Identification Of Mosquito Species Research Articles

Infrared light sensors permit rapid recording of wingbeat frequency and bioacoustic species identification of mosquitoes

Recognition and classification of mosquitoes is a critical component of vector-borne disease management. Vector surveillance, based on wingbeat frequency and other parameters, is becoming increasingly important in the development of automated identification systems, but inconsistent data quality and results frequently emerge from different techniques and data processing methods which have not been standardized on wingbeat collection of numerous species. We developed a simple method to detect and record mosquito wingbeat by multi-dimensional optical sensors and collected 21,825 wingbeat files from 29 North American mosquito species. In pairwise comparisons, wingbeat frequency of twenty six species overlapped with at least one other species. No significant differences were observed in wingbeat frequencies between and within individuals of Culex quinquefasciatus over time. This work demonstrates the potential utility of quantifying mosquito wingbeat frequency by infrared light sensors as a component of an automated mosquito identification system. Due to species overlap, wingbeat frequency will need to integrate with other parameters to accurately delineate species in support of efficient mosquito surveillance, an important component of disease intervention.

Identification of mosquito species and determination of population density in the Taif governorate, Saudi Arabia

The surveillance of mosquitoes is the primary method for protecting humans from the spread of dangerous diseases such as malaria and dengue fever transmitted by certain mosquito species. The present study aimed to survey and identify mosquito species in the Taif governorate to determine their medical importance and monitor their distribution across seasons. A black hole light trap was used to collect adult mosquitoes, with four readings per month over an entire year recorded. A total of 3796 adult mosquitoes were collected, and 12 species were identified. All species belonged to the following genera: Culex, Aedes, Anopheles, Culiseta, and Lutzia; however, mosquito genera of medical importance (i.e., Culex, Aedes, and Anopheles) were examined in the present study. Adult mosquito species occurred throughout the entire year, with peaks of density and activity during summer and autumn (24-30°C), confirming that environmental temperature plays a key role in mosquito existence and distribution. This study might provide evidence regarding the spread of mosquitoes and creates a database of the mosquito species in the Taif governorate, which would assist in pest control programs.

Metagenomic sequencing reveals viral abundance and diversity in mosquitoes from the Shaanxi-Gansu-Ningxia region, China.

BackgroundMosquitoes host and transmit numerous arthropod-borne viruses (arboviruses) that cause disease in both humans and animals. Effective surveillance of virome profiles in mosquitoes is vital to the prevention and control of mosquito-borne diseases in northwestern China, where epidemics occur frequently.MethodsMosquitoes were collected in the Shaanxi-Gansu-Ningxia region (Shaanxi Province, Gansu Province, and Ningxia Hui Autonomous Region) of China from June to August 2019. Morphological methods were used for taxonomic identification of mosquito species. High-throughput sequencing and metagenomic analysis were used to characterize mosquito viromes.ResultsA total of 22,959 mosquitoes were collected, including Culex pipiens (45.7%), Culex tritaeniorhynchus (40.6%), Anopheles sinensis (8.4%), Aedes (5.2%), and Armigeres subalbatus (0.1%). In total, 3,014,183 (0.95% of clean reads) viral sequences were identified and assigned to 116 viral species (including pathogens such as Japanese encephalitis virus and Getah virus) in 31 viral families, including Flaviviridae, Togaviridae, Phasmaviridae, Phenuiviridae, and some unclassified viruses. Mosquitoes collected in July (86 species in 26 families) showed greater viral diversity than those from June and August. Culex pipiens (69 species in 25 families) and Culex tritaeniorhynchus (73 species in 24 families) carried more viral species than Anopheles sinensis (50 species in 19 families) or Aedes (38 species in 20 families) mosquitoes.ConclusionViral diversity and abundance were affected by mosquito species and collection time. The present study elucidates the virome compositions of various mosquito species in northwestern China, improving the understanding of virus transmission dynamics for comparison with those of disease outbreaks.

The Unequal Taxonomic Signal of Mosquito Wing Cells.

