scan uses state-of-the-art object detection algorithms for the recognition of different tick species belonging to the Hyalomma genus. Ticks of this genus are amongst the most frequent ectoparasites of livestock in the NENA region, they transmit several pathogens of veterinary and zoonotic importance. scan has been applied up to date to the recognition of two important Hyalomma species in Tunisia, Hyalomma dromedarii which has been recently shown to carry the Crimean–Congo hemorrhagic fever virus in Southern Tunisia, and H. scupense which is the vector of T. annulata the agent of tropical theileriosis an important disease of cattle in the NENA region. scan may help better mitigate tick threats through early detection of population dynamic shifts, having therefore the potential to be applied as a tick surveillance tool.
This work has been developed and implemented by
Oussama othmani
Sayed Zamiti
Amine Mosbah
Mourad Ben Said
Sajid Ali
Moez Mhadhbi
Mourad Rekik
Mohamed Aziz Darghouth