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We analysed both pooled and individual tick samples collected from four countries in Eastern Europe and the Black Sea region, using metagenome-based nanopore sequencing (NS) and targeted amplification. Initially, 1337 ticks, belonging to 11 species, were screened in 217 pools. Viruses (21 taxa) and human pathogens were detected in 46.5% and 7.3%, respectively. Tick-borne viral pathogens comprised Tacheng Tick Virus 2 (TTV2, 5.9%), Jingmen Tick Virus (JMTV, 0.9%) and Tacheng Tick Virus 1 (TTV1, 0.4%). An association of tick species with individual virus taxa was observed, with the exception of TTV2, which was observed in both Dermacentor and Haemaphysalis species. Individual ticks from pools with pathogen detection were then further screened by targeted amplification and then NS, which provided extensive genome data and revealed probable pathogen Haseki Tick Virus (HTV, 10.2%). Two distinct TTV2 clades were observed in phylogenetic analysis, one of which included closely related Dermacentor reticulatus Uukuviruses. JMTV detection indicated integrated virus sequences. Overall, we observed an expansion of newly documented pathogenic tick-borne viruses into Europe, with TTV1 being identified on the continent for the first time. These viruses should be included in the diagnostic assessment of symptomatic cases associated with tick bites and vector surveillance efforts. NS is shown as a useful tool for monitoring tick-associated pathogens in pooled or individual samples., (© 2023. The Author(s).)

With over 3500 mosquito species described, accurate species identification of the few implicated in disease transmission is critical to mosquito borne disease mitigation. Yet this task is hindered by limited global taxonomic expertise and specimen damage consistent across common capture methods. Convolutional neural networks (CNNs) are promising with limited sets of species, but image database requirements restrict practical implementation. Using an image database of 2696 specimens from 67 mosquito species, we address the practical open-set problem with a detection algorithm for novel species. Closed-set classification of 16 known species achieved 97.04 ± 0.87% accuracy independently, and 89.07 ± 5.58% when cascaded with novelty detection. Closed-set classification of 39 species produces a macro F1-score of 86.07 ± 1.81%. This demonstrates an accurate, scalable, and practical computer vision solution to identify wild-caught mosquitoes for implementation in biosurveillance and targeted vector control programs, without the need for extensive image database development for each new target region.

Long-distance migration of insects impacts food security, public health, and conservation-issues that are especially significant in Africa. Windborne migration is a key strategy enabling exploitation of ephemeral havens such as the Sahel, however, its knowledge remains sparse. In this first cross-season investigation (3 years) of the aerial fauna over Africa, we sampled insects flying 40-290 m above ground in Mali, using nets mounted on tethered helium-filled balloons. Nearly half a million insects were caught, representing at least 100 families from thirteen orders. Control nets confirmed that the insects were captured at altitude. Thirteen ecologically and phylogenetically diverse species were studied in detail. Migration of all species peaked during the wet season every year across localities, suggesting regular migrations. Species differed in flight altitude, seasonality, and associated weather conditions. All taxa exhibited frequent flights on southerly winds, accounting for the recolonization of the Sahel from southern source populations. "Return" southward movement occurred in most taxa. Estimates of the seasonal number of migrants per species crossing Mali at latitude 14°N were in the trillions, and the nightly distances traversed reached hundreds of kilometers. The magnitude and diversity of windborne insect migration highlight its importance and impacts on Sahelian and neighboring ecosystems.

Over the past two decades efforts to control malaria have halved the number of cases globally, yet burdens remain high in much of Africa and the elimination of malaria has not been achieved even in areas where extreme reductions have been sustained, such as South Africa 1,2 . Studies seeking to understand the paradoxical persistence of malaria in areas in which surface water is absent for 3-8 months of the year have suggested that some species of Anopheles mosquito use long-distance migration 3 . Here we confirm this hypothesis through aerial sampling of mosquitoes at 40-290 m above ground level and provide-to our knowledge-the first evidence of windborne migration of African malaria vectors, and consequently of the pathogens that they transmit. Ten species, including the primary malaria vector Anopheles coluzzii, were identified among 235 anopheline mosquitoes that were captured during 617 nocturnal aerial collections in the Sahel of Mali. Notably, females accounted for more than 80% of all of the mosquitoes that we collected. Of these, 90% had taken a blood meal before their migration, which implies that pathogens are probably transported over long distances by migrating females. The likelihood of capturing Anopheles species increased with altitude (the height of the sampling panel above ground level) and during the wet seasons, but variation between years and localities was minimal. Simulated trajectories of mosquito flights indicated that there would be mean nightly displacements of up to 300 km for 9-h flight durations. Annually, the estimated numbers of mosquitoes at altitude that cross a 100-km line perpendicular to the prevailing wind direction included 81,000 Anopheles gambiae sensu stricto, 6 million A. coluzzii and 44 million Anopheles squamosus. These results provide compelling evidence that millions of malaria vectors that have previously fed on blood frequently migrate over hundreds of kilometres, and thus almost certainly spread malaria over these distances. The successful elimination of malaria may therefore depend on whether the sources of migrant vectors can be identified and controlled.