J. Rapp, Matthias Grossler, Melanie Platz, E. Niehaus
{"title":"Development of a mathematical model to estimate negative impacts on human health with the help of risk maps and Fuzzy membership functions","authors":"J. Rapp, Matthias Grossler, Melanie Platz, E. Niehaus","doi":"10.1109/ISTAFRICA.2014.6880595","DOIUrl":null,"url":null,"abstract":"The health situation especially in developing countries must be improved. This is the aim of several governmental and nongovernmental organizations. To improve the health situation it is important to know about the spatial and temporal distribution of a specific risk. The existing risk, e.g. for the outbreak of a disease, can be visualized with risk maps. We developed a mathematical method, with which it is possible to estimate the existing risk at a specific location. Because of the use of Fuzzy Logic it is possible to combine information about the existing risk with other data based on Fuzzy Logic, like the spatial distribution of medical resources. Thus it is possible to take effective countermeasures to improve the health situation.","PeriodicalId":248893,"journal":{"name":"2014 IST-Africa Conference Proceedings","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IST-Africa Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISTAFRICA.2014.6880595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The health situation especially in developing countries must be improved. This is the aim of several governmental and nongovernmental organizations. To improve the health situation it is important to know about the spatial and temporal distribution of a specific risk. The existing risk, e.g. for the outbreak of a disease, can be visualized with risk maps. We developed a mathematical method, with which it is possible to estimate the existing risk at a specific location. Because of the use of Fuzzy Logic it is possible to combine information about the existing risk with other data based on Fuzzy Logic, like the spatial distribution of medical resources. Thus it is possible to take effective countermeasures to improve the health situation.