The development of stochastic Sir and S(ImIf)R models for heterosexual HIV and AIDS disease mapping in Malaysia (IR)
The purpose of this research is to develop an alternative method of relative risk estimation based on stochastic discrete time-space model. There are two main methods proposed which are stochastic discrete time-space SIR (Susceptible-Infected-Removed) model and S(ImIf)R (Susceptible-[Infected male]-...
Saved in:
| Main Author: | |
|---|---|
| Format: | thesis |
| Language: | eng |
| Published: |
2016
|
| Subjects: | |
| Online Access: | https://ir.upsi.edu.my/detailsg.php?det=2689 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The purpose of this research is to develop an alternative method of relative risk estimation based on stochastic discrete time-space model. There are two main methods proposed which are stochastic discrete time-space SIR (Susceptible-Infected-Removed) model and S(ImIf)R (Susceptible-[Infected male]-[infected female]-Removed) according to gender for HIV and AIDS. Firstly, the deterministic compartmental SIR model that is suitable for the transmission of HIV and AIDS is discussed. This model then is adapted to develop corresponding discrete time-space stochastic SIR model. This is followed by the discussion of the alternative method of relative risk estimation based on the stochastic SIR model. Furthermore, applications of the common methods such as SMR and Poisson-gamma using HIV and AIDS data from Malaysia is also discussed in this thesis and the results are compared in tables, graphs and maps. Subsequently, discussion on modelling of S(ImIf)R model based on gender is discussed in the same regulation of discussion based on SIR in order to identify risk for male and female respectively. Finally, the results of analysis showed that the alternative relative risk estimation method based on the discrete time-space stochastic SIR model and S(ImIf)R according to gender have small number of range for estimating relative risk which has been examined by using goodness-of-fit method compared to the other common approaches. As conclusion, the proposed models are better than to the common methods in estimating of relative risk. However, the SIR model can be used for the analysis of HIV and AIDS generally while S(ImIf)R model is used to analyse relative risk specifically for gender. Besides that, the proposed model also takes into account the transmission process of the disease while allowing spatial adjustment between risks in adjacent areas. The disease risk map in this study can be used as a tool to identify states that need more attention and further action by authorities at the same time to give awareness to society about the risks in the area where they live. Furthermore, this improvement of disease mapping is able to be used as a medical or inquiry tool in any corresponding HIV and AIDS research and development study. |
|---|