The application of fuzzy sets and fuzzy logic to analyse the habitat quality of mosquito vectors
Jörg Rapp (Pres.), Engelbert Niehaus
University of Koblenz-Landau
Mosquitoes can act as vectors for diseases like malaria or dengue fever. A spatial and temporal relationship between the existence of a vector and the outbreak of the disease, transmitted by the vector, can be observed. To initiate appropriate countermeasures against the disease, like vector control, it is necessary to have information about the temporal and spatial distribution of the vector. In general, every species has its one ecological niche and prefers characteristic biotic and abiotic environmental conditions in their habitats. With data about the temporal and spatial distribution of the mentioned parameters describing the ecological niche of a species or vector it is possible to generate data and maps, representing the spatial quality of a location for a given parameter and vector.
In the following talk a method is presented, describing how the spatial breeding quality related to the daily mean temperature can be evaluated with open source software tools. A breeding quality function in relation to the mean temperature is developed by interpolation. In the next step the breeding quality function is combined with spatial and temporal data about the daily mean temperature. The maps are generated in a way, that they can be logically combined with data describing other relevant habitat parameters. Through the logical connection with fuzzy rules it is possible to evaluate the temporal and spatial distribution of areas suitable as habitat for a given vector.
In the following talk a method is presented, describing how the spatial breeding quality related to the daily mean temperature can be evaluated with open source software tools. A breeding quality function in relation to the mean temperature is developed by interpolation. In the next step the breeding quality function is combined with spatial and temporal data about the daily mean temperature. The maps are generated in a way, that they can be logically combined with data describing other relevant habitat parameters. Through the logical connection with fuzzy rules it is possible to evaluate the temporal and spatial distribution of areas suitable as habitat for a given vector.
