Due to the global increase in mosquito-borne diseases outbreaks it is recommended to increase surveillance and monitoring of vector species to respond swiftly and with early warning indicators. Usually, however, the information about vector presence and activity seems to be insufficient to implement timely and effective control strategies. Here we present an improved mathematical model of Aedes aegypti population dynamics with the aim of making the Dengue surveillance system more proactive. The model considers the four life stages of the mosquito: egg, larva, pupa and adult. As driving factors, it incorporates temperature which affects development and mortality rates at certain stages, and precipitation which is known to affect egg submergence and hatching, as well as larval mortality associated with desiccation. Our mechanistic model is implemented as a free and stand-alone system that automatically retrieves all needed inputs, runs a simulation and shows the results. A major improvement in our implementation is the capacity of the system to predict the population dynamics of Ae. aegypti in the near future, given that it uses gridded weather forecast data. Hence, it is independent by meteorological station proximity. The model predictions are compared with field data from Córdoba City, Argentina. Although field data have high variability, an overall accordance has been observed. The comparison of results obtained using observed weather data, with the simulations based on forecasts, suggests that the modeled dynamics are accurate up to 15 days in advance. Preliminary results of Ae. aegypti population dynamics for a consecutive three-year period, spanning different eco-regions of Argentina, are presented, and demonstrate the flexibility of the system.

由于全球蚊媒疾病爆发的增加，建议加强对媒介物种的监测和监测，以迅速做出反应并提供预警指标。然而，通常有关媒介存在和活动的信息似乎不足以实施及时有效的控制策略。在这里，我们提出了一种改进的埃及伊蚊数学模型人口动态，目的是使登革热监测系统更加主动。该模型考虑了蚊子的四个生命阶段：卵、幼虫、蛹和成虫。作为驱动因素，它包括影响特定阶段发育和死亡率的温度，已知影响鸡蛋浸没和孵化的降水，以及与干燥相关的幼虫死亡率。我们的机械模型是作为一个免费的独立系统实现的，它可以自动检索所有需要的输入、运行模拟并显示结果。我们实施的一个主要改进是系统预测Ae种群动态的能力。埃及在不久的将来，鉴于它使用网格天气预报数据。因此，它与气象站的距离无关。模型预测与阿根廷科尔多瓦市的现场数据进行了比较。尽管现场数据具有高度可变性，但已观察到总体一致。将使用观测天气数据获得的结果与基于预测的模拟进行比较，表明建模的动态最多可提前 15 天准确。Ae 的初步结果。介绍了跨越阿根廷不同生态区的连续三年的埃及人口动态，并展示了该系统的灵活性。