Authors
Wasia Ullah, Rabia Rabia
Published in
Die Naturwissenschaften. Volume 113. Issue 4. Jul 17, 2026. Epub Jul 17, 2026.
Abstract
Leishmania parasites, which cause leishmaniasis-an extensive and growing public health concern in Pakistan-are only transmitted to humans by phlebotomine sand flies (Diptera: Psychodidae). This systematic literature review provides an overview of existing entomological surveillance conducted from 2015 to 2025, using rigorous biogeographical and ecological methodologies to describe patterns of species distributions, habitat associations and vector dynamics across Pakistan's diverse landscapes. Our synthesis of data from 73 studies shows that 32 species have been recorded from both the Phlebotomus and Sergentomyia genera. Of these, Phlebotomus papatasi Scopoli and Phlebotomus sergenti Parrot represent successful hematophagous phlebotomine vectors with potential for significant biogeographical expansion due to human-induced landscape alterations or changes caused by climate change. There are clear deficits in the number of entomological studies available in Gilgit-Baltistan, Southern Punjab and Eastern Balochistan compared to the hyperendemic districts of Khyber Pakhtunkhwa (χ2 = 24.7, p < 0.001). Cryptic speciation of the Phlebotomus sergenti complex has been resolved via molecular phylogenetics, whereas ecological niche modelling suggests northward contractions under RCP climatic scenarios. The paper discusses important gaps in our understanding of the ecology of larval habitats, insecticide resistance monitoring, and thorough studies of vector incrimination beyond primary sites. We suggest that the biogeography of the sand fly vectors that transmit leishmaniasis in Pakistan is driven by their dynamic and climate-sensitive nature and, as such, should be a fundamental component of any strategy to control the disease. To this end, we propose a strategic framework that promotes an integrated and One Health-aligned national surveillance program to support evidence-based vector control and reduce the impact of disease using standardized molecular diagnostic tools, longitudinal monitoring techniques, and predictive spatial modelling.
PMID:
42467232
Bibliographic data and abstract were imported from PubMed on 17 Jul 2026.
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