Volume 77, Issue 6
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645


The ecology and distribution of is poorly understood despite continued anthrax outbreaks in wildlife and livestock throughout the United States. Little work is available to define the potential environments that may lead to prolonged spore survival and subsequent outbreaks. This study used the genetic algorithm for rule-set prediction modeling system to model the ecological niche for in the contiguous United States using wildlife and livestock outbreaks and several environmental variables. The modeled niche is defined by a narrow range of normalized difference vegetation index, precipitation, and elevation, with the geographic distribution heavily concentrated in a narrow corridor from southwest Texas northward into the Dakotas and Minnesota. Because disease control programs rely on vaccination and carcass disposal, and vaccination in wildlife remains untenable, understanding the distribution of plays an important role in efforts to prevent/eradicate the disease. Likewise, these results potentially aid in differentiating endemic/natural outbreaks from industrial-contamination related outbreaks or bioterrorist attacks.


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  1. Smith KL, De Vos V, Price LB, Hugh-Jones ME, Keim P, 2000. Bacillus anthracis diversity in Kruger National Park. J Clin Microbiol 38 : 3780–3784.
  2. Gainer RS, Saunders R, 1989. Aspects of the epidemiology of anthrax in Wood Buffalo National Park and environs. Can Vet J 30 : 953–956.
  3. Kaufmann AF, 1990. Observations on the occurrence of anthrax as related to soil type and rainfall. Salisbury Med Bull Suppl 68 : 16–17.
  4. Smith KL, De Vos V, Bryden HB, Hugh-Jones ME, Klevytska A, Price LB, Keim P, Scholl DT, 1999. Meso-scale ecology of anthrax in southern Africa: a pilot study of diversity and clustering. J Appl Microbiol 87 : 204–207.
  5. Van Ness G, Stein CD, 1956. Soils of the United States favorable for anthrax. J Am Vet Med Assoc 128 : 7–9.
  6. Van Ness GB, 1959. Anthrax—a soil borne disease. Soil Conserv 21 : 206–208.
  7. Van Ness GB, 1959. Soil relationship in the Oklahoma-Kansas anthrax outbreak of 1957. J Soil Water Conserv 1 : 70–71.
  8. Van Ness GB, 1971. Ecology of anthrax. Science 172 : 1303–1307.
  9. Dragon DC, Rennie RP, 1995. The ecology of anthrax spores: tough but not invincible. Can Vet J 36 : 295–301.
  10. Stein CD, 1945. The history and distribution of anthrax in livestock in the United States. Vet Med (Praha) 40 : 340–349.
  11. Stein CD, van Ness GB, 1955. A ten year survey of anthrax in livestock with special reference to outbreaks in 1954. Vet Med (Praha) 50 : 579–590.
  12. Hugh-Jones ME, de Vos V, 2002. Anthrax and wildlife. Rev Sci Tech 21 : 359–383.
  13. Grinnell J, 1917. The niche-relationships of the California thrasher. Auk 34 : 427–433.
  14. Hutchinson GE, 1957. Concluding remarks. Cold Spring Harb Symp Quant Biol 22 : 415–427.
  15. Peterson AT, Bauer JT, Mills JN, 2004. Ecologic and geographic distribution of filovirus disease. Emerg Infect Dis 10 : 40–47.
  16. Stockwell D, Peters D, 1999. The GARP modelling system: problems and solutions to automated spatial prediction. Int J Geogr Inf Sci 13 : 143–158.
  17. Stockwell DRB, Peterson AT, 2002. Effects of sample size on accuracy of species distribution models. Ecol Modell 148 : 1–13.
  18. Anderson RP, Lew D, Peterson AT, 2003. Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecol Modell 162 : 211–232.
  19. Kluza DA, McNyset KM, 2005. Ecological niche modeling of aquatic invasion species. Aquat Invaders 16 : 1–7.
  20. Ron RS, 2005. Predicting the distribution of the amphibian pathogen Batrachochytrium dendrobatidis in the New World. Biotropica 37 : 209–221.
  21. Peterson AT, 2001. Predicting species’ geographic distributions based on ecological niche modeling. Condor 103 : 599–605.
  22. Peterson AT, Vieglais DA, 2001. Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem. Bioscience 51 : 363–371.
