Biology subjects

McCall, P. J.

Publications and source records attributed to McCall, P. J..

5 recordsLinked to original sources

bioRxiv2024

Three years of insecticide resistance evolution and associated mechanisms in Aedes aegypti populations of Ouagadougou, Burkina Faso.

BackgroundResistance to insecticides is spreading among populations of Aedes aegypti, the primary vector of important human arboviruses. The escalating insecticide resistance poses a significant threat to dengue vector control, with an expanding number of countries affected by the disease. To gain a deeper insight into the evolution of insecticide resistance, it is essential to have longitudinal surveillance results, which are currently lacking, particularly from African Ae. aegypti populations. Here we report on three-years of surveillance of Ae. aegypti susceptibility to insecticide resistance phenotypes and associated kdr mutations in Burkina Faso, a country with regular dengue outbreaks. MethodsAe. aegypti susceptibility to insecticides and the V410L, V1016I, and F1534C kdr target site mutations linked to pyrethroid insecticide resistance were monitored in Ouagadougou from 2016 to 2018. Larvae were collected from artificial containers at two sites and reared to adulthood in an insectary. Bioassays were conducted on female adults, alongside with a laboratory-susceptible strain, following standard WHO protocols. Allele-specific PCR genotyping assays were utilized to identify the V410L, V1016I, and F1534C kdr pyrethroid target site mutations. ResultsBioassays revealed a high level of resistance to permethrin and deltamethrin that progressively increased over the three-year period in both localities. The 1534C mutation was nearly fixed throughout the three years at each locality, and while the closely related 410L and 1016I mutations did not vary between localities, their frequency notably increased from 2016 to 2018. Interestingly, Ae. aegypti populations in both areas remained susceptible to bendiocarb, fenitrothion, and malathion. Modeling the mortality data further confirmed the escalating resistance trend over the years and emphasized the significant role played by the three kdr mutations in conferring resistance to pyrethroids. ConclusionMortality rates indicate that Ae. aegypti populations from Ouagadougou are becoming increasingly resistant to pyrethroid insecticides, likely due to an increase in the frequencies of the 410L and 1016I kdr mutations. Organophosphate insecticides are likely to be better alternative options for control.

evolutionary biology↗

bioRxiv2022

Behaviour of pyrethroid-resistant Anopheles gambiae at the interface of two dual active-ingredient bed nets, assessed by room-scale infrared video tracking

BackgroundThe success of Insecticide Treated Bednets (ITNs) for malaria vector control in Africa relies on the behaviour of the major malaria vectors, Anopheles species. Research into mosquito behavioural traits influencing the performance of ITNs has focused largely on time or location of biting. Here we investigated less tractable behaviours including timings of net contact, willingness to refeed and longevity post exposure to two next-generation nets, PermaNet(R) 3.0 (P3) and Interceptor(R) G2 (IG2) in comparison with a standard pyrethroid only net (Olyset (OL)) and an untreated net. MethodsSusceptible and resistant Anopheles gambiae mosquitoes were exposed to the nets with a human volunteer host in a room scale assay. Mosquito movements were tracked for two hours using an infrared video system, collecting flight trajectory, spatial position and net contact data. Post-assay, mosquitoes were monitored for a range of sublethal insecticide effects. ResultsOL, P3 and IG2 all killed over 90% of susceptible mosquitoes 24 hours after exposure, but this effect was not seen with resistant mosquitoes where mortality ranged from 16% to 72%. Total mosquito activity was higher around untreated nets than ITNs. There was no difference in total activity, the number, or duration, of net contact, between any mosquito strain, with similar behaviours recorded in susceptible and resistant strains at all ITNs. Net contact was focussed predominantly on the roof for all bednets. We observed a steep decay in activity for both susceptible strains when P3 and OL were present and with IG2 for one of the two susceptible strains. All treated nets reduced the willingness of resistant strains to re-feed when offered blood one-hour post-exposure, with a more pronounced effect seen with P3 and OL than IG2. ConclusionResults indicate that the effects of ITNs on mosquito behaviour are consistent, with no major differences in responses between strains of different pyrethroid susceptibility.

animal behavior and cognition↗

bioRxiv2021

Flying In-formation: A computational method for the classification of host seeking mosquito flight patterns using path segmentation and unsupervised machine learning

