Spatial Distribution of Cutaneous Leishmaniasis Cases Referred to Health Centers of Three Khorasan Provinces in Iran Using Geographical Information System

Background: Nowadays, geographic information system (GIS) is one of the most useful epidemiological tools for identifying high-risk areas of cutaneous leishmaniasis. The aim of this study was to determine the spatial distribution of cutaneous leishmaniasis in northeastern Iran. Methods: In this cr...

Full description

Bibliographic Details
Main Authors: Mohammad Reza SHIRZADI, Mohammad JAVANBAKHT, Nahid JESRI, Abedin SAGHAFIPOUR
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2019-10-01
Series:Iranian Journal of Public Health
Subjects:
Online Access:https://ijph.tums.ac.ir/index.php/ijph/article/view/18551
Description
Summary:Background: Nowadays, geographic information system (GIS) is one of the most useful epidemiological tools for identifying high-risk areas of cutaneous leishmaniasis. The aim of this study was to determine the spatial distribution of cutaneous leishmaniasis in northeastern Iran. Methods: In this cross-sectional study, information on positive cases of cutaneous leishmaniasis in the three provinces located in northeastern Iran during Jul 2011 to Jul 2017 was obtained from the Iranian Ministry of Health. Based on the postal address of each case, the geographical coordinates of each patient were determined for spatial analysis of cutaneous leishmaniasis. For spatial analysis, Moran’s index autocorrelation and Kriging interpolation method were used in GIS software. Results: Moran’s index autocorrelation showed that spatial distribution of disease incidence in the study area was cluster pattern (Z-score > 1). In addition, Kriging interpolation method revealed that 90% of southern parts of North Khorasan province and northern parts of Razavi Khorasan Province formed hot spots. Conclusion: The CL incidence is a function of spatial and geographical trends. In addition, spatial trends in the disease incidence distribution indicate that it is not greatly increased or decreased from one area to another. It appears as hot spots areas. Spatial analysis by showing high risk areas can be useful tools for controlling and preventing CL incidence.
ISSN:2251-6085
2251-6093