Simple SummaryMosquitoes of the genus Aedes include important vectors of human disease viruses, including dengue, chikungunya and Zika. Surveillance programs used to detect and control these pests need accurate, fast and low-cost techniques to track the primary target and monitor possible re-infestations. Geometric morphometrics of mosquito wings is a convenient tool in mosquito species identification, but this method requires a complete wing in good condition for maximum accuracy. In this study, we investigate the amount of taxonomic signal provided by shape analysis of the internal cells of the wing. We show that (i) the internal cells of the wing provide differing amounts of taxonomic information, and (ii) the taxonomic signal of a given cell depends on the species under comparison. Since some of these cells are very informative, our study suggests that even damaged wings may provide key taxonomic information to differentiate among species found in mixed species surveillance collections.Accurate identification of mosquito species is critically important for monitoring and controlling the impact of human diseases they transmit. Here, we investigate four mosquito species: Aedes aegypti, Ae. albopictus, Ae. scutellaris and Verrallina dux that co-occur in tropical and subtropical regions, and whose morphological similarity challenges their accurate identification, a crucial requirement in entomological surveillance programs. Previous publications reveal a clear taxonomic signal embedded in wing cell landmark configuration, as well as in the external contour of the wings. We explored this signal for internal cells of the wings as well, to determine whether internal cells could uniformly provide the same taxonomic information. For each cell to be tentatively assigned to its respective species, i.e., to measure the amount of its taxonomic information, we used the shape of its contour, rather than its size. We show that (i) the taxonomic signal of wing shape is not uniformly spread among internal cells of the wing, and (ii) the amount of taxonomic information of a given cell depends on the species under comparison. This unequal taxonomic signal of internal cells is not related to size, nor to apparent shape complexity. The strong taxonomic signal of some cells ensures that even partly damaged wings can be used to improve species recognition.

DNA-based identification and control of disease spreading mosquito species: A review

DNA-based identification and control of disease spreading mosquito species: A review

Identification and seasonal distribution of mosquito species in Telangana state, India

An entomological study was conducted to determine species composition, relative abundance, and seasonal population fluctuation of mosquitoes. Thirty localities were randomly selected and sampled once in summer, monsoon and winter seasons for a period of three years. Adult mosquitoes were collected from in and around human dwellings and animal sheds using aspirator and flash light between 6 PM and 7:30 PM hrs and 06:00 AM and 7:00 AM hrs. Larvae were collected from ditches, rock pool and other domestic habitats, reared to formation of adults in the lab. A total of 18425 mosquitoes were collected. Five genera (Culex, Anopheles, Aedes, Mansonia and Armigeres) were found to be circulating. Further, with respect to habitat, more number of mosquitoes were observed around cattle sheds and houses. Culex quinquefasciatus occupies top place, followed by Aedes albopictus and Culex gelidus, Culex tritaeniorhynchus with respect to density, whereas Mansonia uniformis occupies last place. Culex quinquifasciatus is top again followed by Culex gelidus and Aedes albopictus, Mansonia uniformis is last again with respect to distribution. The vector species studied were Aedes aegypti, Aedes albopictus for chikungunya and dengue, Anopheles stephensi, Anopheles culicifacies for malaria, Culex tritaeniorhynchus for Japanese encephalitis and Culex quiquefasciatus for lymphatic filaria.

Classifying mosquito presence and genera using median and interquartile values from 26-filter wingbeat acoustic properties

Mosquitoes are known to be one of the deadliest creatures in the world. There have been several studies that aim to identify mosquito presence and species using various techniques. The most common ones involve automatic identification of mosquito species from the sounds produced by flapping its wings. The development of these important concepts and technologies can help reduce the spread of mosquito-borne diseases. This paper presents a simple model based on mean and interquartile values that aim to solve the mosquito classification. Despite its simplicity, the proposed model significantly outperforms a Convolutional Neural Network (CNN) model in identifying the mosquito genus from the classes of Aedes, Anopheles and Culex, with an additional fourth class of No-Mosquito. A dataset of sound recordings from the Humbug Zooniverse, collected by researchers from Oxford University, and augmented with locally collected audio recordings of mosquitoes in the Philippines were used in this study. The proposed technique uses the numerical data from a series of 26 different pass-band filter values generated from spectrograms of audio recordings, specifically computing the statistical measures of median and interquartile values for each filter from instances of the same class. To predict the class of an instance, the sum of squares of differences was computed between the actual values of the instance against the expected values of each class on each of these three statistical measures. The average classification accuracy of our proposed model was 92.8%, and this was higher than the 86.6% classification accuracy yielded by the CNN model. Moreover, the proposed model required much less time for both training and classification than the CNN model. As the proposed model outperformed the CNN model in accuracy and efficiency, the results offer a promising technique that may also simplify the process of solving other sound-based classification problems.

