Modelling hand, foot and mouth disease in Malaysia using generalized linear models
HFMD is an infection which caused by a group of enteroviruses, both Coxsackievirus A16(CA16) and Enterovirus-71(EV71) are the two major pathogens of this disease. People at all ages exposed to HFMD but children of age 5 years and younger is the riskiest group because they have no immunity to the vir...
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/102418/1/TayHuiShienMFS2019.pdf.pdf |
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| Summary: | HFMD is an infection which caused by a group of enteroviruses, both Coxsackievirus A16(CA16) and Enterovirus-71(EV71) are the two major pathogens of this disease. People at all ages exposed to HFMD but children of age 5 years and younger is the riskiest group because they have no immunity to the viruses yet. The disease causes children fever, malaise, poor appetite and ulcers in the mouth. There is no specific treatment for HFMD, the general treatment is to cure fever and treat the ulcers to reduce the pains. HFMD is an endemic in Malaysia but this disease is not extensively studied in Malaysia. Several researches focus on the pathological and diagnostic aspects of HFMD but there is a lack of research in studying the interaction between HFMD and weather in Malaysia. Although HFMD incidences were being notified continuously and HFMD outbreak occurred few years repeatedly in Malaysia, the study regarding HFMD is limited and not much information can be obtained. Hence, this research aims to model the association between HFMD incidences and climate in Selangor using Generalized Linear Models. Descriptive analysis, Mann Kendall trend test, Pearson correlation coefficient, Poisson regression and Negative Binomial regression modelling were applied in this study in order to achieve the research objectives. Then, the best model was selected by comparing the values of AIC and underwent model adequacy test. The finding showed that the number of HFMD incidences was related positively to temperature and cumulative rainfall. Specifically, the modelling demonstrated that increase in mean temperature increase the risk of HFMD infection and the higher weekly cumulative rainfall corresponded to higher weekly HFMD cases. From the finding of this study, authority can set up a proper warning system on the possible HFMD outbreak to community when there is an increase in rainfall and temperature. With this information, HFMD transmission could potentially be monitored and hence the HFMD infection can be prevented and reduced. This study is useful for government to increase the public awareness and give a global warning which possibly to reduce the infection cases. |
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