The rational design of effective vector control tools requires detailed knowledge of vector behaviour. Yet, behavioural observations, interpretations, evaluations and definitions by even the most experienced researcher are constrained by subjectivity and perceptual limits. Seeking an objective alternative to expertise, we developed and tested an unsupervised method for the automatic identification of video-tracked mosquito flight behaviour. This method unites path-segmentation and unsupervised machine learning in an innovative workflow and is implemented using a combination of R and python. The workflow (1) records movement trajectories; (2) applies path-segmentation; (3) clusters path segments using unsupervised learning; and (4) interprets results. Analysis of the flight patterns of An. gambiae s.s., responding to human-baited insecticide-treated bednets (ITNs), by the new method identified four distinct behaviour modes: with swooping and approaching modes predominant at ITNs; increased walking behaviours at untreated nets; similar rates of reacting at both nets; and higher overall activity at treated nets. The methods validity was tested by comparing these findings with those from a similar setting using an expertise-based method. The level of correspondence found between the studies validated the accuracy of the new method. While researcher-defined behaviours are inherently subjective, and prone to corollary shortcomings, the new approachs mathematical method is objective, automatic, repeatable and a validated alternative for analysing complex vector behaviour. This method provides a novel and adaptable analytical tool and is freely available to vector biologists, ethologists and behavioural ecologists. Author summaryVector control targets the insects and arachnids that transmit 1 in every 6 communicable diseases worldwide. Since the effectiveness of many vector control tools depends on exploiting or changing vector behaviour, a firm understanding of this behaviour is required to maximise the impact of existing tools and design new interventions. However, current methods for identifying such behaviours are based primarily on expert knowledge, which can be inefficient, difficult to scale and limited by perceptual abilities. To overcome this, we present, detail and validate a new method for categorising vector behaviour. This method combines existing path segmentation and unsupervised machine learning algorithms to identify changes in vector movement trajectories and classify behaviours. The accuracy of the new method is demonstrated by replicating existing, expert-derived, findings covering the behaviour of host-seeking mosquitos around insecticide treated bednets, compared to nets without insecticide. As the method found the same changes in mosquito activity as previous research, it is said to be validated. The new method is significant, as it improves the analytical capabilities of biologists working to reduce the burden of vector-borne diseases, such as malaria, through an understanding of behaviour.

animal behavior and cognition↗

bioRxiv2020

A minimal 3D model of mosquito flight behavior around the human baited bed net

Advances in digitized video-tracking and behavioral analysis have enabled accurate recording and quantification of mosquito flight and host-seeking behaviors, enabling development of Individual (agent) Based Models at much finer spatial scales than previously possible. We used such quantified behavioral parameters to create a novel virtual testing model, capable of accurately simulating indoor flight behavior by a virtual population of host-seeking mosquitoes as it interacts with and responds to simulated stimuli from a human-occupied bed net. We describe the model, including base mosquito behavior, state transitions, environmental representation and host stimulus representation. In the absence of a bed net and human bait, flight distribution of the model population is relatively uniform in the arena. Introducing an unbaited net induces a change in distribution due to landing events on the net surface, predominantly occurring on the sides and edges of the net. Presence of simulated human baited net strongly impacted flight distribution patterns, exploratory foraging, the number and distribution of net landing sites, depending on the bait orientation. As recorded in live mosquito experiments, contact with baited nets (a measure of exposure to the lethal insecticide) occurred predominantly on the top surface of the net. Number of net contacts and height of contacts decreased with increasing attractant dispersal noise. Results generated by the model are an accurate representation of actual mosquito behavior recorded at and around a human-occupied bed net in untreated and insecticide treated nets. In addition to providing insights into host-seeking behavior of endophilic vectors, this fine-grained model is highly flexible and has significant potential for in silico screening of novel bed net designs, accelerating the deployment of new and more effective tools for protecting against malaria in sub-Saharan Africa.

animal behavior and cognition↗

bioRxiv2019

Diffuse retro-reflective imaging for improved mosquito tracking around human baited bednets

Robust imaging techniques for tracking insects have been essential tools in numerous laboratory and field studies on pests, beneficial insects and model systems. Recent innovations in optical imaging systems and associated signal processing have enabled detailed characterisation of nocturnal mosquito behaviour around bednets and improvements in bednet design, a global essential for protecting populations against malaria. Nonetheless, there remain challenges around ease of use for large scale in situ recordings and extracting data reliably in the critical areas of the bednet where the optical signal is attenuated. Here we introduce a retro-reflective screen at the back of the measurement volume, which can simultaneously provide diffuse illumination, and remove optical alignment issues whilst requiring only one-sided access to the measurement space. The illumination becomes significantly more uniform, although, noise removal algorithms are needed to reduce the effects of shot noise particularly across low intensity bednet regions. By systematically introducing mosquitoes in front and behind the bednet in lab experiments we are able to demonstrate robust tracking in these challenging areas. Overall, the retro-reflective imaging setup delivers mosquito segmentation rates in excess of 90% compared to less than 70% with back-lit systems.

animal behavior and cognition↗