Origin of Aedes aegypti In Clark County, Nevada

Mesocosm Studies Suggest Climate Change May Release Aedes aegypti (Diptera: Culicidae) Larvae from Cold Inhibition and Enable Year-Round Development in a Desert City

AbstractGlobal warming trends, human-assisted transport, and urbanization have allowed poleward expansion of many tropical vector species, but the specific mechanisms responsible for thermal mediation of range changes and ecological success of invaders remain poorly understood. Aedes aegypti (Diptera: Culicidae) is a tropical mosquito currently expanding into many higher-latitude regions, including the urban desert region of Maricopa County, Arizona. Here, adult populations virtually disappear in winter and spring and then increase exponentially through summer and fall, indicating that winter conditions remain a barrier to the development of some life stages of A. aegypti. To determine whether cold limits the winter development of A. aegypti larvae in Maricopa County, we surveyed for larval abundance and tested their capacity to develop in ambient and warmed conditions. Aedes aegypti larvae were not observed in artificial aquatic habitats in winter and spring but were abundant in summer and fall, suggesting winter suppression of adults, larvae, or both. Water temperatures in winter months fluctuated strongly; larvae were usually cold paralyzed at night but active during the day. Despite daytime temperatures that allowed activity and achieving similar degree-days as warmed mesocosms, larvae reared under ambient winter conditions were unable to develop to adulthood, perhaps due to repetitive cold damage. However, warming average temperature by 1.7°C allowed many larvae to successfully develop to adults. Because daytime highs in winter will often allow adult flight, it is likely that relatively minor additional winter warming may allow A. aegypti populations to develop and reproduce year-round in Maricopa County.

Origins of high latitude introductions of Aedes aegypti to Nebraska and Utah during 2019

Aedes aegypti (L.), the yellow fever mosquito, is also an important vector of dengue and Zika viruses, and an invasive species in North America. Aedes aegypti inhabits tropical and sub-tropical areas of the world and in North America is primarily distributed throughout the southern US states and Mexico. The northern range of Ae. aegypti is limited by cold winter months and establishment in these areas has been mostly unsuccessful. However, frequent introductions of Ae. aegypti to temperate, non-endemic areas during the warmer months can lead to seasonal activity and disease outbreaks. Two Ae. aegypti incursions were reported in the late summer of 2019 into York, Nebraska and Moab, Utah. These states had no history of established populations of this mosquito and no evidence of previous seasonal activity. We genotyped a subset of individuals from each location at 12 microsatellite loci and ~ 14,000 single nucleotide polymorphic markers to determine their genetic affinities to other populations worldwide and investigate their potential source of introduction. Our results support a single origin for each of the introductions from different sources. Aedes aegypti from Utah likely derived from Tucson, Arizona, or a nearby location. Nebraska specimen results were not as conclusive, but point to an origin from southcentral or southeastern US. In addition to an effective, efficient, and sustainable control of invasive mosquitoes, such as Ae. aegypti, identifying the potential routes of introduction will be key to prevent future incursions and assess their potential health threat based on the ability of the source population to transmit a particular virus and its insecticide resistance profile, which may complicate vector control.

A machine-learning approach to map landscape connectivity in Aedes aegypti with genetic and environmental data

Aedes mosquitoes are projected to continue expanding their ranges, which could expose millions more humans to the diseases they carry. The implementation of vector control methods ranging from traditional (e.g., insecticides) to cutting edge (e.g., genetic modification) could be improved with landscape connectivity maps and increased understanding of the factors that affect mosquito dispersal. Here we present an iterative random forest method for integrating genetic and environmental data to map landscape connectivity. We achieve a correlation of 0.83 between the model’s predicted genetic distance and actual genetic distance. We produce a genetic connectivity map for the southern tier of the United States and discuss important factors to consider in mosquito control, e.g., the release of genetically modified mosquitoes.

