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A n a i s d o I HM T
Conclusions
Smart public health information systems, like SSIS, are
tools that will take public health into the future. It can
actually address the goal of real-time epidemics surveil-
lance and management as an intervention in elimina-
tion programs require.
Combing smart systems based on artificial intelligence
and geographic information, with a well-designed set
of features for better information analysis and visuali-
zation, it allows the follow-up of epidemics, screening
and highlighting the priority cases and even simulat-
ing future scenarios (e.g. for training epidemiologists),
based on past and actual data. Interactive layouts and
basic gamification functionalities can be applied to en-
gage and motivate users, while facilitating the adoption
of the new innovative solution (because HP participat-
ed actively in developing it). A participatory process is
an important driver to encourage behavior change, im-
proved resilience and awareness of the time-lapse from
information collection to action.
The system is going to be tested using IBMWatson Dis-
covery Advisor functionalities, hopefully providing the
right framework to facilitate quick decision-making and
effectively reducting malaria cases.
Acknowledgements
We would like to acknowledge and thanks the valuable
discussions with Prof. João Pinto and Dr. César Capin-
ha from
GHTM.Wealso thanks the collaboration with
IBM Portugal and IBM Angola.The authors would like
to thanks the support of the Global Health and Tropi-
cal Medicine research center, GHTM – UID/Mul-
ti/04413/2013.This support and the individual grants
from Fundação para a Ciência e Tecnologia to Mélanie
Maia are gratefully acknowledged.
Conflict of interests statement:
No conflits of interest for disclosure.
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