Distribution of vectors and arboviruses, and healthcare workers’ knowledge of vector-borne diseases in Armenia - Babayan, Lilit; Manucharyan, Arsen; Paronyan, Lusine; Vardanyan, Haykuhi; Danielyan, Ruben; Melik-Andreasyan, Gayane; Achenbach, Jenna E (The Journal of Infection in Developing Countries, 2024)
Introduction: Armenia’s favorable geographical and climatic conditions support mosquitoes, sandflies, and ticks that can transmit various diseases. This study aimed to determine the prevalence of these vectors and circulating arboviruses in Armenia and assess healthcare workers` knowledge of arboviral diseases. Methodology: In 2021, we conducted fieldwork, combining morphological identification of vectors with polymerase chain reaction (PCR) analysis of pathogens to map the distribution of potential arbovirus vectors across Armenia. Results: Our entomological surveys identified four mosquito genera—Anopheles, Aedes, Culex, and Culiseta—comprising 20 species; and 11 species of Ixodidae ticks. Culex pipiens was found in all 11 regions, while Culiseta spp. was absent in Ararat Province. PCR testing of mosquito and tick samples revealed Crimean-Congo hemorrhagic fever virus (CCHFV) in 13 tick samples, but West Nile virus (WNV) was not detected in mosquitoes. Specifically, 13 out of 525 Ixodes tick pools tested positive for CCHFV; the positive samples originated from Hyalomma marginatum ticks in Syunik’s Sisian region. None of the 11 pools that contained 473 Cx. pipiens mosquitoes tested positive for WNV. Analysis of questionnaires from 499 healthcare workers showed that epidemiologists, infectious disease specialists, and family doctors had greater awareness of arboviral diseases than other specialists. However, there was a low rate of sample submission for laboratory diagnosis and confirmation. Conclusions: The extensive presence of vectors combined with limited knowledge of arboviral diseases complicates disease understanding in Armenia. Strengthening the surveillance system through training and improved sample collection is essential for disease monitoring and public health interventions.