Optimal control for disease vector management in SIT models: an integrodifference equation approach

Kura, Klodeta; Khamis, Doran; Mouden, Claire El; Bonsall, Michael B.

doi:10.1007/s00285-019-01327-6

Cited by 13 publications

(7 citation statements)

References 34 publications

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“…The theoretical approximation of the conditions for Wolbachia -based mosquito replacement [ 47 ] and simulation modeling of this and other mosquito control strategies [ 10 , 55 – 58 ] have all been developed assuming isotropic dispersal (invariable based on direction) in a 2-dimensional landscape. The approximation of the dispersal kernel for high-rise uniform landscapes could be achieved by considering the releases of mosquitoes from multiple floors rather than from the ground level only.…”

Section: Discussionmentioning

confidence: 99%

Using spatial genetics to quantify mosquito dispersal for control programs

et al. 2020

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Background Hundreds of millions of people get a mosquito-borne disease every year and nearly one million die. Transmission of these infections is primarily tackled through the control of mosquito vectors. The accurate quantification of mosquito dispersal is critical for the design and optimization of vector control programs, yet the measurement of dispersal using traditional mark-release-recapture (MRR) methods is logistically challenging and often unrepresentative of an insect’s true behavior. Using Aedes aegypti (a major arboviral vector) as a model and two study sites in Singapore, we show how mosquito dispersal can be characterized by the spatial analyses of genetic relatedness among individuals sampled over a short time span without interruption of their natural behaviors. Results Using simple oviposition traps, we captured adult female Ae. aegypti across high-rise apartment blocks and genotyped them using genome-wide SNP markers. We developed a methodology that produces a dispersal kernel for distance which results from one generation of successful breeding (effective dispersal), using the distance separating full siblings and 2nd- and 3rd-degree relatives (close kin). The estimated dispersal distance kernel was exponential (Laplacian), with a mean dispersal distance (and dispersal kernel spread σ) of 45.2 m (95% CI 39.7–51.3 m), and 10% probability of a dispersal > 100 m (95% CI 92–117 m). Our genetically derived estimates matched the parametrized dispersal kernels from previous MRR experiments. If few close kin are captured, a conventional genetic isolation-by-distance analysis can be used, as it can produce σ estimates congruent with the close-kin method if effective population density is accurately estimated. Genetic patch size, estimated by spatial autocorrelation analysis, reflects the spatial extent of the dispersal kernel “tail” that influences, for example, the critical radii of release zones and the speed of Wolbachia spread in mosquito replacement programs. Conclusions We demonstrate that spatial genetics can provide a robust characterization of mosquito dispersal. With the decreasing cost of next-generation sequencing, the production of spatial genetic data is increasingly accessible. Given the challenges of conventional MRR methods, and the importance of quantified dispersal in operational vector control decisions, we recommend genetic-based dispersal characterization as the more desirable means of parameterization.

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Section: Discussionmentioning

confidence: 99%

Using spatial genetics to quantify mosquito dispersal for control programs

et al. 2020

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“…The above mentioned theoretical approximation of the conditions for Wolbachia initiation and spread [61] assumes isotropic dispersal in a 2-dimensional habitat. Optimal release strategy for the Sterile Insect Technique programs [62], different suppression and replacement strategies [63,64], the effect of larval habitat fragmentation on population crash [65], and confinement and reversibility conditions for threshold-dependent gene drive systems [10] have all been simulated in the spatially explicit models of mosquito populations that applied the exponential dispersal kernel in a 2-dimensional landscape. The approximation of the parametrized dispersal kernel for high-rise landscapes could be achieved by considering the releases of mosquitoes from multiple floors rather than from the ground level only.…”

