The Impact of Administrative Districts and Urban Landscape on the Dispersal of Aedes aegypti via Genetic Differentiation

Mol Ecol. 2025 Jan 7:e17644. doi: 10.1111/mec.17644. Online ahead of print.

Abstract

Mosquito-borne diseases affect millions and cause numerous deaths annually. Effective vector control, which hinges on understanding their dispersal, is vital for reducing infection rates. Given the variability in study results, likely due to environmental and human factors, gathering local dispersal data is critical for targeted disease control. To analyse the spread and differentiation of Aedes aegypti in southern Taiwan, we established a dengue vector monitoring network in Southern Taiwan's cities. This network employed GPS-equipped ovitraps to gather eggs that were subsequently hatched in the laboratory and genotyped using genome-wide SNP markers. From 168 individuals, we identified 757,238 SNPs for detailed analysis. The estimated effective dispersal distance was 154 m (95% CI: 126-180 m), consistent with prior mark-release-recapture (MRR) estimates. We discovered that geographic isolation significantly influences genetic differentiation at larger scales, such as between cities, whereas its correlation with genetic distances is considerably weaker at smaller scales, like within cities. This is likely due to the urban landscape in Taiwan, characterised by narrow roads and densely packed buildings, which facilitates extensive dispersal of Ae. aegypti. In evaluating potential barriers to Ae. aegypti dispersal, we found that roads had no significant impact, whereas administrative districts accounted for 4.8% of the population differentiation (p < 10-4). Surprisingly, this variation aligns with the effects of district-specific mosquito control measures implemented at the municipal level. These findings highlight the complex interplay between urban landscapes, administrative measures and Ae. aegypti dispersal, emphasising the need for implementing targeted control strategies that consider these local dynamics.

Keywords: Mantel test; dispersal barriers; kinship analysis; landscape genomics; population structure.