INTRODUCTION: Dengue is currently a major public health burden in Asia Pacific Region. This study aims to establish an association between dengue incidence, mean temperature and precipitation, and further discuss how weather predictors influence the increase in intensity and magnitude of dengue in Singapore during the period 2000-2007. MATERIALS and METHODS: Weekly dengue incidence data, daily mean temperature and precipitation and the midyear population data in Singapore during 2000-2007 were retrieved and analysed. We employed a time series Poisson regression model including time factors such as time trends, lagged terms of weather predictors, considered autocorrelation, and accounted for changes in population size by offsetting. RESULTS: The weekly mean temperature and cumulative precipitation were statistically significant related to the increases of dengue incidence in Singapore. Our findings showed that dengue incidence increased linearly at time lag of 5-16 and 5-20 weeks succeeding elevated temperature and precipitation, respectively. However, negative association occurred at lag week 17-20 with low weekly mean temperature as well as lag week 1-4 and 17-20 with low cumulative precipitation. DISCUSSION: As Singapore experienced higher weekly mean temperature and cumulative precipitation in the years 2004-2007, our results signified hazardous impacts of climate factors on the increase in intensity and magnitude of dengue cases. The ongoing global climate change might potentially increase the burden of dengue fever infection in near future.