Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 969–973, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-969-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 969–973, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-969-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Oct 2019

19 Oct 2019

SPATIO-STATISTICAL MODELING OF HUMAN BRUCELLOSIS USING ENVIRONMENTAL PARAMETERS: A CASE STUDY OF NORTHERN IRAN

N. Seyedalizadeh1, A. A. Alesheikh1, and M. Ahmadkhani2 N. Seyedalizadeh et al.
  • 1Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
  • 2Dept. of Geography, Environmental and Society, University of Minnesota, USA

Keywords: Spatial-statistical modeling, Health GIS, Maximum Entropy, Jackknife, Brucellosis, Environment

Abstract. Brucellosis is one of the most important zoonotic diseases which is endemic in Iran. This disease is considered a significant hazard to citizens’ health and imposes heavy economic burdens, hence, requires a thorough control and management plan. The aims of this study are identifying the areas having the highest risk of brucellosis, as well as discovering the contributing environmental factors. The maximum entropy (MaxEnt) method was used to model the probability of brucellosis in Golestan, Mazandaran, and Guilan provinces. The possible contribution of 12 environmental parameters in this disease was also measured using the Jackknife method. The results showed that the highest risk of brucellosis is located in southern Golestan, East, and West of Mazandaran, and south of Guilan province, and moisture, slope, vegetation and elevation are the most effective environmental factors on the spatial distribution of the disease. In addition, the probability of the disease in northern Iran increases from west to east. These findings could assist the public health managers and decision-makers in organizing a more efficient public health system.