logging in or signing up Gavin cholera risk prediction Tarzen Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 362 Category: News & Reports.. License: All Rights Reserved Like it (0) Dislike it (0) Added: September 04, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript 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: You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
Gavin cholera risk prediction Tarzen Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 362 Category: News & Reports.. License: All Rights Reserved Like it (0) Dislike it (0) Added: September 04, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript 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: