ABSTRACT
Objective: To determine whether permutation scan statistics was more efficient in finding prospective spatial-temporal outbreaks for cutaneous leishmaniasis (CL) or for malaria in Fars province, Iran in 2016. Methods: Using time-series data including 29 177 CL cases recorded during 2010-2015 and 357 malaria cases recorded during 2010-2015, CL and malaria cases were predicted in 2016. Predicted cases were used to verify if they followed uniform distribution over time and space using space-time analysis. To testify the uniformity of distributions, permutation scan statistics was applied prospectively to detect statistically significant and non-significant outbreaks. Finally, the findings were compared to determine whether permutation scan statistics worked better for CL or for malaria in the area. Prospective permutation scan modeling was performed using SatScan software. Results: A total of 5 359 CL and 23 malaria cases were predicted in 2016 using time-series models. Applied time-series models were well-fitted regarding auto correlation function, partial auto correlation function sample/model, and residual analysis criteria (P
ABSTRACT
Background: Geographical distribution of zoonotic cutaneous leishmaniasis [ZCL] has continuously been extended in recent years in Iran. The Beiza District is one of the newly-emerged endemic foci of ZCL in southern Iran. The main aim of the present study was to detect the vector[s] of ZCL in this area
Methods: To detect the fauna and vectors of ZCL in this district, sand flies were caught using sticky papers. Seventy randomly selected female sand flies out of 730 were molecularly investigated for Leishmania infection using species-specific nested polymerase chain reaction [PCR] assay between April and October 2010
Results: A total of 2543 sand flies were caught. The fauna was identified as 10 species [five Phlebotomus spp. and five Sergentomyia spp.]. Phlebotomus papatasi was the most dominant species both indoors and outdoors [37.55% and 16.35%, respectively]. L. major was detected in 5 out of 48 investigated Phlebotomus papatasi [10.41%]. Sequence-based characterization was carried out to confirm the PCR findings. The positive samples were shown to have 75-88% similarity with L. major sequences in GenBank
Conclusion: According to the findings of the present study, similar to the other foci of ZCL in Iran, P. papatasi is the proven and primary vector of CL. This study could be drawn upon for future strategy planning in this newly emerged endemic focus