FUZZY EXPECTED VALUE IN EPIDEMIOLOGY MODEL SI AND SIS
The SI and SIS epidemic models are two models that are well known in epidemiology. Commonly, the disease transmission rate for both models are assumed to be constant. However, in reallity the transmission may depend on amount of pathogen in an infected body. To get insight into this, in this final p...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/27843 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The SI and SIS epidemic models are two models that are well known in epidemiology. Commonly, the disease transmission rate for both models are assumed to be constant. However, in reallity the transmission may depend on amount of pathogen in an infected body. To get insight into this, in this final project the disease transmission rate will be relaxed to contain uncertainty and is considered as fuzzy number. Our main focus will be paid into determination of fuzzy basic reproduction number through fuzzy expected value concept. It turns out that for SI model the endemic, that is represented by a fuzzy basic reproduction number, will occur when the pathogen number exceeds a certain value; as for the the classical SI model the endemic always occurs. While for the SIS models it turns out that a fuzzy basic reproduction number is greater than classical basic reproductionn number. It means that fuzzy SIS model can used as an early warning model for the endemic case. |
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