48 Holistics for Health

Wednesday, 28 August 2013
3:30 PM - 5:30 PM
Washington III

INTEGRATING BIG DATA INTO REGIONAL ATMOSPHERIC MODELS FOR PUBLIC HEALTH APPLICATIONS

Paper number: 48-5
Program: Sessions
Time: 4:50 PM – 5:10 PM

Authors

Abstract

Central to the concept of Holistics for Health is the need to recognize that human health is affected by a myriad of environmental phenomena that are part of an interdependent multifaceted system, requiring large amounts of data from various sources and intellectual domains. These large datasets are integrated with computational techniques to provide new scientific discoveries, support decision making, and to support or form new policies. These data are collected by instruments ranging from satellite sensors to airborne systems to ground-based sampling stations. “New data also can be derived from these sources by applying algorithms or models that generate new products for enhancing our understanding of human health.

Environmentally induced health risks to populations with respiratory illnesses are a growing concern globally. Of particular concern are dust and smoke events carrying PM2.5 (respirable) and PM10 (inhalable) particle sizes, aerosols, and pollen. We discuss EDAC's PHAiRS and ENPHSYS projects, wherein a real-time atmospheric model ingests meteorological, USGS, NASA, EPA, and other global datasets to provide 48-hour daily dust forecasts and to study aerosol trends. We also summarize ongoing work with a parallel project that uses NASA products and phenology data to forecast pollen events throughout the southwestern region of the U.S.

The “Big Data” revolution requires delivering data and information in a timely and efficient manner for providing decision makers crucial information that could impact the well-being of humans. Advances in web mapping and related technologies open new doors for data providers and users that, under ideal circumstances, can deliver data and information in near-real time. In the public health community these technologies are being used to enhance disease and syndromic surveillance systems, visualize environmentally-related events such as dust storms, and to provide mapping and analysis capabilities. These systems will be described briefly.