Literature DB >> 30538355

Spatio-temporal distribution analysis of zoonotic cutaneous leishmaniasis in Qom Province, Iran.

Mojtaba Salimi1, Nahid Jesri2, Mohammad Javanbakht3, Leyli Zanjirani Farahani4, Mohammad Reza Shirzadi5, Abedin Saghafipour6.   

Abstract

Geographic information system (GIS) nowadays is one of the most helpful epidemiological tools for identifying the high risk areas of cutaneous leishmaniasis (CL). This study was conducted to determine the spatio-temporal distribution of CL in Qom province during 2009-2017. In a cross-sectional study, for the survey of spatial dispersion of CL in the study region, the incidence rate of disease was calculated in all of 23 villages during 2009-2017. Then, spatial analysis of the infection was performed using two methods: spatial autocorrelation (Moran's I) in order to determine the special distribution pattern of disease and Kriging method to reveal high risk areas for disease. The incidence of CL in Qom province has been decreasing as of 2009-2015 and increasing in 2015-2017. The highest incidence was stated in 2009 (36.5 per 100,000) and the least was reported in 2015 (13.3 per 100,000). The Moran autocorrelation index revealed that the study area has a cluster pattern. The temporal distribution of disease incidence showed that northeast, southwest and northwest parts of Qom province involved highest incidence of CL in 90% significant level. Leishmaniasis incidence is a function of spatial and geographical trends, thus spatial variations of the infection incidence illustrate that the incidence rate does not increase or decrease from one region to another intensively. The results of this study indicate that marking high risk areas using spatial analysis can be helpful as a main tool in CL control and prevention.

Entities:  

Keywords:  Cutaneous leishmaniasis; GIS; Iran; Qom; Spatio-temporal analysis

Year:  2018        PMID: 30538355      PMCID: PMC6261142          DOI: 10.1007/s12639-018-1036-5

Source DB:  PubMed          Journal:  J Parasit Dis        ISSN: 0971-7196


  10 in total

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  10 in total
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