The evaluation of stochastic mosquito-borne infectious disease mapping model in Malaysia (IR)
The main aim of this research is to propose an alternative method for estimating relative risk of mosquito-borne infectious disease mapping in Malaysia. This estimation method is based on stochastic SIR-SI model (susceptible-infectiverecovered for human populations; susceptible-infective for mosquit...
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Format: | thesis |
Language: | eng |
Published: |
2016
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Subjects: | |
Online Access: | https://ir.upsi.edu.my/detailsg.php?det=1281 |
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Summary: | The main aim of this research is to propose an alternative method for estimating relative risk of mosquito-borne infectious disease mapping in Malaysia. This estimation method is based on stochastic SIR-SI model (susceptible-infectiverecovered for human populations; susceptible-infective for mosquito populations). Based on previous research, relative risk estimation used total number of new infective cases at the denominator of the relative risk equation. In this research, relative risk estimation with the used of total posterior mean number of new infective cases at the denominator of the relative risk equation is introduced. This model is then been applied using data of mosquito-borne infectious disease from Malaysia. Data used in this research is provided by the Ministry of Health Malaysia which include 43339 dengue cases, 7 chikungunya cases and 3850 malaria cases for 16 states in Malaysia during year 2013. The findings revealed that the alternative method can overcome the problem of relative risk estimation, especially when there is no observed cases in certain regions. This is because this model considers spatial correlation between adjacent areas, takes into account the disease transmission model, as well as enable covariates adjustment which are known will contribute to the increasing number of disease cases. Pattern displayed on disease risk map proposed in this research can be used as reference by the authorities in preventing and reducing the cases of dengue, chikungunya and malaria in Malaysia. |
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