Delimiting cryptic morphological variation among human malaria vector species using convolutional neural networks.

Deep learning is a powerful approach for distinguishing classes of images, and there is a growing interest in applying these methods to delimit species, particularly in the identification of mosquito vectors. Visual identification of mosquito species is the foundation of mosquito-borne disease surveillance and management, but can be hindered by cryptic morphological variation in mosquito vector species complexes such as the malaria-transmitting Anopheles gambiae complex. We sought to apply Convolutional Neural Networks (CNNs) to images of mosquitoes as a proof-of-concept to determine the feasibility of automatic classification of mosquito sex, genus, species, and strains using whole-body, 2D images of mosquitoes. We introduce a library of 1, 709 images of adult mosquitoes collected from 16 colonies of mosquito vector species and strains originating from five geographic regions, with 4 cryptic species not readily distinguishable morphologically even by trained medical entomologists. We present a methodology for image processing, data augmentation, and training and validation of a CNN. Our best CNN configuration achieved high prediction accuracies of 96.96% for species identification and 98.48% for sex. Our results demonstrate that CNNs can delimit species with cryptic morphological variation, 2 strains of a single species, and specimens from a single colony stored using two different methods. We present visualizations of the CNN feature space and predictions for interpretation of our results, and we further discuss applications of our findings for future applications in malaria mosquito surveillance.

Modeling host-feeding preference and molecular systematics of mosquitoes in different ecological niches in Canada

Several mosquito-borne viruses (mobovirus) cause infections in Canada. Ecological data on mosquito species and host range in Canada remains elusive. The main aim of the current study is to determine the host range and molecular systematics of mosquito species in Canada. Mosquitoes were collected using BG-Sentinel traps and aspirators at 10 trapping sites in Canada during 2018 and 2019. Mosquitoes collected were identified via morphology and molecular techniques. Mosquito sequences were aligned by MUSCLE algorithm and evolutionary systematics were drawn using MEGA and SDT software. Moreover, the source of blood meals was identified using a DNA barcoding technique. A total of 5,708 female mosquitoes over 34 different taxa were collected. DNA barcodes and evolutionary tree analysis confirmed the identification of mosquito species in Canada. Of the total collected samples, 201 specimens were blood-fed female mosquitoes in 20 different taxa. Four mosquito species represented about half (51.47%) of all collected blood-fed specimens: Aede cinereus (39 specimens, 19.11%), Aedes triseriatus (23, 11.27%), Culex pipiens (22, 10.78%), and Anopheles punctipennis (21, 10.29%). The most common blood meal sources were humans (49 mosquito specimens, 24% of all blood-fed mosquito specimen), pigs (44, 21.5%), American red squirrels (28, 13.7%), white-tailed deers (28, 13.7%), and American crows (16, 7.8%). Here, we present the first analysis of the host-feeding preference of different mosquito species in Canada via molecular techniques. Our results on mosquito distribution and behavior will aid in the development of effective mitigation and control strategies to prevent or reduce human/animal health issues in regards to moboviruses.

Identification of mosquitoes (Diptera: Culicidae) from Mexico State, Mexico using morphology and COI DNA barcoding

