Prediction model of Japanese encephalitis cases using satellite remotely sensed data and its application to climate change impact assessment in Thailand | |
| Author | Suwannee Adsavakulchai |
| Call Number | AIT Diss. no. SR-00-3 |
| Subject(s) | Japanese B encephalitis--Thailand Climatic changes--Thailand Remote sensing--Thailand |
| Note | A dissertation submitted in the partial fulfillment of the requirements for the degree of Doctor of Technical Science., School of Advanced Technologies |
| Publisher | Asian Institute of Technology |
| Abstract | Japanese encephalitis (JE) is one of the mosquito-borne viral diseases that is serious . infection transmitted by Cu/ex tritaeniorhynchus. In Thailand, JE remains a public health problem dues to its high fatality rate. The environmental interactions are important in the various effects of temperature and rainfall. To tackle with problems on JE, it is needed to develop a model which can predict JE case as a function of these environmental factors. The main objectives of this study are to develop JE model as a function of environmental factors such as rainfall, temperature, number of mosquito, area of rice field using remote sensing as a tool for explaining the relationships . between number of JE case and the changing of environment conditions, and to assess the impact of possible climate change on JE cases in Thailand. Two JE 'models have been developed in this study based on multiple regress~on analysis. One is in Chiangrai Province and the other is in Th~iland. The accuracy (R 2 ) of these models are 0.902 (p < 0.05) and 0.692 (p < 0.05) respectively in 1992-1993. Remote sensing data from NOA.A AVHRR is introduced to identify rice fields to make it possible to predict JE cases at near real time in Thailand. Climate change scenarios were simulated by JE model in Thailand. The scenarios are ±1°C and ±2°C change in average monthly temperature, and ±10% and ±20% change in average monthly rainfall. A rise in temperatures decreased the number of JE cases 0.4-14.2%. In contrast, a decrease in temperatures increased the number of JE cases 0.3-14.6%. A rise both in rainfall of 10% and 20% increase the number of JE cases 2.2-5.0%. In.contrast, a decrease both in rainfall of 10% and 20% decr~ase the number of JE cases 2.2-4.6%. Furthermore, the models are meant to contribute to the ongoing . discussion and development of methods in the analyses of climate change, ecosystems and health relationships. |
| Year | 2000 |
| Type | Dissertation |
| School | School of Advanced Technologies (SAT) |
| Department | Department of Information and Communications Technologies (DICT) |
| Chairperson(s) | Honda, Kiyoshi |
| Examination Committee(s) | Kaew Nualchawee;Murai, Shunji;Athapol Noomhorm;Bishop, Ian David |
| Scholarship Donor(s) | Royal Thai Government |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2000 |