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Mosquito-borne diseases (MBDs) have been spreading across many countries including Europe over the past two decades, causing thousands of deaths annually. They are transmitted through the bites of infectious mosquitoes. Environmental, meteorological and other spatio-temporally variables affect the mosquito abundance (MA), and thus affect the circulation of the MBDs in the community. So an early warning system of MA based on these parameters could serve as a warning for the upcoming MBDs incidence. We propose Deep-MAMOTH, a data driven, generic and accurate early warning system for predicting MA in the upcoming period, based on earth observational (EO) environmental data and optionally in-situ entomological data. Deep-MAMOTH can be easily replicated and applied to multiple areas of interest without any special parametrization.The Deep-MAMOTH pipeline collects EO information from various data sources (temperature, rainfall, vegetation, distance from coast, elevation, etc.) and in-situ entomological data for each area of interest. Then, there is a feature extraction phase that combines the previous collected information to more complex features, and finally this data is fed into a Deep Neural Network responsible to capture the relationship between the above mentioned features and the MA, delivering a MA risk class ordered from 0 to 9 for the upcoming period (e.g. 15 days). The pipeline provides a standardized way to predict MA without depending on the area of interest or the mosquito genus and can be modified to predict the actual MA instead of a risk class. However, risk classes help to better propagate the severity of the situation.Two versions of Deep-MAMOTH were implemented, the first one is using recently collected entomological information in order to produce predictions (i.e. mosquitoes collected 1 week ago). The other version works when there is no recently collected entomological information for the area of interest. The latter version is expected to perform worse than the first one, but gives us the capability to produce predictions anywhere on earth without the need of recently collected entomological data. We applied Deep-MAMOTH in Veneto (Italy), in Upper Rhine region (Germany), and the Vojvodina region (Serbia) regarding the Culex spp. genus mosquito. The results are promising as Deep-MAMOTH in Italy achieves a mean absolute error (MAE) of 1.27 classes with the percentage of predictions that deviate at most 3 classes (e3) from the actual one reaching up to 95%. In Serbia MAE is 1.77 classes, with e3 equal to 88% and finally for Germany MAE is 0.92 classes and e3 equal to 94%. It’s worth mentioning that prediction performance in the version of Deep-MAMOTH without using entomological information remains promising. MAE in Italy was increased only by 0.02 and in Germany by 0.1, with e3 remaining at the same level in both cases, while in Serbia MAE increased by 0.2 with e3 decreasing by 8%. We conclude that the prediction of MA from EO data can be accurate with or without recently collected entomological data.Acknowledgment:This research has been co-financed by the ERD Fund of the EU and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, RESEARCH-CREATE-INNOVATE(project code:T2EDK-02070)

Background Colonization of large part of Europe by the Asian tiger mosquito Aedes albopictus is causing autochthonous transmission of chikungunya and dengue exotic arboviruses. While pyrethroids are recommended only to reduce/limit transmission, they are widely implemented to reduce biting nuisance and to control agricultural pests, increasing the risk of insurgence of resistance mechanisms. Worryingly, pyrethroid resistance (with mortality Ae. albopictus populations from Italy and Spain and associated with the V1016G point mutation in the voltage-sensitive sodium channel gene conferring knockdown resistance (kdr). Genotyping pyrethroid resistance-associated kdr mutations in field mosquito samples represents a powerful approach to detect early signs of resistance without the need for carrying out phenotypic bioassays which require availability of live mosquitoes, dedicated facilities and appropriate expertise. Methods Here we report results on the PCR-genotyping of the V1016G mutation in 2530 Ae. albopictus specimens from 69 sampling sites in 19 European countries. Results The mutation was identified in 12 sites from nine countries (with allele frequencies ranging from 1 to 8%), mostly distributed in two geographical clusters. The western cluster includes Mediterranean coastal sites from Italy, France and Malta as well as single sites from both Spain and Switzerland. The eastern cluster includes sites on both sides of the Black Sea in Bulgaria, Turkey and Georgia as well as one site from Romania. These results are consistent with genomic data showing high connectivity and close genetic relationship among West European populations and a major barrier to gene flow between West European and Balkan populations. Conclusions The results of this first effort to map kdr mutations in Ae. albopictus on a continental scale show a widespread presence of the V1016G allele in Europe, although at lower frequencies than those previously reported from Italy. This represents a wake-up call for mosquito surveillance programs in Europe to include PCR-genotyping of pyrethroid resistance alleles, as well as phenotypic resistance assessments, in their routine activities. Graphical Abstract

The epidemiology of West Nile (WNV) and Usutu virus (USUV) has changed dramatically over the past two decades. Since 1999, there have been regular reports of WNV outbreaks and the virus has expanded its area of circulation in many Southern European countries. After emerging in Italy in 1996, USUV has spread to other countries causing mortality in several bird species. In 2009, USUV seroconversion in horses was reported in Italy. Co-circulation of both viruses was detected in humans, horses and birds. The main vector of WNV and USUV in Europe is Culex pipiens, however, both viruses were found in native Culex mosquito species (Cx. modestus, Cx. perexiguus). Experimental competence to transmit the WNV was also proven for native and invasive mosquitoes of Aedes and Culex genera (Ae. albopictus, Ae. detritus, Cx. torrentium). Recently, Ae. albopictus and Ae. japonicus naturally-infected with USUV were reported. While neuroinvasive human WNV infections are well-documented, USUV infections are sporadically detected. However, there is increasing evidence of a role of USUV in human disease. Seroepidemiological studies showed that USUV circulation is more common than WNV in some endemic regions. Recent data showed that WNV strains detected in humans, horses, birds, and mosquitoes mainly belong to lineage 2. In addition to European USUV lineages, some reports indicate the presence of African USUV lineages as well. The trends in WNV/USUV range and vector expansion are likely to continue in future years. This mini- review provides an update on the epidemiology of WNV and USUV infections in Southern Europe within a multidisciplinary "One Health" context.

AIC (Table S1) and MAE (Table S2) scores for the different models and correlations between weather variables per functional unit (Fig. S1). (PDF 478Â kb)

Book Review: Mosquitoes and Their Control, Norbert Becker, Dusan Petric, Marija Zgomba, Clive Boase, Christine Dahl, John Lane, Achim Kaiser, Kluwer Academic/Plenum Publishers, New York (2003).