Department of Industrial Engineering, Texas A&M University, College Station, USA.
Department of Entomology, Texas A&M University, College Station, USA.
Sci Rep. 2021 Sep 23;11(1):18909. doi: 10.1038/s41598-021-98316-x.
Mosquitoes transmit several infectious diseases that pose significant threat to human health. Temperature along with other environmental factors at breeding and resting locations play a role in the organismal development and abundance of mosquitoes. Accurate analysis of mosquito population dynamics requires information on microclimatic conditions at breeding and resting locations. In this study, we develop a regression model to characterize microclimatic temperature based on ambient environmental conditions. Data were collected by placing sensor loggers at resting and breeding locations such as storm drains across Houston, TX. Corresponding weather data was obtained from National Oceanic and Atmospheric Administration website. Features extracted from these data sources along with contextual information on location were used to develop a Generalized Linear Model for predicting microclimate temperatures. We also analyzed mosquito population dynamics for Aedes albopictus under ambient and microclimatic conditions using system dynamic (SD) modelling to demonstrate the need for accurate microclimatic temperatures in population models. The microclimate prediction model had an R value of ~ 95% and average prediction error of ~ 1.5 °C indicating that microclimate temperatures can be reliably estimated from the ambient environmental conditions. SD model analysis indicates that some microclimates in Texas could result in larger populations of juvenile and adult Aedes albopictus mosquitoes surviving the winter without requiring dormancy.
蚊子传播多种传染病，对人类健康构成重大威胁。繁殖地和栖息地的温度以及其他环境因素在蚊子的生物发育和数量中起着作用。准确分析蚊子种群动态需要了解繁殖地和栖息地的微气候条件。在这项研究中，我们开发了一种回归模型，根据环境条件来描述微气候温度。数据是通过在德克萨斯州休斯顿的雨水井等繁殖地和栖息地放置传感器记录器收集的。相应的天气数据是从美国国家海洋和大气管理局网站获得的。从这些数据源中提取的特征以及有关位置的上下文信息被用于开发广义线性模型，以预测微气候温度。我们还使用系统动力学 (SD) 模型分析了环境和微气候条件下白纹伊蚊的种群动态，以证明在种群模型中需要准确的微气候温度。微气候预测模型的 R 值约为 95%，平均预测误差约为 1.5°C，表明可以从环境条件可靠地估计微气候温度。SD 模型分析表明，德克萨斯州的一些微气候可能导致更多的白纹伊蚊幼虫和成虫在冬季不进入休眠状态也能存活下来。
