Abstracts Sought for 2013 URISA GIS in Public Health Conference

URISAAbstract submissions for URISA’s GIS in Public Health Conference will be accepted until January 31, 2013. The conference will take place in Miami, Florida, June 17-20, 2013 and is chaired by long-time committee member, Jason K. Blackburn, PhD, Emerging Pathogens Institute & Department of Geography at the University of Florida. This biennial conference has been previously presented in New Orleans (2007), Providence (2009) and Atlanta (2011) and was established to provide an open and participatory forum for advancing the effective use of spatial information and geographic information system technologies across the domains of public health, healthcare and community health preparedness.

The educational program is developed through a peer review of submissions received through the Call for Presentations. The broad conference theme for the 2013 event is: Geospatial tools for understanding health issues related to the environment, human population, and animal populations and the intersections of the three.

Individuals are asked to categorize their abstract submissions according to the thematic areas noted below:

Disease Ecology & Environment

  • Disease Ecology – such topics as vector ecology, parasitic diseases, pathogen reservoirs and pathogen persistence
  • One Health – Human Health topics (chronic diseases like cancer, obesity & diabetes and HIV), other communicable diseases, non-communicable diseases and public health applications; Built Environment & Neighborhood Effects (including food environment); Animal Health (livestock and wildlife diseases) and Zoonoses (human/livestock/wildlife interface).
  • Environmental monitoring including water quality, pollution, waste management, and air quality

Geospatial/GIS Applications & Techniques

  • Spatio-temporal modeling – topics such as prospective surveillance (syndromic surveillance) and retrospective analysis
  • Data mining
  • Predictive modeling – spatial regression; ecological niche & species distribution modeling; and other modeling techniques/methods
  • Web-based applications – participatory; Mobile GIS; spatial decision support systems

Health Care Services, Delivery & Access

  • Health services – health care delivery; health care access; health care disparities; program monitoring and evaluation; community epidemiology and public health preparedness

The committee encourages the submission of individual papers, sessions, and posters until January 31, 2013. The link to the Call for Presentations is: http://www.urisa.org/2013health_call

[Source: URISA press release]

Comparison of Geostatistical Interpolation and Remote Sensing Techniques for Estimating Long-Term Exposure to Ambient PM2.5 Concentrations across the Continental United States

Environmental Health PerspectivesEnvironmental Health Perspectives, 120:1727–1732 (2012)

Seung-Jae Lee, Marc L. Serre, Aaron van Donkelaar, Randall V. Martin, Richard T. Burnett, and Michael Jerrett

“Background: A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from monitor-based data.

“Objective: We evaluated and compared the predictive capabilities of remote sensing and geostatistical interpolation.

Map of the United States indicating the month of the year when the monthly average PM2.5 concentration was highest; circles indicate individual monitoring sites.

Map of the United States indicating the month of the year when the monthly average PM2.5 concentration was highest; circles indicate individual monitoring sites.

“Methods: We developed a space–time geostatistical kriging model to predict PM2.5 over the continental United States and compared resulting predictions to estimates derived from satellite retrievals.

“Results: The kriging estimate was more accurate for locations that were about 100 km from a monitoring station, whereas the remote sensing estimate was more accurate for locations that were > 100 km from a monitoring station. Based on this finding, we developed a hybrid map that combines the kriging and satellite-based PM2.5 estimates.

“Conclusions: We found that for most of the populated areas of the continental United States, geostatistical interpolation produced more accurate estimates than remote sensing. The differences between the estimates resulting from the two methods, however, were relatively small. In areas with extensive monitoring networks, the interpolation may provide more accurate estimates, but in the many areas of the world without such monitoring, remote sensing can provide useful exposure estimates that perform nearly as well.”