Web GIS in Decision Support to Control Malaria, Case Study in Tiro Afeta Woreda, Oromia Region, Ethiopia
| dc.contributor.advisor | Legesse, Dagnachew (PhD) | |
| dc.contributor.author | Mebratu, Meron | |
| dc.date.accessioned | 2018-07-09T05:49:08Z | |
| dc.date.accessioned | 2023-11-09T14:09:30Z | |
| dc.date.available | 2018-07-09T05:49:08Z | |
| dc.date.available | 2023-11-09T14:09:30Z | |
| dc.date.issued | 2010-06 | |
| dc.description.abstract | Malaria remains a major public health threat killing millions of people every year. Morethan 17 million people are at risk of malaria in Oromia regional state of Ethiopia. Therefore, the objective of this study is aiming at assessing areas prone to malaria, to analyze the incidence of malaria with climatic conditions particularly rainfall in Tiro Afeta Woreda of Oromia. Further, integrating malaria data into a decision support system (DSS) that can provide information within shortest period of time, so that, decision makers get prepared to make better and faster decisions which can reduce the damage and minimize the loss. This paper attempts to asses and produce malaria prone areas maps including the most important natural factors. Further analysis was made regarding malaria incidence and rainfall using remote sensing and geographical information system techniques. Moreover, it was attempted to develop a decision support system (DSS) using the available open source technologies which may help in providing the required information which is more organized and helps in preparing the prevention of the disease. From the study it is indicated that almost all of the study area i.e. 99.78% is prone to malaria mainly due to the natural factors particularly rainfall and altitude. It was also evident that the peak malaria transmission occurred immediately after the rainy season’s, implying the direct relationship between malaria incidence and rainfall. Since the peak malaria transmission coincides with the planting and harvesting season, the socio-economic impact of malaria is very significant. As a result, epidemics detection and preparedness should further be assessed and strengthen. Key words: malaria, epidemic, Remote Sensing, Geographical Information Systems, Decision Support System. | en_US |
| dc.identifier.uri | http://10.90.10.223:4000/handle/123456789/7127 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa Universty | en_US |
| dc.subject | Malaria | en_US |
| dc.subject | Epidemic | en_US |
| dc.subject | Remote Sensing | en_US |
| dc.subject | Geographical Information Systems | en_US |
| dc.subject | Decision Support System | en_US |
| dc.title | Web GIS in Decision Support to Control Malaria, Case Study in Tiro Afeta Woreda, Oromia Region, Ethiopia | en_US |
| dc.type | Thesis | en_US |