First evidence of circulation of multiple arboviruses in Algeria

Abstract

Background: Algeria like other North African countries is experiencing recurrent episodes of West Nile Virus (WNV) emergences and new health threats associated with the introduction of Aedes albopictus in 2010 are to be feared. To improve the surveillance of mosquito-borne pathogens, we performed a study using innovative tools based on multiplex molecular methods.

Methods: We combined two approaches: a high-throughput chip based on the BioMark Dynamic array system to detect arboviruses in mosquitoes, and a set of immunologic methods (ELISA, microsphere immunoassays (MIA) and virus microneutralization tests (MNT)) for serological surveys in animal hosts. We investigated two distinct regions: a first zone located in the coastal humid region and a second one in the Saharan desert region.

Principal findings: We collected a total of 1,658 mosquitoes belonging to nine different species and found predominantly Culex pipienss. l. (56.5%) and Cx. perexiguus (27.5%). From 180 pools of 10 mosquitoes, we detected four arboviruses: Banna virus (BAV), chikungunya virus (CHIKV), Sindbis virus (SINV), and Usutu virus (USUV). Moreover, we examined 389 blood samples from equids and poultry and found that 52.4% were positive for flavivirus antibodies in ELISA, while 30.8% were positive for WNV and two chickens and two equids were positive for USUV by MNT and MIA respectively.

Conclusions: To our knowledge, this is the first report of five arboviruses circulating in Algeria, with three reported for the first time (CHIKV, BAV, and USUV). Our study brings evidence that reinforcing surveillance using more discriminant tools may help in anticipating future emergences and propose adapted control measures.

Fig 1. Map of mosquito and animal (equids and birds) collection sites.

The map was built using the open source map site: Qgis 3.28.13 Software(https://qgis.org/license/), Shape files: Algeria subnational administrative boundaries: https://data.humdata.org/dataset/cod-ab-dza?https://data.humdata.org/dataset/3d17274d-0812-4b21-b87a-4854af4eb244/resource/34f317e5-7de9-4e1b-a457-91ab786dc952/download/dza_admbnda_unhcr2020_shp.zip.

Fig 2. Phylogenetic tree of Banna virus based on the 12^th segment (SV12).

Sequences were aligned by MUSCLE. The phylogenetic tree was inferred using the Maximum Likelihood method, the General Time Reversible model and bootstrap method. The tree with the highest log likelihood (-6246.98) is shown.