Robust mosquito species identification from diverse body and wing images using deep learning.

Mosquito-borne diseases are a major global health threat. Traditional morphological or molecular methods for identifying mosquito species often require specialized expertise or expensive laboratory equipment. The use of convolutional neural networks (CNNs) to identify mosquito species based on images may offer a promising alternative, but their practical implementation often remains limited. This study explores the applicability of CNNs in classifying mosquito species. It compares the efficacy of body and wing depictions across three image collection methods: a smartphone, macro-lens attached to a smartphone and a professional stereomicroscope. The study included 796 specimens of four morphologically similar Aedes species, Aedes aegypti, Ae. albopictus, Ae. koreicus and Ae. japonicus japonicus. The findings of this study indicate that CNN models demonstrate superior performance in wing-based classification 87.6% (95% CI: 84.2-91.0) compared to body-based classification 78.9% (95% CI: 77.7-80.0). Nevertheless, there are notable limitations of CNNs as they perform reliably across multiple devices only when trained specifically on those devices, resulting in an average decline of mean accuracy by 14%, even with extensive image augmentation. Additionally, we also estimate the required training data volume for effective classification, noting a reduced requirement for wing-based classification compared to body-based methods. Our study underscores the viability of both body and wing classification methods for mosquito species identification while emphasizing the need to address practical constraints in developing accessible classification systems.

Host attraction and host feeding patterns indicate generalist feeding of Culex pipiens s.s. and Cx. torrentium.

BACKGROUND: Mosquito host feeding patterns are an important factor of the species-specific vector capacity determining pathogen transmission routes. Culex pipiens s.s./Cx. torrentium are competent vectors of several arboviruses, such as West Nile virus and Usutu virus. However, studies on host feeding patterns rarely differentiate the morphologically indistinguishable females. METHODS: We analyzed the host feeding attraction of Cx. pipiens and Cx. torrentium in host-choice studies for bird, mouse, and a human lure. In addition, we summarized published and unpublished data on host feeding patterns of field-collected specimens from Germany, Iran, and Moldova from 2012 to 2022, genetically identified as Cx. pipiens biotype pipiens, Cx. pipiens biotype molestus, Cx. pipiens hybrid biotype pipiens × molestus, and Cx. torrentium, and finally put the data in context with similar data found in a systematic literature search. RESULTS: In the host-choice experiments, we did not find a significant attraction to bird, mouse, and human lure for Cx. pipiens pipiens and Cx. torrentium. Hosts of 992 field-collected specimens were identified for Germany, Iran, and Moldova, with the majority determined as Cx. pipiens pipiens, increasing the data available from studies known from the literature by two-thirds. All four Culex pipiens s.s./Cx. torrentium taxa had fed with significant proportions on birds, humans, and nonhuman mammals. Merged with the data from the literature from 23 different studies showing a high prevalence of blood meals from birds, more than 50% of the blood meals of Cx. pipiens s.s. were identified as birds, while up to 39% were human and nonhuman mammalian hosts. Culex torrentium fed half on birds and half on mammals. However, there were considerable geographical differences in the host feeding patterns. CONCLUSIONS: In the light of these results, the clear characterization of the Cx. pipiens s.s./Cx. torrentium taxa as ornithophilic/-phagic or mammalophilic/-phagic needs to be reconsidered. Given their broad host ranges, all four Culex taxa could potentially serve as enzootic and bridge vectors.

Genetic diversity and wing geometric morphometrics among four populations of Aedes aegypti (Diptera: Culicidae) from Benin.

BACKGROUND: The impact of the arbovirus vector Aedes aegypti is of major concern for global public health as the viruses that it transmits affect millions of people each year worldwide. Originating in Africa, Ae. aegypti has now spread throughout much of the world. While the genetic makeup of Ae. aegypti in the New World has been extensively studied, there is limited knowledge on its genetic diversity in Africa, particularly at a microgeographical level. METHODS: We investigated mitochondrial cytochrome oxidase I of four Ae. aegypti populations from Benin and employed wing morphometric analyses as a cost-effective and reliable tool to explore population structure. Our sampling encompassed various areas of Benin, from the southern to the northern borders of the country, and included urban, semi-urban, and sylvatic sites. RESULTS: We observed a notable level of genetic diversity (haplotype diversity of 0.8333) and nucleotide diversity (0.00421986), and identified seven distinct haplotypes. Sylvatic and semi-urban sites exhibited a greater number of haplotypes compared to urban sites. Utilizing 18 wing landmarks, we calculated the centroid size, which revealed significant variation among the three landscape types. However, principal component analysis, employed to assess wing shape variation, did not demonstrate significant differences between populations based on landscape type. CONCLUSIONS: Our findings indicate substantial genetic and morphological diversity among Ae. aegypti populations in Benin, and provide insight into important biological characteristics of these populations with respect to their potential to transmit viruses. To the best of our knowledge, this is the first study undertaken in Africa to integrate genetics with morphology to analyse the population structure of the major arbovirus vector Ae. aegypti.

Effects of mosquito resting site temperatures on the estimation of pathogen development rates in near-natural habitats in Germany.

BACKGROUND: Environmental temperature is a key driver for the transmission risk of mosquito-borne pathogens. Epidemiological models usually relate to temperature data from standardized weather stations, but these data may not capture the relevant scale where mosquitoes experience environmental temperatures. As mosquitoes are assumed to spend most of their lifetime in resting sites, we analysed mosquito resting site patterns and the associated temperatures in dependence on the resting site type, resting site height and the surrounding land use. METHODS: The study was conducted in 20 areas in near-natural habitats in Germany. Ten areas were studied in 2017, and another 10 in 2018. Each study area consisted of three sampling sites, where we collected mosquitoes and microclimatic data in artificial (= garden pop-up bags) and natural resting sites at three height levels between 0 and 6 m. Land use of the study sites was characterized as forest and meadows based on reclassified information of the CORINE (Coordination of Information on the Environment) Land Cover categories. The hourly resting site temperatures and the data from the nearest weather station of the German meteorological service were used to model the duration of the extrinsic incubation period (EIP) of mosquito-borne pathogens. RESULTS: Anopheles, Culex and Culiseta preferred artificial resting sites, while Aedes were predominantly collect in natural resting sites. Around 90% of the mosquitoes were collected from resting sites below 2 m. The mosquito species composition did not differ significantly between forest and meadow sites. Mean resting site temperatures near the ground were approximately 0.8 °C lower than at a height of 4-6 m, which changed the predicted mean EIP up to 5 days at meadow and 2 days at forest sites. Compared with temperature data from standardized weather stations, the resting site temperatures near the ground would prolong the mean estimated EIP 4 days at forest sites and 2 days at meadow sites. CONCLUSIONS: The microclimate of mosquito resting sites differs from standardized meteorological data, which can influence the transmission of mosquito-borne pathogens. In a near-natural environment, colder temperatures at mosquitoes' preferred resting sites near the ground would prolong the EIP of mosquito-borne pathogens relative to data from weather stations.