  23. Anderson RP, Gomez-Laverde M, Peterson AT, 2002. Geographical distributions of spiny pocket mice in South America: insights from predictive models. Glob Ecol 11 : 131–141.
  24. Raxworthy CJ, Martinez-Meyer E, Horning N, Nussbaum RA, Schneider GE, Ortega-Huerta MA, Townsend Peterson A, 2003. Predicting distributions of known and unknown reptile species in Madagascar. Nature 426 : 837–841.
  25. Wiley EO, McNyset KM, Peterson AT, Robins CR, Stewart AM, 2003. Niche modeling and geographic range predictions in the marine environment using a machine-learning algorithm. Oceanography 16 : 120–127.
  26. McNyset KM, 2005. Use of ecological niche modelling to predict distributions of freshwater fish species in Kansas. Ecol Freshwater Fish 14 : 243–255.
  27. Peterson AT, Sanchez-Cordero V, Beard CB, Ramsey JM, 2002. Ecologic niche modeling and potential reservoirs for Chagas disease, Mexico. Emerg Infect Dis 8 : 662–667.
  28. Costa J, Peterson AT, Beard CB, 2002. Ecologic niche modeling and differentiation of populations of Triatoma brasiliensis neiva, 1911, the most important Chagas’ disease vector in northeastern Brazil (hemiptera, reduviidae, triatominae). Am J Trop Med Hyg 67 : 516–520.
  29. Beard CB, Pye G, Steurer FJ, Rodriquez R, Campman R, Townsend Peterson A, Ramsey J, Wirtz RA, Robinson LE, 2003. Chagas disease in a domestic transmission cycle in southern Texas, USA. Emerg Infect Dis 9 : 103–105.
  30. Adjemian JCZ, Girvetz EH, Beckett L, Foley JE, 2006. Analysis of genetic algorithm for rule-set prodution (GARP) modeling approach for predicting distributions of fleas implicated as vectors of plague, Yersinia pestis, in California. J Med Entomol 43 : 93–103.
  31. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25 : 1965–1978.
  32. Hay SI, Tatem AJ, Graham AJ, Goetz SJ, Rogers DJ, 2006. Global environmental data for mapping infectious disease distribution. Hay S, Graham AJ, Rogers DJ, eds. Global Mapping of Infectious Diseases: Methods, Examples, and Emerging Application. London: Academic Press, 38–79.
  33. Peterson AT, Papes M, Kluza DA, 2003. Predicting the potential invasive distributions of four alien plant species in North America. Weed Sci 51 : 863–868.
  34. Peterson AT, Cohoon KP, 1999. Sensitivity of distributional prediction algorithms to geographic data completeness. Ecol Modell 117 : 159–164.
  35. Centor RM, 1991. Signal detectability: the use of ROC curves and their analyses. Med Decis Making 11 : 102–106.
  36. Zweig MH, Campbell G, 1993. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39 : 561–577.
  37. Hanley JA, McNeil BJ, 1982. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143 : 29–36.
  38. Van Ert MN, Easterday WR, Huynh LY, Okinaka RT, Hugh-Jones ME, Ravel J, Zanecki SR, Pearson T, Simonson T, Uren JM, Kachur SM, Leadem-Dougherty RR, Rhoton SD, Zinser G, Farlow J, Coker PR, Smith KL, Wang B, Kenefic LJ, Fraser-Liggett CM, Wagner DM, Keim P, 2007. Global genetic population structure of Bacillus anthracis. PLoS ONE 2 : e461.
  39. ProMED-mail, Anthrax—Bovine, USA (Montana). ProMED-mail 2005; September 16, 2005: 20050916.2737. Accessed August 23, 2007. Available from http://www.promedmail.org.
  40. ProMED-mail, Anthrax—Cattle—USA (Montana). PromMED-mail 1999; May 28, 1999: 19990528.0895. Accessed August 23, 2007. Available from http://www.promedmail.org.
  41. ProMED-mail, Anthrax—Cervidae, Livestock—USA (Texas). ProMED-mail 1999, July 9, 1999. 20050709.1944. Accessed August 23, 2007. Available from http://www.promedmail.org.
  42. Peterson AT, Sánchez-Cordero V, Martínez-Meyer E, Navarro-Sigüenza AG, 2006. Tracking population extirpations via melding ecological niche modeling with land-cover information. Ecol Modell 195 : 229–236.

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  • Received : 05 Jul 2007
  • Accepted : 24 Aug 2007

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