewitz & Fred Lu & Leonardo Clemente & Caroline Buckee & Mauricio Santillana, 2022. "Predicting dengue incidence leveraging internet-based data sources. A case study in 20 cities in Brazil," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 16(1), pages 1-21, January.
- Alexandre Gori Maia & Jose Daniel Morales Martinez & Leticia Junqueira Marteleto & Cristina Guimaraes Rodrigues & Luiz Gustavo Sereno, 2023. "Can the Content of Social Networks Explain Epidemic Outbreaks?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(1), pages 1-34, February.
- Aditya Lia Ramadona & Yesim Tozan & Lutfan Lazuardi & Joacim Rocklöv, 2019. "A combination of incidence data and mobility proxies from social media predicts the intra-urban spread of dengue in Yogyakarta, Indonesia," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 13(4), pages 1-12, April.
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