Citation:

Chapman, H., E Hilborn, AND J. Haynes. Operationalizing “One Health”: Integrating Remote Sensing and Citizen-Based Observations. American Public Health Association(APHA), San Diego, California, November 10 - 14, 2018.

Impact/Purpose:

One Health is a transdisciplinary paradigm that integrates human, animal and environmental health. We provide an overview of how a combination of remote sensing and field observations can inform One Health projects. We give examples including harmful algal blooms and vector-borne disease as proof of concept.

Description:

The “One Health” concept promotes transdisciplinary collaborations that lead scientists and community practitioners to identify risk factors, develop innovative approaches, and implement established strategies for intervention, as they relate to human, animal, and environmental health. According to the Centers for Disease Control and Prevention, this holistic approach can foster collaborations, strengthen communication among stakeholders, coordinate disease surveillance, and increase public awareness through educational outreach programs. With increased use of transdisciplinary science, cutting-edge remote sensing technology, and “big data”, the ability to operationalize the “One Health” concept, from theory to practice, has become a more realistic goal. Using a three-step cycle – observation, analysis, and communication – scientists, practitioners, and communities themselves can take coordinated action in response to environmental health risks and infectious disease outbreaks. To initiate effective action, at least two broad sets of data sources are essential. First, remote sensing data from remote sensors such as drones, aircraft or Earth observing satellites can allow end users to detect changes in air and water quality, assess environmental hazards, and identify habitats of key disease vectors such as mosquitoes, ticks, birds, and bats. Second, field observation data from citizen scientists can shed light on where affected communities identify environmental risks (e.g., mosquito-breeding sites, harmful algal blooms). Coordinated data collection, effective analysis of data sets, and timely communication regarding health and environmental risks can save lives. In this paper, we will describe the framework of the three-step cycle for real world applications. We will highlight at least two examples that demonstrate the benefit of integrating remote sensing data and local observations for disease surveillance and for public health and environmental protection. This is an abstract of a proposed presentation and does not necessarily reflect EPA policy.

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