Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

Journal: BMJ open

Published Date: Mar 3, 2016

Abstract

OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections correlation with socioeconomic status using geographical information system (GIS) and neural network models.

Authors

Luma Akil

Department of Biology/Environmental Science, Jackson State University, Jackson, Mississippi, USA.
H Anwar Ahmad

Department of Biology/Environmental Science, Jackson State University, Jackson, Mississippi, USA.

Keywords

Disease Outbreaks Foodborne Diseases Geographic Information Systems Humans Mississippi Models, Statistical Neural Networks, Computer Population Surveillance Regression Analysis Salmonella Infections Social Class Socioeconomic Factors

External Resources

View on PubMed Access via DOI PubMed (26940103)

Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

Abstract

Authors

Keywords

External Resources

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