Beltran, JD;
Boscor, A;
dos Santos, WP;
Massoni, T;
Kostkova, P;
(2018)
ZIKA: A New System to Empower Health Workers and Local Communities to Improve Surveillance Protocols by E-learning and to Forecast Zika Virus in Real Time in Brazil.
In:
Proceedings of the DH'18: International Digital Health Conference.
(pp. pp. 90-94).
ACM (Association for Computing Machinery)
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Abstract
The devastating consequences of neonates infected with the Zika virus makes it necessary to fight and stop the spread of this virus and its vectors (Aedes mosquitoes). An essential part of the fight against mosquitoes is the use of mobile technology to support routine surveillance and risk assessment by community health workers (health agents). In addition, to improve early warning systems, the public health authorities need to forecast more accurately where an outbreak of the virus and its vector is likely to occur. The ZIKΛ system aims to develop a novel comprehensive framework that combines e-learning to empower health agents, community-based participatory surveillance, and forecasting of occurrences and distribution of the Zika virus and its vectors in real time. This system is currently being implemented in Brazil, in the cities of Campina Grande, Recife, Jaboatão dos Guararapes, and Olinda, the State of Pernambuco and Paraiba with the highest prevalence of the Zika virus disease. In this paper, we present the ZIKA system which helps health agents to learn new techniques and good practices to improve the surveillance of the virus and offer a real time distribution forecast of the virus and the vector. The forecast model is recalibrated in real time with information coming from health agents, governmental institutions, and weather stations to predict the areas with higher risk of a Zika virus outbreak in an interactive map. This mapping and alert system will help governmental institutions to make fast decisions and use their resources more efficiently to stop the spread of the Zika virus. The ZIKA app was developed and built in Ionic which allows for easy cross-platform rendering for both iOS and Android. The system presented in the current paper is one of the first systems combining public health surveillance, citizen-driven participatory reporting and weather data-based prediction. The implementation of the ZIKA system will reduce the devastating consequences of Zika virus in neonates and improve the life quality of vulnerable people in Brazil.
| Type: | Proceedings paper |
|---|---|
| Title: | ZIKA: A New System to Empower Health Workers and Local Communities to Improve Surveillance Protocols by E-learning and to Forecast Zika Virus in Real Time in Brazil |
| Event: | DH'18: International Digital Health Conference |
| Location: | Lyon, France |
| Dates: | 23rd-26th April 2018 |
| ISBN-13: | 978-1-4503-6493-5 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3194658.3194683 |
| Publisher version: | https://doi.org/10.1145/3194658.3194683 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Zika virus; big data; surveillance; forecasting; e-learning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10088842 |
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