Predictive model of dengue focus applied to Geographic Information Systems

Dengue is a viral disease transmitted by the aedes aegypti mosquito. In Paraguay - South America, health authorities carry out entomological surveillance activities in order to monitor the vector density in endemic and non-endemic areas through techniques based on the use of traditional index. Currently there are numerous methods and most practical, efficient and economic indicators to determine the populations of aedes aegypti mosquito as larvitraps and ovitraps. The regionalized information obtained from the sampling procedures can be combined with environmental, demographic or epidemiological information in order to obtain detailed models that have the ability to monitor, simulate the behavior of the vector and therefore predict a possible outbreak of dengue. This paper presents the design and implementation of a predictive model to identify outbreaks of dengue vector infestation and the representation of its spread in a geographical information system. The model is implemented as a simulator of the evolutionary process of vector ecology, composed of a set of sub-models that seek to estimate the rate of development, mortality, reproduction and spread of the dengue vector exposed to simulations of climatic variations, where the initial population is generated from data obtained from larvitraps geographically referenced, in order to generate enough alphanumeric and geographical information to contribute to the early detection of potkential disease outbreaks.