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.

Two snapshot surveys to establish the diversity and ecological preferences of mosquitoes (Diptera: Culicidae) in the terra firme primary rain forest surrounding the Tiputini Biodiversity Station in the UNESCO Yasuní Biosphere Reserve of eastern Amazonian Ecuador were carried out in November 1998 and May 1999. The mosquito fauna of this region is poorly known; the focus of this study was to obtain high quality link-reared specimens that could be used to unequivocally confirm species level diversity through integrated systematic study of all life stages and DNA sequences. A total of 2,284 specimens were preserved; 1,671 specimens were link-reared with associated immature exuviae, all but 108 of which are slide mounted. This study identified 68 unique taxa belonging to 17 genera and 27 subgenera. Of these, 12 are new to science and 37 comprise new country records. DNA barcodes [658-bp of the mtDNA cytochrome c oxidase ( COI ) I gene] are presented for 58 individuals representing 20 species and nine genera. DNA barcoding proved useful in uncovering and confirming new species and we advocate an integrated systematics approach to biodiversity studies in future. Associated bionomics of all species collected are discussed. An updated systematic checklist of the mosquitoes of Ecuador (n = 179) is presented for the first time in 60 years.

Arboviral mosquito vectors are key targets for the surveillance and control of vector-borne diseases worldwide. In recent years, changes to the global distributions of these species have been a major research focus, aimed at predicting outbreaks of arboviral diseases. In this study, we analyzed a global scenario of climate change under regional rivalry to predict changes to these species’ distributions over the next century. Using occurrence data from VectorMap and environmental variables (temperature and precipitation) from WorldClim v. 2.1, we first built fundamental niche models for both species with the boosted regression tree modelling approach. A scenario of climate change on their fundamental niche was then analyzed. The shared socioeconomic pathway scenario 3 (regional rivalry) and the global climate model Geophysical Fluid Dynamics Laboratory Earth System Model v. 4.1 (GFDL-ESM4.1; gfdl.noaa.gov) were utilized for all analyses, in the following time periods: 2021–2040, 2041–2060, 2061–2080, and 2081–2100. Outcomes from these analyses showed that future climate change will affect Ae. aegypti and Ae. albopictus distributions in different ways across the globe. The Northern Hemisphere will have extended Ae. aegypti and Ae. albopictus distributions in future climate change scenarios, whereas the Southern Hemisphere will have the opposite outcomes. Europe will become more suitable for both species and their related vector-borne diseases. Loss of suitability in the Brazilian Amazon region further indicated that this tropical rainforest biome will have lower levels of precipitation to support these species in the future. Our models provide possible future scenarios to help identify locations for resource allocation and surveillance efforts before a significant threat to human health emerges.

Abstract.Crimean-Congo hemorrhagic fever (CCHF) is endemic in Africa, but the epidemiology remains to be defined. Using a broad database search, we reviewed the literature to better define CCHF evidence in Africa. We used a One Health approach to define the impact of CCHF by reviewing case reports, human and animal serology, and records of CCHF virus (CCHFV) isolations (1956–mid-2020). In addition, published and unpublished collection data were used to estimate the geographic distribution of Hyalomma ticks and infection vectors. We implemented a previously proposed classification scheme for organizing countries into five categories by the level of evidence. From January 1, 1956 to July 25, 2020, 494 CCHF cases (115 lethal) were reported in Africa. Since 2000, nine countries (Kenya, Mali, Mozambique, Nigeria, Senegal, Sierra Leone, South Sudan, Sudan, and Tunisia) have reported their first CCHF cases. Nineteen countries reported CCHF cases and were assigned level 1 or level 2 based on maturity of their surveillance system. Thirty countries with evidence of CCHFV circulation in the absence of CCHF cases were assigned level 3 or level 4. Twelve countries for which no data were available were assigned level 5. The goal of this review is to inform international organizations, local governments, and healthcare professionals about shortcomings in CCHF surveillance in Africa to assist in a movement toward strengthening policy to improve CCHF surveillance.

Tick-borne Crimean-Congo hemorrhagic fever virus (CCHFV) is endemic in numerous countries, but the epidemiology and epizoology of Crimean-Congo hemorrhagic fever (CCHF) remain to be defined for most regions of the world. Using a broad database search approach, we reviewed the literature on CCHF and CCHFV in Southern and Western Asia to better define the disease burden in these areas. We used a One Health approach, moving beyond a focus solely on human disease burden to more comprehensively define this burden by reviewing CCHF case reports, human and animal CCHFV seroprevalence studies, and human and animal CCHFV isolations. In addition, we used published literature to estimate the distribution of Hyalomma ticks and infection of these ticks by CCHFV. Using these data, we propose a new classification scheme for organizing the evaluated countries into five categories by level of evidence for CCHF endemicity. Twelve countries have reported CCHF cases, five from Southern Asia and seven from Western Asia. These were assigned to level 1 or 2. Eleven countries that have evidence of vector circulation but did not report confirmed CCHF cases were assigned to level 3 or 4. This classification scheme was developed to inform policy toward strengthening CCHF disease surveillance in the Southern and Western Asia regions. In particular, the goal of this review was to inform international organizations, local governments, and health-care professionals about current shortcomings in CCHFV surveillance in these two high-prevalence regions.

No abstract

We feature SandflyMap (www.sandflymap.org), a new map service within VectorMap (www.vectormap.org) that allows free public online access to global sand fly, tick and mosquito collection records and habitat suitability models. Given the short home range of sand flies, combining remote sensing and collection point data give a powerful insight into the environmental determinants of sand fly distribution. SandflyMap is aimed at medical entomologists, vector disease control workers, public health officials and health planners. Data are checked for geographical and taxonomic errors, and are comprised of vouchered specimen information, and both published and unpublished observation data. SandflyMap uses Microsoft Silverlight and ESRI's ArcGIS Server 10 software platform to present disease vector data and relevant remote sensing layers in an online geographical information system format. Users can view the locations of past vector collections and the results of models that predict the geographic extent of individual species. Collection records are searchable and downloadable, and Excel collection forms with drop down lists, and Excel charts to country, are available for data contributors to map and quality control their data. SandflyMap makes accessible, and adds value to, the results of past sand fly collecting efforts. We detail the workflow for entering occurrence data from the literature to SandflyMap, using an example for sand flies from South America. We discuss the utility of SandflyMap as a focal point to increase collaboration and to explore the nexus between geography and vector-borne disease transmission.

Scientific collections such as the U.S. National Museum (USNM) are critical to filling knowledge gaps in molecular systematics studies. The global taxonomic impediment has resulted in a reduction of expert taxonomists generating new collections of rare or understudied taxa and these large historic collections may be the only reliable source of material for some taxa. Integrated systematics studies using both morphological examinations and DNA sequencing are often required for resolving many taxonomic issues but as DNA methods often require partial or complete destruction of a sample, there are many factors to consider before implementing destructive sampling of specimens within scientific collections. We present a methodology for the use of archive specimens that includes two crucial phases: 1) thoroughly documenting specimens destined for destructive sampling—a process called electronic vouchering, and 2) the pipeline used for whole genome sequencing of archived specimens, from extraction of genomic DNA to assembly of putative genomes with basic annotation. The process is presented for eleven specimens from two different insect subfamilies of medical importance to humans: Anophelinae (Diptera: Culicidae)—mosquitoes and Triatominae (Hemiptera: Reduviidae)—kissing bugs. Assembly of whole mitochondrial genome sequences of all 11 specimens along with the results of an ortholog search and BLAST against the NCBI nucleotide database are also presented.