Mosquitoes are commonly identified to species level using morphological traits, but complementary methods for identification are often necessary when specimens are collected as immature stages, stored inadequately, or when delineation of species complexes is problematic. DNA-barcoding using the mitochondrial cytochrome c oxidase subunit 1 (COI) gene is one such tool used for the morphological identification of species. A comprehensive entomological survey of mosquito species in Mexico State identified by COI DNA barcoding and morphology is documented in this paper. Specimens were collected from all the physiographic provinces in Mexico State between 2017 and 2019. Overall, 2,218 specimens were collected from 157 localities representing both subfamilies Anophelinae and Culicinae. A species checklist that consists of 6 tribes, 10 genera, 20 subgenera, and 51 species, 35 of which are new records for Mexico State, is provided. Three hundred and forty-two COI sequences of 46 species were analysed. Mean intraspecific and interspecific distances ranged between 0% to 3.9% and from 1.2% to 25.3%, respectively. All species groups were supported by high bootstraps values in a Neighbour-Joining analysis, and new COI sequences were generated for eight species: Aedes chionotum Zavortink, Ae. vargasi Schick, Ae. gabriel Schick, Ae. guerrero Berlin, Ae. ramirezi Vargas and Downs, Haemagogus mesodentatus Komp and Kumm, Culex restrictor Dyar and Knab, and Uranotaenia geometrica Theobald. This study provides a detailed inventory of the Culicidae from Mexico State and discusses the utility of DNA barcoding as a complementary tool for accurate mosquito species identification in Mexico.

MALDI-TOF MS: optimization for future uses in entomological surveillance and identification of mosquitoes from New Caledonia

BackgroundMosquito vectors cause a significant human public health burden through the transmission of pathogens. Due to the expansion of international travel and trade, the dispersal of these mosquito vectors and the pathogens they carry is on the rise. Entomological surveillance is therefore required which relies on accurate mosquito species identification. This study aimed to optimize the use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for mosquito identification.MethodsAedes aegypti of the Bora-Bora strain and 11 field-sampled mosquito species were used in this study. Analyses were performed to study the impact of the trapping duration on mosquito identification with MALDI-TOF MS. The best preservation methods to use for short, medium and long-term preservation before MALDI-TOF MS analysis were also assessed. In addition, the number of specimens per species required for MALDI-TOF MS database creation was determined. The first MALDI-TOF database of New Caledonian mosquitoes was assembled and the optimal threshold for mosquito species identification according to the sensitivity and specificity of this technique was determined.ResultsThis study showed that the identification scores decreased as the trapping duration increased. High identification scores were obtained for mosquitoes preserved on silica gel and cotton at room temperature and those frozen at − 20 °C, even after two months of preservation. In addition, the results showed that the scores increased according to the number of main spectrum patterns (MSPs) used until they reached a plateau at 5 MSPs for Ae. aegypti. Mosquitoes (n = 67) belonging to 11 species were used to create the MALDI-TOF reference database. During blind test analysis, 96% of mosquitoes tested (n = 224) were correctly identified. Finally, based on MALDI-TOF MS sensitivity and specificity, the threshold value of 1.8 was retained for a secure identification score.ConclusionsMALDI-TOF MS allows accurate species identification with high sensitivity and specificity and is a promising tool in public health for mosquito vector surveillance.

Wing geometric morphometrics for identification of mosquito species (Diptera: Culicidae) of neglected epidemiological importance

Culicidae comprises more than 3500 species, some of which are responsible for the spread of various human diseases, causing millions of deaths worldwide. Correct identification of these species is essential for the development of surveillance and control strategies. The most common method of mosquito identification is based on specific traits of the external morphology of species. However, identification of mosquitoes by morphological characters can be inaccurate or even unfeasible if the specimen is damaged or there is a lack of distinguishing features, as in the case of cryptic species complexes. Wing geometric morphometrics is a reliable, affordable tool for the identification of mosquito species, including sibling species. More importantly, it can be used in addition to both traditional morphologic identification methods as well as genetic approaches. Here, wing geometric morphometrics was used to identify sixteen mosquito species from eight genera: Aedes, Coquillettidia, Culex, Limatus, Mansonia, Psorophora, Runchomyia, and Wyeomyia. The 390 specimens used here were collected in São Paulo, Brazil using CDC traps, aspiration, and Shannon traps. Allometry was assessed by multivariate regression of the Procrustes coordinates on centroid size followed by canonical variate analysis and a pairwise cross-validated reclassification test. A Neighbor-Joining tree based on Mahalanobis distances was constructed with 1,000 bootstrap replicates using MorphoJ 1.02 and Past 2.17c. The canonical variate analysis of genera resulted in distinct clusters for Culex, Limatus, and Psorophora and partial overlapping between Aedes, Coquilettidia, and Mansonia, and between Runchomyia and Wyeomyia. Pairwise cross-validated reclassification tests indicated that genera were identified with an accuracy of at least 99% and subgenera with a mean accuracy of 96% and that in 160 of the 240 possible comparisons species were identified with an accuracy of 100%. Our results show that the eight genera in the study were correctly distinguished by wing shape, as were subgenera and most species, demonstrating that wing geometric morphometrics can be used for the identification of the mosquito species studied here.

