Gavin cholera risk prediction

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Information about Gavin cholera risk prediction

Published on September 4, 2007

Author: Tarzen


Fuzzy Expert Systems and GIS for Cholera Health Risk Prediction in Southern Africa :  Fuzzy Expert Systems and GIS for Cholera Health Risk Prediction in Southern Africa Gavin Fleming, Marna van der Merwe, Graeme McFerren, Kerry Murphy CSIR, South Africa Vibrio cholerae:  Vibrio cholerae Untreated: death within 24h from loss of fluid Transmission: ingest contaminated material Treatment: fluid replacement and antibiotics Origins in the Orient Now endemic in many places Disaster: Cholera epidemics:  Disaster: Cholera epidemics Frequent South Africa 2000-2002 andgt;115000 cases 260 deaths Prevention and mitigation:  Prevention and mitigation Interventions Water supply and sanitation Poverty reduction Education Treatment New Disaster Management Act Department of Health Department of Water Affairs The problem…:  The problem… Response is not well directed Scarce resources are wasted History of response, not mitigation Often too late Risk assessment and forecasting Premise:  Premise Integrate understanding of cholera biology human factors Improve accuracy and reduce uncertainly of predictions The complex nature of cholera:  The complex nature of cholera Hierarchical approach:  Hierarchical approach Slide9:  Simulation model - Stella:  Simulation model - Stella Expert systems:  Expert systems Bayesian networks Facilitated expert workshop Erdas Imagine Knowledge Engineer Codify final set of rules from Bayesian networks and simulation model Slide12:  GIS and Fuzzy LogicArcInfo: raster, AML:  GIS and Fuzzy Logic ArcInfo: raster, AML Model variables:  Model variables Slide15:  Conclusions:  Conclusions An integrative approach is effective for modelling complex problems Non-linear simulation modelling Expert systems AI integration (fuzzy logic) We have established a framework and working model Taking it further:  Taking it further Funding to collect missing data Several proposals submitted Develop predictive capability – now mainly risk assessment Improve algal bloom (cholera) prediction Consider other factors Red tide events in Mozambique channel La niña, el nio Develop and integrate social model Slide18: 

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