142nd APHA Annual Meeting and Exposition

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301773
More than a means to an end: Spatial data architecture for a complex field-based malaria intervention trial

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Tuesday, November 18, 2014

Joshua Tootoo, MS, GISP , Children's Environmental Health Initiative, University of Michigan, Ann Arbor, MI
Randall Kramer, PhD , Nicholas School of the Environment and Duke Global Health Institute, Duke University, Durham, NC
Adriane Lesser, MS , Duke Global Health Institute, Duke University, Durham, NC
Leonard Mboera, BVM, MSc., PhD, DIC , National Institute for Medical Research Tanzania, Dar-es-Salaam, Tanzania
Susan Rumisha, BSc MSc PhD , Directorate of Information Technology and Communication, National Institute for Medical Research Tanzania, Dar-es-Salaam, Tanzania
Marie Lynn Miranda, PhD , School of Natural Resources & Environment, University of Michigan, Ann Arbor, MI
Ruiyang Li, MS , Children's Environmental Health Initiative, University of Michigan, Ann Arbor, MI
Background: Working collaboratively with Tanzania’s National Institute for Medical Research (NIMR), we have designed, implemented, and evaluated a spatially-enabled database. This database was developed for the collection, quality assurance and quality control (QA/QC), and analysis of datasets generated from a multiyear cluster-randomized health experiment seeking to determine the human impacts of malaria vector control and disease management interventions.

Objectives: We sought to establish a spatially resolved data infrastructure to flexibly support a complex field-based health intervention. The data infrastructure was designed to: 1) accommodate the research design; 2) respond to the unique research needs and organizational constraints of collaborating partners; 3) safeguard the protected health information of study participants; and 4) provide the flexibility required for a multiyear research project.

Methods: We designed the database for the paper-based field collection and digital capture of a number of spatially referenced datasets including patterns of malaria and anemia, environmental conditions, and social characteristics for study participants in the Mvomero District of Tanzania. We established a data infrastructure within NIMR to support the development and maintenance of the spatial database. The key components of the spatial database, the factors precipitating their development, and their effectiveness over the course of the research project are discussed.

Discussion: Spatial data architectures encourage both data standards and a set of readily available tools in support of data interoperability - an essential element for successful interagency research collaborations. Spatial data architecture is built on an integrated foundation of hardware, software, data, and policies. Recognizing the challenges of this integrated approach, we offer key lessons learned from our multi-stakeholder research collaboration. We have identified several appropriate data infrastructure policies and practices that enhance the ability of host country research organizations and their international collaborators to implement spatial data architectures.

Learning Areas:

Communication and informatics
Diversity and culture
Other professions or practice related to public health
Public health or related research

Learning Objectives:
Identify information technology infrastructure challenges faced by a multi-partner research collaboration involving institutions in the U.S. and Tanzania Describe an appropriate information technology infrastructure approach for enabling an effective spatial data architecture for use by partner research organizations Understand and evaluate key components of a flexible data system for the collection, validation, and analysis of field-collected data

Keyword(s): Data Collection and Surveillance, Information Technology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I lead a series of projects seeking to understand the complex factors that contribute to health outcomes, and direct our research group’s technical capacity building efforts. My research interests include: the application of administrative datasets into analyses examining environmentally driven health disparities; informal project based approaches to education and training for public health/environmental professionals; and the communication of complex data analyses and explanatory narratives through visualization.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.