Phylogeny of Anopheles (Kerteszia) (Diptera: Culicidae) Using Mitochondrial Genes.

Identification of mosquito species is necessary for determining the entomological components of malaria transmission, but it can be difficult in morphologically similar species. DNA sequences are largely used as an additional tool for species recognition, including those that belong to species complexes. Kerteszia mosquitoes are vectors of human and simian malaria in the Neotropical Region, but there are few DNA sequences of Kerteszia species in public databases. In order to provide relevant information about diversity and improve knowledge in taxonomy of Kerteszia species in Peru, we sequenced part of the mitochondrial genome, including the cytochrome c oxidase I (COI) barcode region. Phylogenetic analyses structured all species of mosquitoes collected in Peru into a single clade, separate from the Brazilian species. The Peruvian clade was composed of two lineages, encompassing sequences from Anopheles (Kerteszia) boliviensis and Anopheles (Kerteszia) pholidotus. An. pholidotus sequences were recorded for the first time in Peru, whereas An. boliviensis sequences were for the first time published in the GenBank database. Sequences generated from specimens morphologically identified as Anopheles (Kerteszia) cruzii clustered into three separate clades according to the collection localities of Serra do Mar, Serra da Mantiqueira, and Serra da Cantareira, confirming An. cruzii as a species complex, composed of at least three putative species.

Real-Time Mosquito Species Identification using Deep Learning Techniques

According to the World Health Organization, diseases such as malaria and dengue account for almost one million deaths every year. Carrier mosquitoes for a particular disease remain exclusive to it. A majority of carrier mosquitoes spread the disease throughout a region by reproducing in it. With advancements in Machine Learning and Computer Vision technologies, the species of mosquitoes in a particular region can be easily and swiftly detected using recordings of their wing movements. The wingbeats of a particular mosquito species are unique, making this a reliable method to identify them. Once these solutions are deployed on mosquito traps, a particular region can be alerted if, for example, an Aedes Aegypti mosquito is found. This mosquito species is widely known to carry the Zika virus. The identification of such carrier species can also help in detecting the spread of mosquito-borne diseases in the surveyed region. In this paper, we go through various techniques that show promising results in the identification of mosquito species. The trained models can be deployed on constrained devices to make a cost-effective and efficient mosquito species identification system.

Ecology and Contribution of Anopheles hancocki Edwards, 1929 in Malaria Transmission in a Village of South Cameroon Forest Block

Anopheles hancocki is one of the secondary vectors of malaria whose larval ecology in the South Cameroonian forest block is still unknown. This information is however fundamental for developing efficient and sustainable control strategies against this mosquito in localities where it acts as a disease vector. The present study describes the larval ecology of A. hancocki and its contribution in malaria transmission in a riverbank village of the Ayos Health District. Mosquito sampling took place in 2018 on a quarterly rate, combining the dipping method for larval collection with adult mosquito capture on volunteers. For each of the breeding sites, physicochemical characteristics were measured and larvae were collected and reared to adult. Molecular alongside morpho-taxonomic techniques were used for the identification of mosquito species. Physiological age was determined based on the appearance of their ovarian tracheoles and CSP Elisa test was used to assess infectivity. In total, 3,618 adult mosquitoes belonging to seven species were collected in the study area, namely A. hancocki, Anopheles gambiae, Anopheles moucheti, Mansonia africana, Culex pipiens quinquefasciatus, Aedes albopictus and Aedes aegypti. Breeding sites of A. hancocki were similar to those of A. gambiae. However, the total dissolved solids and conductivity values were significantly higher in A. gambiae breeding sites than in those of A. hancocki. A. hancocki was the most aggressive mosquito species and represented 45.6% of the local aggressive culicidofauna. Male species' nocturnal cycle of aggression showed maximum activity between 8 pm and 10 pm. Females of this species were significantly older than those of A. gambiae and contributed to 40% of malaria transmission in the locality with an average annual Entomological Inoculation Rate (EIR) of 2.92 ib/p/year lower than that of A. gambiae (3.65 ib/p/year). Except few differences, ecological requirements for the development of A. hancocki larvae are similar to that of A. gambiae. A. hancocki contributes to the perennial transmission of malaria in the Ayos area; implementation of vector control strategies is therefore needed.

