Forecasting Anthrax in Livestock in Karnataka State using Remote Sensing and Climatic Variables
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Statistics | India | Volume 6 Issue 5, May 2017

Forecasting Anthrax in Livestock in Karnataka State using Remote Sensing and Climatic Variables

Suma A P, Suresh K P, Gajendragad M R, Kavya B A

Anthrax is a well-known zoonotic disease caused by Bacillus anthracis, a gram positive, spore forming bacteria. In livestock it is usually peracute and fatal whereas in humans it is a highly fatal disease, if not treated immediately. Anthrax is prevalent world-wide and is one of the top ten livestock diseases in India and hence forecasting the outbreak of this disease by modeling is very helpful in saving the livestock and thereby averting economic loss to the livestock farmer in particular and country in general. In this paper, past anthrax outbreak data was analyzed and a forecasting model is developed. To develop the model, in the risk factor domain, amount of rainfall, atmospheric temperature, and soil nutrients were collected retrospectively. Further, remote sensed variables like Normalized Difference Vegetative Index (NDVI) and Land surface temperature (LST) were collected using Moderate Resolution Imaging spectro-radiometer tools (MODIS Tools). Zero Truncated Poisson regression with log link model was used for developing the climate-anthrax relationship model with outbreak of anthrax as dependent variable and LST, NDVI, amount of rainfall and soil nutrients were considered as predictors in the model. Then a risk map forecasting the outbreak of anthrax was generated.

Keywords: Anthrax, Remote-sensing, Zero-truncated Poisson, Risk-map

Edition: Volume 6 Issue 5, May 2017

Pages: 1891 - 1897

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Suma A P, Suresh K P, Gajendragad M R, Kavya B A, "Forecasting Anthrax in Livestock in Karnataka State using Remote Sensing and Climatic Variables", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20173531, Volume 6 Issue 5, May 2017, 1891 - 1897

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