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Spatially Integrating Microbiology and Geochemistry to Reveal Complex Environmental Health Issues: Anthrax in the Contiguous United States

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Abstract

Maxent models were run using the B. anthracis presence data and/or the animal outbreak presence data. Models run using the animal outbreak data alone utilized two scales: the Outbreak State scale which included only states reporting animal anthrax outbreaks from 2001 to 2013 and the National scale which included all states in the contiguous United States. Three iterations of the environmental data were used and included the Sample Location dataset which utilized the environmental variable data with assigned latitude and longitude locations from the USGS NASGLP project; the Normalized dataset which scaled the environmental variables so that the values fell between 0 and 1; and the Interpolated dataset which provided an interpolation of the environmental variables averaged for each county and assigned to a point for that county at the centroid (rather than using the NASGLP latitude and longitude location). Two metrics were used to measure model performance including the widely used area under the curve (AUC) and an alternative method, the True Skill Statistic (TSS). The AUC gives the probability that a randomly chosen presence location has been correctly ranked higher than the absence/background site. AUC values at 0.5 or lower mean the ranking is no better than random, while the AUC values nearer to 1 mean the model is a better predictor. The TSS provides a comparison of how well the background predictions made by the model match the model results at the test dataset (presence) locations. TSS values near +1 means the model approaches perfect agreement, while values near −1 indicate the model is no better than random.

Maxent models to determine the influence of environmental factors on the B. anthracis distribution using the PCR data yielded a low TSS, which suggested the model might be underfitting the data. This was not surprising due to the difficulty in recovering B. anthracis in soil samples as well as the samples themselves being discrete in nature and only capturing a snapshot in time. Therefore, the distribution of B. anthracis and its niche in the contiguous United States could not be determined in this study. However, efforts to investigate environmental factors that would have a higher potential of supporting an anthrax outbreak in wildlife and livestock yielded better results. Results showed that most of the Maxent models in this study performed best when using the Outbreak State scale. When the models were scaled up to the National scale, model performance declined, except for the Normalized variable dataset. At the Outbreak State scale, a large proportion of the area was predicted to be of higher probability for wildlife/livestock anthrax outbreaks, and the statistical measures assumed the model was underfitting the data. The model with the highest AUC and TSS scores for this study was the Outbreak State scale using Sample Location dataset (AUC = 0.918 and TSS = 0.82). Some of the variables found to be closely related to the occurrence of B. anthracis in this study included pH, drainage potential, and concentration of elements including Na, Ca, Sr, and Mg, which have also been found to be related to animal outbreaks or to the occurrence of B. anthracis in previous studies.

The models in the current study indicated possible regions that have not had recent wildlife/livestock anthrax outbreaks but contained environmental conditions that could potentially support an outbreak if one were to occur (Michigan and Maine). This work provides an extension to the use of ecological niche modeling to outbreak potential in livestock/wildlife in the United States because it utilizes additional soil geochemistry data and has shown that further validation techniques, such as the TSS, should be considered in addition to AUC. Results from this study could be used by animal and public health officials to identify areas with a higher potential for anthrax outbreak in wildlife and livestock due to naturally occurring soil and environmental conditions.

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Acknowledgements and Disclaimer

USGS collaborated on the analysis of samples for the presence of Bacillus and B. anthracis with the US Environmental Protection Agency (USEPA) through USEPA’s Office of Research and Development under EPA IA# DW 1495774801. Maxent and statistical analysis was completed by completed under the USEPA and USGS IA # DW 1492401101. This joint agency project was supported by the USGS Geochemical Landscape Project and the USGS Environmental Health Mission Area’s Contaminate Biology Program. We would like to thank John Lisle (USGS), Sarah Perkins (formerly from USEPA), Charlena Bowling (USEPA), M. Worth Calfee (USEPA), and Paul Lemieux (USEPA) for their help and assistance on this project. This content has been peer and administratively reviewed and has been approved for publication as a joint USGS and USEPA publication. Note that approval does not signify that the contents necessarily reflect the views of the USEPA or the USGS. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the US government. The views and opinions expressed herein do not state or reflect those of the US government and shall not be used for advertising or product endorsement purposes.

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Authors and Affiliations

  1. U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Solutions and Emergency Response, Homeland Security and Materials Management Division, Disaster Characterization Branch, Cincinnati, OH, USA

    Erin E. Silvestri

  2. Geospatial Analyst, Versar, Inc., Newport News, Virginia, USA

    Steven H. Douglas

  3. University of South Florida, Center for Biological Defense, Tampa, FL, USA

    Vicky A. Luna

  4. Cindy (or Cynthia) Ogolla Jean-Baptiste, DrPH, MA, MPH, CPH Former research assistant for Dale Griffin, USGS, Current Public Health Analyst, United States Air Force, Suffolk County, Massachusetts, IL, USA

    C. A. O. Jean-Babtiste

  5. MBA Hydrological technician and assistant to Dale Griffin, Director of Community Engagement and Communications, Epstein Hillel School, Marblehead, Massachusetts, DeBary, FL, USA

    Deryn Pressman-Mashin née Harbin

  6. Former research assistant for Dale Griffin, USGS. Current Hydrologist U.S. Geological Survey, Colorado Water Science Center, Pueblo, CO, USA

    Laura A. Hempel

  7. Geographer, US EPA, Office of Research and Development, Center for Solutions and Emergency Response, Homeland Security and Materials Management Division, Research Triangle Park, NC, USA

    Timothy R. Boe

  8. U.S. Environmental Protection Agency, Threat and Consequence Assessment Division, National Homeland Security Research Center, Washington, DC, USA

    Tonya L. Nichols

  9. U. S. Geological Survey, Coastal and Marine Science Center, St. Petersburg, FL, USA

    Dale W. Griffin

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  1. Erin E. Silvestri
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Correspondence to Dale W. Griffin .

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  1. Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS, USA

    Fazlay S. Faruque

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Silvestri, E.E. et al. (2022). Spatially Integrating Microbiology and Geochemistry to Reveal Complex Environmental Health Issues: Anthrax in the Contiguous United States. In: Faruque, F.S. (eds) Geospatial Technology for Human Well-Being and Health. Springer, Cham. https://doi.org/10.1007/978-3-030-71377-5_19

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