SNP barcoding based on decision tree algorithm: A new tool for identification of mosquito species with special reference to Anopheles

Molecular taxonomy based identification of species in the form of DNA barcodes are extensively used in evolutionary systematics. Almost all the DNA barcodes contain detailed information of the barcoding gene along with uninformative sequences of a particular species. Therefore, a technique is highly essential to remove or to reduce the number of uninformative sequences and ought to create species-specific barcodes for differentiation. The actual variation in genetic sequences, called single nucleotide polymorphism (SNP) genotyping, can be utilized to develop a new tool for rapid, reliable, and high-throughput assay to distinguish the known species. SNPs act as important hereditary markers for uncovering the evolutionary history and normal genetic polymorphisms. Keeping in mind, we propose a decision tree-based barcoding (DTB) algorithm for generating SNP barcodes from the DNA barcoding sequence of several evolutionarily related species to accurately identify a single species. To address this issue, we analyzed mitochondrial COI gene sequences of 64 species of Anopheles mosquitoes. After alignment and truncating, 32 SNPs were discovered in COI gene sequences of Anopheles mosquitoes and then computed to set up the decision rule for constructing the decision tree. The decision tree based barcoding algorithm generates 126 nodes and 32 loci for discriminating 64 Anopheles mosquito species. Finally, we concluded that the DTB method is useful and effective for generating sequence tags for Anopheles mosquito species identification.

Comparative analysis of the internal and external outlines of wings for an outline-based geometric morphometric approach to distinguish three Aedes mosquitoes (Diptera: Culicidae) in Thailand

Aedes mosquitoes belong to a subgenus of Stegomyia (Diptera: Culicidae), which are dengue and chigunkunya vectors, including Aedes aegypti, Ae. albopictus, and Ae. scutellaris, and have a worldwide distribution in tropical and subtropical regions. Species identification of mosquitoes is challenging yet necessary to select appropriate control methods for each species. In this study, we have analyzed the different wing components for identification to find the optimal outline for Aedes mosquito analysis by an outline-based GM approach. Two internal and external outlines of the wing were considered for Aedes species identification in this study. A total of 90 Aedes wings were analysed, divided into 30 wings per species (Ae. aegypti, Ae. albopictus, and Ae. scutellaris). The results showed that the mean size of Ae. albopictus had the largest wings, followed by Ae. Aegypti, and Ae. scutellaris, respectively, in all the internal and external outlines. While, the shape analysis in the three outlines were expressed by the factor map, the statistical difference and cross-validated classification scores indicated the ability of the outline-based GM approach to distinguish species of Aedes mosquitoes. The external outline has a relatively good range of cross-validated classification scores compared to the other internal outlines. The results of this research reveal the suitability of this external outline to identify species of Aedes vectors in Thailand.

DNA barcodes and evidence of cryptic diversity of anthropophagous mosquitoes in Quintana Roo, Mexico.

Culicidae mosquitoes are potential vectors of pathogens that affect human health. The correct species identification, as well as the discovery and description of cryptic species, is important in public health for the control and management of specific vectors. In the present study, the diversity of anthropophagous mosquitoes in Quintana Roo, at the border between Mexico and Belize, was evaluated using morphological and molecular data (COI‐DNA Barcoding). A total of 1,413 adult female specimens were collected, belonging to eight genera and 31 morphospecies. Most species formed well‐supported clades. Intraspecific Kimura 2 parameters (K2P) distance average was 0.75%, and a maximum distance of 4.40% was observed for Anopheles crucianss.l. ABGD method identified 28 entities, while 32 entities were identified with the BIN system. In Culex interrogator and Culex nigripalpus a low interspecific genetic distance of 0.1% was observed. One undescribed species belonging to the genus Aedes (Aedesn. sp.) was discovered, but no clear genetic divergence was found between this species and the closely related species Aedes angustivittatus. An intraspecific K2P distance greater than 2.7% was observed in Aedes serratus(3.9%), Anopheles crucianss.l. (4.4%), Culex taeniopus (3.7%), Haemagogus equinus (3.9%), Culex erraticus (5.0%), Psorophora ferox (4.5%), and in Anopheles apicimacula(8.10%); therefore, evidences of cryptic diversity are shown in these species. This study showed that DNA barcodes offer a reliable framework for mosquito species identification in Quintana Roo, except for some closely related species for which it is recommended to use additional nuclear genetic markers such as ITS2, in order to resolve these small discrepancies.

