Spatio-temporal modelling of dengue fever incidence in Malaysia
Previous studies reported significant relationship between dengue incidence rate (DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non�climatic factors. The data use...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7033/1/P10153_5e4142f853442708f7293738ac2c4b9a.pdf http://eprints.uthm.edu.my/7033/ https://doi.org/10.1088/1742-6596/995/1/012003 |
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| Institution: | Universiti Tun Hussein Onn Malaysia |
| Language: | English |
| Summary: | Previous studies reported significant relationship between dengue incidence rate
(DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised
additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non�climatic factors. The data used is monthly DIR for 12 states of Malaysia from 2001 to 2009. In
this study, we considered an annual trend, seasonal effects, population, population density and
lagged DIR, rainfall, temperature, number of rainy days and El Niño-Southern Oscillation
(ENSO). The population density is found to be positively related to monthly DIR. There are
generally weak relationships between monthly DIR and climate variables. A negative binomial
GAM shows that there are statistically significant relationships between DIR with climatic and
non-climatic factors. These include mean rainfall and temperature, the number of rainy days, sea
surface temperature and the interaction between mean temperature (lag 1 month) and sea surface
temperature (lag 6 months). These also apply to DIR (lag 3 months) and population density. |
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