Architecture of a Learning Surveillance System for Malaria Elimination in India

S D Sreeganga, Susanna G. Mitra, Arkalgud Ramaprasad, Arkalgud Ramaprasad

2020

Abstract

Surveillance is critical for malaria elimination. Malaria transmission takes place in a dynamic and complex environment. The key goal in developing a malaria surveillance system is to ensure that it is robust, systematic, and effective for improving data availability for decision-making. We present a unified framework for envisioning malaria surveillance informatics as an ontology-based feedback system. The framework presented is a solution for the current fragmented and linear surveillance processes for malaria case management. It encapsulates a comprehensive natural language enumeration of the requirements of the cyberenvironment, structured into 5 dimensions - timing, surveillance process, information surveyed, malaria management, and stakeholder, with each of them articulated as a taxonomy of its constituent elements. The elements are combined to form natural language statements of the cyberenvironment requirement. The information generation through the semiotic cycle provides real-time sense and response capability for timely and targeted interventions. The response mechanism creates both positively and negatively reinforcing feedback-based learning processes at multiple levels. Such a system enables data interoperability for capturing malaria incidence, discover epidemiological clusters, and predict propagation dynamics. On a larger scale, the integrative framework enables data harmonization, analytics, and visualization towards effective management and knowledge generation on disease surveillance.

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Paper Citation


in Harvard Style

Sreeganga S., Mitra S. and Ramaprasad A. (2020). Architecture of a Learning Surveillance System for Malaria Elimination in India. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF; ISBN 978-989-758-398-8, SciTePress, pages 377-382. DOI: 10.5220/0008944103770382


in Bibtex Style

@conference{healthinf20,
author={S D Sreeganga and Susanna G. Mitra and Arkalgud Ramaprasad},
title={Architecture of a Learning Surveillance System for Malaria Elimination in India},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF},
year={2020},
pages={377-382},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008944103770382},
isbn={978-989-758-398-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF
TI - Architecture of a Learning Surveillance System for Malaria Elimination in India
SN - 978-989-758-398-8
AU - Sreeganga S.
AU - Mitra S.
AU - Ramaprasad A.
PY - 2020
SP - 377
EP - 382
DO - 10.5220/0008944103770382
PB - SciTePress