Molecular Identification of Phlebotomus caucasicus and Phlebotomus mongolensis (Diptera: Psychodidae) in a Hyperendemic Area of Zoonotic Cutaneous Leishmaniasis in Iran

Evaluation of the biodiversity and distribution of sand flies and tracking of Leishmania major in them in central Iran

Many areas of Iran are endemic regarding Cutaneous leishmaniasis (CL) as a parasitic disease transmitted by a female sand fly vector's bite. The present study investigated the distribution of sand flies in Harand and Egieh in Isfahan province, Central Iran. Overall, 408 out of 1260 collected sand flies were identified morphologically, among which 353 and 55 were isolated from Harand and Egieh, respectively. Also, 66.4% and 33.6% of the sand flies were female and male, respectively. The most prevalent sand fly species were Phlebotomus papatasi (52%), followed by Ph. caucasicus (40.4%), Sergentomyia sintoni (4.9%), and Ph. kazeruni (0.7%). Among 180 molecularly-analyzed sand flies, 14 (7.77%) were found infected with L. major, with 9 out of 103 (8.73%) Ph. papatasi and 5 out of 75 (6.66%) Ph. caucasicus.

Distribution and Risk of Cutaneous Leishmaniasis in Khyber Pakhtunkhwa, Pakistan

Cutaneous leishmaniasis (CL) is a zoonotic infection caused by obligate intracellular protozoa of the genus Leishmania. This study aimed to investigate CL in Khyber Pakhtunkhwa, Pakistan and to estimate the risk of epidemics. Clinico-epidemiological data of 3188 CL patients were collected from health facilities in 2021. Risk factors were analyzed using the chi-square test. ArcGIS V.10.7.1 was applied for spatial analysis. The association between CL occurrence and climatic variables was examined by Bayesian geostatistical analysis. The clinical data revealed males or individuals younger than 20 years old were more affected. Most patients presented with a single lesion, and the face was the most attacked body part. CL was prevalent in the southern region in winter. A proportional symbol map, a choropleth map, and a digital elevation model map were built to show the distribution of CL. Focal transmission was predicted by inverse distance weighting interpolation. Cluster and outlier analysis identified clusters in Bannu, Dir Lower, and Mardan, and hotspot analysis suggested Bannu as a high-risk foci. Bayesian geostatistical analysis indicated that increasing precipitation and temperature as well as low altitudes were associated with CL infection. The study has provided important information for public health sectors to develop intervention strategies for future CL epidemics.