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.

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