Martín Mía Elisa, Stein Marina, Sangermano Florencia, Estallo Elizabet Lilia
Instituto de Investigaciones Biológicas y Tecnológicas, FCEFyN, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional de Córdoba, CP 5000, Córdoba, Córdoba, Argentina.
Facultad de Ciencias Exactas, Físicas y Naturales, Centro de Investigaciones Entomológicas de Córdoba, Universidad Nacional de Córdoba, CP 5000, Córdoba, Córdoba, Argentina.
Ecohealth. 2025 Jun 15. doi: 10.1007/s10393-025-01721-1.
Aedes aegypti and Aedes albopictus are the primary vectors of arboviruses in Argentina, with increasing importance in Northeastern Argentina (NEA). This study used ecological niche modeling (MaxEnt) to estimate the potential geographic distribution of both species in NEA, integrating bioclimatic, land cover, and sociodemographic variables such as population density and urban accessibility. Occurrence data were compiled from global databases and literature, and model calibration was based on variable selection, spatial filtering, and cross-validation. Results indicate a broader potential distribution for Ae. albopictus compared to Ae. aegypti, particularly in under-sampled areas of Misiones and Corrientes. Urban accessibility emerged as the most influential predictor for both species, with models combining environmental and sociodemographic variables outperforming climate-only models (AUC > 0.84). Binary habitat suitability maps showed marked differences between models, underscoring the importance of human-driven factors. These findings support the use of integrative modeling approaches to better anticipate vector expansion and prioritize surveillance. The study provides critical information to guide vector control programs and reduce the risk of arbovirus transmission, especially in densely populated and highly connected areas.
埃及伊蚊和白纹伊蚊是阿根廷虫媒病毒的主要传播媒介，在阿根廷东北部（NEA）的重要性日益增加。本研究使用生态位建模（MaxEnt）来估计这两个物种在NEA的潜在地理分布，整合了生物气候、土地覆盖以及人口密度和城市可达性等社会人口统计学变量。出现数据来自全球数据库和文献，模型校准基于变量选择、空间滤波和交叉验证。结果表明，与埃及伊蚊相比，白纹伊蚊的潜在分布范围更广，特别是在米西奥内斯省和科连特斯省采样不足的地区。城市可达性是这两个物种最具影响力的预测因子，结合环境和社会人口统计学变量的模型优于仅考虑气候因素的模型（AUC > 0.84）。二元栖息地适宜性地图显示模型之间存在显著差异，突出了人为驱动因素的重要性。这些发现支持使用综合建模方法来更好地预测病媒扩散并确定监测重点。该研究提供了关键信息，以指导病媒控制计划并降低虫媒病毒传播风险，特别是在人口密集和联系紧密的地区。