Section: Discussionmentioning

confidence: 99%

Using spatial genetics to quantify mosquito dispersal for control programs

Filipović

Hapuarachchi

Tien

et al. 2020

Preprint

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Background: Hundreds of millions of people get a mosquito-borne disease every year, of which nearly one million die. Mosquito-borne diseases are primarily controlled and mitigated through the control of mosquito vectors. Accurately quantified mosquito dispersal in a given landscape is critical for the design and optimization of the control programs, yet the field experiments that measure dispersal of mosquitoes recaptured at certain distances from the release point (markrelease-recapture MRR studies) are challenging for such small insects and often unrepresentative of the insect's true field behavior. Using Singapore as a study site, we show how mosquito dispersal patterns can be characterized from the spatial analyses of genetic relatedness among individuals sampled over a short time span without interruption of their natural behaviors. Methods and Findings:We captured ovipositing females of Aedes aegypti, a major arboviral disease vector, across floors of high-rise apartment blocks and genotyped them using thousands of genome-wide SNP markers. We developed a methodology that produces a dispersal kernel for distance that results from one generation of successful breeding (effective dispersal), using the distances separating full siblings, 2 nd and 3 rd degree relatives (close kin). In Singapore, the estimated dispersal distance kernel was exponential (Laplacian), giving the mean effective dispersal distance (and dispersal kernel spread σ) of 45.2 m (95%CI: 39.7-51.3 m), and 10% probability of dispersal >100 m (95%CI: 92-117 m). Our genetic-based estimates matched the parametrized dispersal kernels from the previously reported MRR experiments. If few close-kin are captured, a conventional genetic isolation-by-distance analysis can be used, and we show that it can produce σ estimates congruent with the close-kin method, conditioned on the accurate estimation of effective population density. We also show that genetic patch size, estimated with the spatial autocorrelation analysis, reflects the spatial extent of the dispersal kernel 'tail' that influences e.g. predictions of critical radii of release zones and Wolbachia wave speed in mosquito replacement programs. Conclusions:We demonstrate that spatial genetics (the newly developed close-kin analysis, and conventional IBD and spatial autocorrelation analyses) can provide a detailed and robust characterization of mosquito dispersal that can guide operational vector control decisions. With the decreasing cost of next generation sequencing, acquisition of spatial genetic data will become increasingly accessible, and given the complexities and criticisms of conventional MRR methods, but the central role of dispersal measures in vector control programs, we recommend genetic-based dispersal characterization as the more desirable means of parameterization.

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“…Zhou and Kot, 2011) and invasive species control (e.g. Kura et al, 2019). All rely on a dispersal kernel to relate movement from one location to another (e.g.…”

Section: Discussionmentioning

confidence: 99%

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

Ahmed

Benhamou

Bonsall

et al. 2020

Preprint

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Background: Random walks (RWs) have proved to be a powerful modelling tool in ecology, particularly in the study of animal movement. An application of RW concerns trapping which is the predominant sampling method to date in insect ecology, invasive species, and agricultural pest management. A lot of research effort has been directed towards modelling ground-dwelling insects by simulating their movement in 2D, and computing pitfall trap counts, but comparatively very little for flying insects with 3D elevated traps. Methods: We introduce the mathematics behind 3D RWs and present key metrics such as the mean squared displacement (MSD) and path sinuosity, which are already well known in 2D. We develop the mathematical theory behind the 3D correlated random walk (CRW) which involves short-term directional persistence and the 3D Biased random walk (BRW) which introduces a long-term directional bias in the movement so that there is an overall preferred movement direction. In this study, we consider three types of shape of 3D traps, which are commonly used in ecological field studies; a spheroidal trap, a cylindrical trap and a rectangular cuboidal trap. By simulating movement in 3D space, we investigated the effect of 3D trap shapes and sizes and of movement diffusion on trapping efficiency. Results: We found that there is a non-linear dependence of trap counts on the trap surface area or volume, but the effect of volume appeared to be a simple consequence of changes in area. Nevertheless, there is a slight but clear hierarchy of trap shapes in terms of capture efficiency, with the spheroidal trap retaining more counts than a cylinder, followed by the cuboidal type for a given area. We also showed that there is no effect of short-term persistence when diffusion is kept constant, but trap counts significantly decrease with increasing diffusion . Conclusion: Our results provide a better understanding of the interplay between the movement pattern, trap geometry and impacts on trapping efficiency, which leads to improved trap count interpretations, and more broadly, has implications for spatial ecology and population dynamics.

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Optimal control for disease vector management in SIT models: an integrodifference equation approach

Cited by 13 publications

References 34 publications

Using spatial genetics to quantify mosquito dispersal for control programs

Using spatial genetics to quantify mosquito dispersal for control programs

Using spatial genetics to quantify mosquito dispersal for control programs

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

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