DNA barcoding of British mosquitoes (Diptera, Culicidae) to support species identification, discovery of cryptic genetic diversity and monitoring invasive species.

Correct mosquito species identification is essential for mosquito and disease control programs. However, this is complicated by the difficulties in morphologically identifying some mosquito species. In this study, variation of a partial sequence of the cytochrome c oxidase unit I (COI) gene was used for the molecular identification of British mosquito species and to facilitate the discovery of cryptic diversity, and monitoring invasive species. Three DNA extraction methods were compared to obtain DNA barcodes from adult specimens. In total, we analyzed 42 species belonging to the genera Aedes Meigen, 1818 (21 species), Anopheles Meigen, 1818 (7 species), Coquillettidia Theobald, 1904 (1 species), Culex Linnaeus, 1758 (6 species), Culiseta Felt, 1904 (7 species), and Orthopodomyia Theobald, 1904 (1 species). Intraspecific genetic divergence ranged from 0% to 5.4%, while higher interspecific divergences were identified between Aedesgeminus Peus, 1971/Culisetalitorea (Shute, 1928) (24.6%) and Ae.geminus/An.plumbeus Stephens, 1828 (22.5%). Taxonomic discrepancy was shown between An.daciae Linton, Nicolescu & Harbach, 2004 and An.messeae Falleroni, 1828 indicating the poor resolution of the COI DNA barcoding region in separating these taxa. Other species such as Ae.cantans (Meigen, 1818)/Ae.annulipes (Meigen, 1830) showed similar discrepancies indicating some limitation of this genetic marker to identify certain mosquito species. The combination of morphology and DNA barcoding is an effective approach for the identification of British mosquitoes, for invasive mosquitoes posing a threat to the UK, and for the detection of hidden diversity within species groups.

A community-level investigation following a yellow fever virus outbreak in South Omo Zone, South-West Ethiopia.

BackgroundDespite the availability of a highly effective vaccine, yellow fever virus (YFV) remains an important public health problem across Africa and South America due to its high case-fatality rate. This study investigated the historical epidemiology and contemporary entomological and social determinants of a YFV outbreak in South Omo Zone (SOZ), Ethiopia.MethodsA YFV outbreak occurred in SOZ, Ethiopia in 2012–2014. Historical epidemiological data were retrieved from the SOZ Health Department and analyzed. Entomological sampling was undertaken in 2017, including mosquito species identification and molecular screening for arboviruses to understand mosquito habitat distribution, and finally current knowledge, attitudes and preventative practices within the affected communities were assessed.ResultsFrom October 2012 to March 2014, 165 suspected cases and 62 deaths were reported, principally in rural areas of South Ari region (83.6%). The majority of patients were 15–44 years old (75.8%) and most case deaths were males (76%). Between June and August 2017, 688 containers were sampled across 180 households to identify key breeding sites for Aedes mosquitoes. Ensete ventricosum (“false banana”) and clay pots outside the home were the most productive natural and artificial breeding sites, respectively. Entomological risk indices classified most sites as “high risk” for future outbreaks under current World Health Organization criteria. Adult mosquitoes in houses were identified as members of the Aedes simpsoni complex but no YFV or other arboviruses were detected by PCR. The majority of community members had heard of YFV, however few activities were undertaken to actively reduce mosquito breeding sites.DiscussionStudy results highlight the potential role vector control could play in mitigating local disease transmission and emphasize the urgent need to strengthen disease surveillance systems and in-country laboratory capacity to facilitate more rapid responses to future YFV outbreaks.