Spatio-temporal modelling of dengue fever incidence in Malaysia by Che-Him, Norziha, Kamardan, M. Ghazali, Rusiman, Mohd Saifullah, Sufahani, Suliadi Firdaus, Mohamad, Mahathir, Kamaruddin, Nafisah @ Kamariah

“…The population density is found to be positively related to monthly DIR. …”
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Generalised additive model of DIR based on region, monsoon and state in Peninsular Malaysia by Che Him, Norziha, Yusof, Yusliandy, Samat, Nor Azah

“…A spatio-temporal series of 1296 observations with the following explanatory variables; state, latitude and longitude of state capital, land area of state, year, month, total dengue cases, estimated state population pertaining to the year, population density of state, maximum, minimum and average monthly rainfall, maximum, minimum and average monthly temperature, monthly number of rainy days and Nino 4. …”
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Overview of urban heat island (UHI) phenomenon towards human thermal comfort by Lee, Yee Yong, Md Din, Mohd Fadhil, Ponraj, Mohanadoss, Noor, Zainura Zainon, Kenzo, Iwao, Chelliapan, Shreeshivadasan

“…The impacts of UHI are even getting worse due to large population density with improper building design especially in dense metropolitan cities. …”
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Potential for using climate forecasts in spatio-temporal prediction of dengue fever incidence in Malaysia submitted by Che Him, Norziha

“…The variables that were considered included annual trend, in year seasonal effects, population, population density and lagged dengue incidence rate as well as climate factors such as average rainfall and temperature, number of rainy days, ENSO and lagged values of these climate variables. …”
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Dengue incidence rate clustering by district in Selangor by Che Him, Norziha, Mohamad, Nazeera, Rusiman, Mohd Saifullah, Khalid, Kamil, Shafi, Muhammad Ammar

“…This study identified a pattern for monthly observed dengue count and successfully select variables includes number of rainy days and amount of rainfall with time lags, number of locality and population density which significant to DIR in Selangor. …”

Application FCM in modelling DIR for Selangor using negative binomial GAM by Mohamad, Nazeera, Che Him, Norziha, Rusiman, Mohd Saifullah, Sufahani, Suliadi, Muhammad Jamil, Siti Afiqah

“…The significant variables include amount of rainfall and number of rainy days with lag 0 until 3 months, number of locality and population density. Fuzzy C-Means clustering (FCM) was applied in clustering DIR data based on the value of membership function. …”

A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy C means model a case study in Selangor by Mohamad, Nazeera

“…Meanwhile, non-climatic variables such as population density, number of locality and lag DIR from 1 month until 3 months also show significant relationship towards DIR. …”
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A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor by Mohamad, Nazeera

“…Meanwhile, non-climatic vaiiables such as population density, number of locality and lag DIR from I month until 3 months also show significant relationship towards DIR For both clustering techniques, there are two clusters fonned and there are four new models developed in this study. …”
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Epidemiology trend with particular spatio-temporal distribution of DIR in Malaysia by Jamil, Nur Izzah, Che Him, Norziha, Mohd Hamdan, Siti Fatimah Az-Zahra, Rusiman, Mohd Saifullah

“…Among highest incidence rates were located at four districts; Petaling, Hulu Langat, Klang and Gombak where surrounding federal territory of Kuala Lumpur in the center of the region is on of main interest from high population densities and conclusion has been made that high DIR is strongly increase the risk of dengue incidence in that state.…”
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