Background Leptospirosis is a zoonotic disease caused by spirochete bacteria in the genus Leptospira, and it has become a significant public health challenge in Malaysia. Environmental survival and persistence of this pathogen are highly dependent on environmental conditions such as moisture content, pH and temperature. These conditions are further adapted by the natural climate system including precipitation and humidity which is highly heterogeneous at a geographical scale. This paper described the spatial and temporal distribution of leptospirosis incidence with climate factors using Geographical Information System and stratified the climate factors based on their association with the disease incidence rate. Methods Leptospirosis surveillance data from 2012-2016 were integrated into this study along with seven geo-spatial climate variables for the state of Sarawak, Malaysia. High and low clustering of incidence rate was explored by Getis Ord Gi* statistics. Geographical Weighted Regression model was utilized to study the relationship between the incidence rate and selected climate variables. Results Spatial analysis revealed seven districts in the state of Sarawak as hot spot areas, and six cold spot areas with GiZ score varies between (-3.092 to 3.203). The cumulative incidence rate demonstrated an increasing trend towards the South-East region of Sarawak with an average of 162 cases per 100,000 population. The univariate analysis reported a significant relationship (p<0.05) between leptospirosis incidence rate and temperature seasonality with the lowest AIC value of 31741.4. The results showed that temperature seasonality explained 99% (R2: 0.99) of the spatial variances in incidence rate with 42.31% of the localities showing a significant positive relationship. Conclusion The present study highlighted the importance of temperature seasonality as a potential determinant for the spatial distribution of leptospirosis cases with different strength and direction of the association. In conclusion, this suggests that specific interventions at a locality with strong climate determinants should be implemented to combat the burden of leptospirosis.

Dengue is a major mosquito-borne disease in many tropical and sub-tropical countries worldwide, with entomological surveillance and control activities as the key management approaches. This study aimed to explore the spatial dispersal of the vector Aedes albopictus, captured by the modified sticky ovitrap (MSO) in residential areas with low-rise buildings in Selangor, Malaysia. Distribution maps were created and shown as temporally distinguished classes based on hotspot analysis by Getis-Ord; spatial autocorrelation assessed by semivariograms using the exponential Kernel function; and universal Kriging showing areas with estimated high and low vector densities. Distribution, hotspot and interpolated maps were analysed based on the total number of mosquitoes by month and week. All maps in the present study were generated and visualised in ArcMap. Spatial autocorrelation of Ae. albopictus based on the monthly occurrence of Ae. albopictus was found in March, April, October, November and December 2018, and when based on the weekly numbers, in weeks 1, 2, 3, 5, 7, 12, 14, 25, 26, 27, 31, 33, 42, 49 and 52. Semivariograms, based on the monthly and weekly numbers of Ae. albopictus, indicated spatial autocorrelation of the species extending between 50 and 70 m. The mosquito density maps reported in this study may provide beneficial information to facilitate implementation of more efficient entomological control activities.