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Al Manir MS, Brenas JH, Baker CJ, et al. A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR Public Health Surveill. 2018;4(2):e10218doi: 10.2196/10218.
Al Manir, M. S., Brenas, J. H., Baker, C. J., & Shaban-Nejad, A. (2018). A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR public health and surveillance, 4(2), e10218. https://doi.org/10.2196/10218
Al Manir, Mohammad Sadnan, et al. "A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability." JMIR public health and surveillance vol. 4,2 (2018): e10218. doi: https://doi.org/10.2196/10218
Al Manir MS, Brenas JH, Baker CJ, Shaban-Nejad A. A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability. JMIR Public Health Surveill. 2018 Jun 15;4(2):e10218. doi: 10.2196/10218. PMID: 29907554; PMCID: PMC6026300.
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JMIR Public Health Surveill. 2018 Jun 15;4(2):e10218. doi: 10.2196/10218.

A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability.

JMIR public health and surveillance

Mohammad Sadnan Al Manir, Jon Haël Brenas, Christopher Jo Baker, Arash Shaban-Nejad

Affiliations

  1. Department of Computer Science, University of New Brunswick, Saint John, NB, Canada.
  2. Oak Ridge National Laboratory Center for for Biomedical Informatics, Department of Pediatrics, The University of Tennessee Health Science Center, Memphis, TN, United States.
  3. IPSNP Computing Inc, Saint John, NB, Canada.

PMID: 29907554 PMCID: PMC6026300 DOI: 10.2196/10218

Abstract

BACKGROUND: According to the World Health Organization, malaria surveillance is weakest in countries and regions with the highest malaria burden. A core obstacle is that the data required to perform malaria surveillance are fragmented in multiple data silos distributed across geographic regions. Furthermore, consistent integrated malaria data sources are few, and a low degree of interoperability exists between them. As a result, it is difficult to identify disease trends and to plan for effective interventions.

OBJECTIVE: We propose the Semantics, Interoperability, and Evolution for Malaria Analytics (SIEMA) platform for use in malaria surveillance based on semantic data federation. Using this approach, it is possible to access distributed data, extend and preserve interoperability between multiple dynamic distributed malaria sources, and facilitate detection of system changes that can interrupt mission-critical global surveillance activities.

METHODS: We used Semantic Automated Discovery and Integration (SADI) Semantic Web Services to enable data access and improve interoperability, and the graphical user interface-enabled semantic query engine HYDRA to implement the target queries typical of malaria programs. We implemented a custom algorithm to detect changes to community-developed terminologies, data sources, and services that are core to SIEMA. This algorithm reports to a dashboard. Valet SADI is used to mitigate the impact of changes by rebuilding affected services.

RESULTS: We developed a prototype surveillance and change management platform from a combination of third-party tools, community-developed terminologies, and custom algorithms. We illustrated a methodology and core infrastructure to facilitate interoperable access to distributed data sources using SADI Semantic Web services. This degree of access makes it possible to implement complex queries needed by our user community with minimal technical skill. We implemented a dashboard that reports on terminology changes that can render the services inactive, jeopardizing system interoperability. Using this information, end users can control and reactively rebuild services to preserve interoperability and minimize service downtime.

CONCLUSIONS: We introduce a framework suitable for use in malaria surveillance that supports the creation of flexible surveillance queries across distributed data resources. The platform provides interoperable access to target data sources, is domain agnostic, and with updates to core terminological resources is readily transferable to other surveillance activities. A dashboard enables users to review changes to the infrastructure and invoke system updates. The platform significantly extends the range of functionalities offered by malaria information systems, beyond the state-of-the-art.

©Mohammad Sadnan Al Manir, Jon Haël Brenas, Christopher JO Baker, Arash Shaban-Nejad. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 15.06.2018.

Keywords: Web services; change management; global health; interoperability; malaria surveillance; population health intelligence

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