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J Vector Borne Dis. 2017 Jul-Sep;54(3):233-239.

Investigation of the spatial distribution of sandfly species and cutaneous leishmaniasis risk factors by using geographical information system technologies in Karaisali district of Adana province, Turkey.

Author information

1
Karaisali Vocational School, Cukurova University, Karaisali, Turkey.

Abstract

BACKGROUND & OBJECTIVES:

Cutaneous leishmaniasis displays two epidemiological routes of transmission, zoonotic cutaneous leishmaniasis (ZCL) which includes animal reservoir hosts in the transmission cycle and anthroponotic cutaneous leishmaniasis (ACL), where human is the sole source of infection for the vector sandflies. About 10-13% of CL cases are reported each year from Adana province in Turkey. The aim of this study was to develop a predictive model for determining the spatial risk level of cutaneous leishmaniasis in the Adana province, southern part of Turkey, in relation to environmental factors.

METHODS:

Entomological survey was carried out between June 2015 and September 2016. Sandflies were collected from Karaisali district of the Adana province using light-traps and sticky papers. Sandfly fauna results were compared with environmental data obtained from field-survey, and examined with univariate and binary logistic regression in PASW statistical software. The ArcMap application of ArcGIS10.0. software was used for geographical adjustments to create maps and establish a risk model.

RESULTS:

In total five sandfly species were identified in the study area, and three of them (Phlebotomus tobbi, P. neglectus/syriacus and P. perfiliewi) were detected as potential vectors of cutaneous leishmaniasis. The results showed that enhanced vegetation index (EVI) and emissivity band 31 (EMIS31) values are related to the distribution of these three species.

INTERPRETATION & CONCLUSION:

The created risk maps may provide useful information to guide the control programme interventions and prevent the economic loses in the future insecticide applications. They could be used to better understand the distribution of vectors, and determine the epidemiology and risk level of the CL.

PMID:
29097638
[Indexed for MEDLINE]
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