Mapping landscape connectivity is important for controlling invasive species and disease vectors. Current landscape genetics methods are often constrained by the subjectivity of creating resistance surfaces and the difficulty of working with interacting and correlated environmental variables. To overcome these constraints, we combine the advantages of a machine-learning framework and an iterative optimization process to develop a method for integrating genetic and environmental (e.g., climate, land cover, human infrastructure) data. We validate and demonstrate this method for the Aedes aegypti mosquito, an invasive species and the primary vector of dengue, yellow fever, chikungunya, and Zika. We test two contrasting metrics to approximate genetic distance and find Cavalli-Sforza–Edwards distance (CSE) performs better than linearized F_ST. The correlation (R) between the model’s predicted genetic distance and actual distance is 0.83. We produce a map of genetic connectivity for Ae. aegypti’s range in North America and discuss which environmental and anthropogenic variables are most important for predicting gene flow, especially in the context of vector control.

A Review of the Control of Aedes aegypti (Diptera: Culicidae) in the Continental United States

Aedes aegypti (L) is an anthropophilic mosquito involved in the transmission of a variety of viral pathogens worldwide including dengue, chikungunya, yellow fever, and Zika viruses. This species, native to Africa, is well established in the continental U.S. (CONUS) and occasionally contributes to localized outbreaks of viral diseases. In the last seven decades, mosquito control programs in the CONUS have been focused on vectors of eastern equine encephalitis, St. Louis encephalitis, and West Nile viruses, as well as nuisance species. Aedes aegypti receives little control focus except during outbreak periods, which has led to a lack of information on appropriate and effective control options targeting Ae. aegypti in the CONUS. As such, in the event of an Ae. aegypti-borne arboviral outbreak in the CONUS, there are limited evidence-based control recommendations or protocols in place. Autochthonous outbreaks of Ae. aegypti-borne pathogens have occurred recently in the CONUS, including dengue outbreaks in 2010 and 2013, a chikungunya outbreak in 2014, and the 2016 outbreak of Zika virus. The increasing frequency of Ae. aegypti-borne outbreaks necessitates increased attention and research on control of this species to prevent and mitigate future outbreaks. This review consolidates and synthesizes the available literature on control of Ae. aegypti, specifically within the CONUS, focusing on data generated through operational applications as well as field and semifield experiments. The purpose of this review is to identify and highlight areas where additional research is needed. The review covers chemical control and insecticide resistance, biological control, source reduction, trapping, and alternative techniques.

Establishment of the Invasive Aedes aegypti (Diptera: Culicidae) in the West Valley Area of San Bernardino County, CA

The yellow fever mosquito, Aedes aegypti (Linnaeus, 1762), is the most aggressive invasive mosquito species with worldwide distribution. In addition to being a notorious nuisance species, it can pose significant public health concern because of its ability to transmit various viral pathogens. The first adult capture in the West Valley area of San Bernardino County, CA, occurred in September 2015 in Montclair. A strategic surveillance plan was implemented accordingly by the West Valley Mosquito and Vector Control District to document the infestation. The Biogent Sentinel (BG-2) trap augmented with BG-Lure and carbon dioxide (CO2) was deployed as a routine surveillance tool during 2017-2019. Extensive trapping revealed an expanding infestation, when positive trap nights (TN) increased from 14.2% in 2017 to 23.9% in 2018 and 55.6% in 2019. The average counts/TN increased from 0.65 in 2017 and 0.90 in 2018 to 3.83 in 2019. The cities of Montclair, Chino, and Ontario had much higher infestation than other cities in the district with the highest positive TN of 46.0% in Montclair, and highest average trap count of 3.23/TN in Chino. It was interesting to note that males coincided with females with more profound trend during warmer months of July to October when ratios of males ranged 28.4-35.0%. The BG-2 trap significantly outperformed the CO2 trap and gravid trap. The establishment of this invasive species in semiarid inland Southern California was further confirmed by concurrent larval collections.

Genetic Variation in Insect Vectors: Death of Typology?

The issue of typological versus population thinking in biology is briefly introduced and defined. It is then emphasized how population thinking is most relevant and useful in vector biology. Three points are made: (1) Vectors, as they exist in nature, are genetically very heterogeneous. (2) Four examples of how this is relevant in vector biology research are presented: Understanding variation in vector competence, GWAS, identifying the origin of new introductions of invasive species, and resistance to inbreeding. (3) The existence of high levels of vector genetic heterogeneity can lead to failure of some approaches to vector control, e.g., use of insecticides and release of sterile males (SIT). On the other hand, vector genetic heterogeneity can be harnessed in a vector control program based on selection for refractoriness.