Urban Landscape Features Influence the Movement and Distribution of the Australian Container-Inhabiting Mosquito Vectors Aedes aegypti (Diptera: Culicidae) and Aedes notoscriptus (Diptera: Culicidae)

Trewin, Brendan J; Pagendam, Dan; Zalucki, Myron P.; Darbro, Jonathan M.; Devine, Gregor J.; Jansen, Cassie C.; Schellhorn, Nancy A.

doi:10.1093/jme/tjz187

Cited by 19 publications

(64 citation statements)

References 38 publications

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“…Location of the recaptured marked insects relative to their release point is typically used to estimate the mean distance traveled (MDT), and the distance within which 50% or 90% of mosquitoes are expected to disperse (FR50 and FR90, respectively). Fewer MRR studies have incorporated the dispersal kernel theory to estimate the distribution of dispersal distances over the whole flight range [ 7 , 15 , 16 ]. MRR experiments in Ae.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%

Using spatial genetics to quantify mosquito dispersal for control programs

et al. 2020

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“…Location of the recaptured marked insects relative to their release point is typically used to estimate the mean distance travelled (MDT), and the distance within which 50% or 90% of mosquitoes are expected to disperse (FR50 and FR90, respectively). Fewer MRR studies have incorporated the dispersal kernel theory to estimate the distribution of dispersal distances over the whole flight range [7,15,16]. MRR experiments in Ae.…”

Section: Introductionmentioning

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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“…The comprehension of the shaping patterns of immature Aedes mosquito ecology along the urbanisation gradient in relation to changes in climatic conditions is of paramount importance in determining their role in maintenance of epidemic arboviral diseases transmission. Studies carried out in southeastern Côte d'Ivoire [24], Texas [25], Buenos Aires [26] and Australia [27], it was possible to identify a spatio-temporal dynamics of Aedes aegypti using ovitraps.…”

Section: Introductionmentioning

confidence: 99%

Spatio‐temporal dynamics of Aedes aegypti and Aedes albopictus oviposition in an urban area of northeastern Brazil

Moura¹,

Oliveira²,

Pedreira³

et al. 2020

Tropical Med Int Health

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objective The objective of this study was to analyse abundance and spatial distribution of Aedes aegypti and Aedes albopictus oviposition in the city of Natal-RN, 2016 to 2018. methods Three hundred and seven oviposition traps were installed covered the whole city and were monitored weekly from January 2016 to December 2018. To verify the abundance of the vector based on its location, the formation of oviposition clusters was studied using the Kernel statistics. Egg Density Index (EDI) and Oviposition Positivity Index (OPI) values were calculated. results Temperature and humidity presented weak and very weak correlation, respectively, with the oviposition indicators. The median of oviposition positivity index (OPI) was 60.5%, and the egg density index (EDI) was 45.4 eggs/trap. The OPI (71.1%) was higher in the second quarter of the year. The areas with the most persistent oviposition are located in a continuous strip that extends from the extreme of the northern district and extends along the western district of the city. Also noteworthy is the proximity to the strategic points. conclusion The spatio-temporal distribution of oviposition revealed that there is spatial segregation and marked seasonality. Therefore, this study highlights the importance of maintaining surveillance targeting and control strategies focused on these areas, especially during the most important period of the year.

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Urban Landscape Features Influence the Movement and Distribution of the Australian Container-Inhabiting Mosquito Vectors Aedes aegypti (Diptera: Culicidae) and Aedes notoscriptus (Diptera: Culicidae)

Cited by 19 publications

References 38 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

Spatio‐temporal dynamics of Aedes aegypti and Aedes albopictus oviposition in an urban area of northeastern Brazil

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