Spatial prediction of human brucellosis (HB) using a GIS-based adaptive neuro-fuzzy inference system (ANFIS).

Journal: Acta tropica

PMID: 33979640

Abstract

OBJECTIVE: This study pursues three main objectives: 1) exploring the spatial distribution patterns of human brucellosis (HB); 2) identifying parameters affecting the disease spread; and 3) modeling and predicting the spatial distribution of HB cases in 2012-2016 and 2017-2018, respectively, in rural districts of Mazandaran province, Iran.

Authors

Elnaz Babaie

Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran. Electronic address: elnaz.babaie@email.kntu.ac.ir.
Ali Asghar Alesheikh

Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran. Electronic address: alesheikh@kntu.ac.ir.
Mohammad Tabasi

Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran. Electronic address: mtabasi@mail.kntu.ac.ir.

Keywords

Animals Brucellosis Climate Cluster Analysis Fuzzy Logic Geographic Information Systems Humans Incidence Linear Models Models, Statistical Neural Networks, Computer Spatial Analysis

External Resources

View on PubMed Access via DOI PubMed (33979640)

Spatial prediction of human brucellosis (HB) using a GIS-based adaptive neuro-fuzzy inference system (ANFIS).

Abstract

Authors

Keywords

External Resources

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