@inproceedings{adam-etal-2017-zikahack,
title = "{Z}ika{H}ack 2016: A digital disease detection competition",
author = "Adam, Dillon C and
Jonnagaddala, Jitendra and
Han-Chen, Daniel and
Batongbacal, Sean and
Almeida, Luan and
Zhu, Jing Z and
Yang, Jenny J and
Mundekkat, Jumail M and
Badman, Steven and
Chughtai, Abrar and
MacIntyre, C Raina",
editor = "Jonnagaddala, Jitendra and
Dai, Hong-Jie and
Chang, Yung-Chun",
booktitle = "Proceedings of the International Workshop on Digital Disease Detection using Social Media 2017 ({DDDSM}-2017)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-5806",
pages = "39--46",
abstract = "Effective response to infectious diseases outbreaks relies on the rapid and early detection of those outbreaks. Invalidated, yet timely and openly available digital information can be used for the early detection of outbreaks. Public health surveillance authorities can exploit these early warnings to plan and co-ordinate rapid surveillance and emergency response programs. In 2016, a digital disease detection competition named ZikaHack was launched. The objective of the competition was for multidisciplinary teams to design, develop and demonstrate innovative digital disease detection solutions to retrospectively detect the 2015-16 Brazilian Zika virus outbreak earlier than traditional surveillance methods. In this paper, an overview of the ZikaHack competition is provided. The challenges and lessons learned in organizing this competition are also discussed for use by other researchers interested in organizing similar competitions.",
}
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%0 Conference Proceedings
%T ZikaHack 2016: A digital disease detection competition
%A Adam, Dillon C.
%A Jonnagaddala, Jitendra
%A Han-Chen, Daniel
%A Batongbacal, Sean
%A Almeida, Luan
%A Zhu, Jing Z.
%A Yang, Jenny J.
%A Mundekkat, Jumail M.
%A Badman, Steven
%A Chughtai, Abrar
%A MacIntyre, C. Raina
%Y Jonnagaddala, Jitendra
%Y Dai, Hong-Jie
%Y Chang, Yung-Chun
%S Proceedings of the International Workshop on Digital Disease Detection using Social Media 2017 (DDDSM-2017)
%D 2017
%8 November
%I Association for Computational Linguistics
%C Taipei, Taiwan
%F adam-etal-2017-zikahack
%X Effective response to infectious diseases outbreaks relies on the rapid and early detection of those outbreaks. Invalidated, yet timely and openly available digital information can be used for the early detection of outbreaks. Public health surveillance authorities can exploit these early warnings to plan and co-ordinate rapid surveillance and emergency response programs. In 2016, a digital disease detection competition named ZikaHack was launched. The objective of the competition was for multidisciplinary teams to design, develop and demonstrate innovative digital disease detection solutions to retrospectively detect the 2015-16 Brazilian Zika virus outbreak earlier than traditional surveillance methods. In this paper, an overview of the ZikaHack competition is provided. The challenges and lessons learned in organizing this competition are also discussed for use by other researchers interested in organizing similar competitions.
%U https://aclanthology.org/W17-5806
%P 39-46
Markdown (Informal)
[ZikaHack 2016: A digital disease detection competition](https://aclanthology.org/W17-5806) (Adam et al., 2017)
ACL
- Dillon C Adam, Jitendra Jonnagaddala, Daniel Han-Chen, Sean Batongbacal, Luan Almeida, Jing Z Zhu, Jenny J Yang, Jumail M Mundekkat, Steven Badman, Abrar Chughtai, and C Raina MacIntyre. 2017. ZikaHack 2016: A digital disease detection competition. In Proceedings of the International Workshop on Digital Disease Detection using Social Media 2017 (DDDSM-2017), pages 39–46, Taipei, Taiwan. Association for Computational Linguistics.