Background: Dengue has affected more than one-third of the world population and Malaysia has recorded an increase in the number of dengue cases since 2012. Selangor state recorded the highest number of dengue cases in Malaysia. Most of the dengue infections occur among people living in hotspot areas of dengue. This study aims to compare Knowledge, Attitude, and Practice among communities living in hotspot and non-hotspot dengue areas. Method: Communities living in 20 hotspot and 20 non-hotspot areas in Selangor were chosen in this study where 406 participants were randomly selected to answer questionnaires distributed at their housing areas. Total marks of each categories were compared using t-test. Result: Results show that there were significant mean differences in marks in Knowledge (p value: 0.003; 15.41 vs. 14.55) and Attitude (p value: < 0.001; 11.41 vs. 10.33), but not Practice (p value 0.101; 10.83 vs. 10.47) categories between communities of non-hotspot and hotspot areas. After considering two confounding variables which are education level and household income, different mean marks are found to be significant in Knowledge when education level acts as a covariate and Attitude when both act as covariates. Conclusion: Overall results show that people living in non-hotspot areas had better knowledge and attitude than people living in hotspot areas, but no difference was found in practice. This suggests that public health education should be done more frequently with people with a low education background and low household income, especially in hotspot areas to fight dengue outbreak and make dengue cases decrease effectively.

Background: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria incidence in Abuja, Nigeria. Methodology/Principal Findings: monthly data on malaria incidence and weather variables were collected in Abuja from the year 2000 to 2013. The analysis of count outcomes was based on generalized linear models, while Pearson correlation analysis was undertaken at the bivariate level. The results showed more malaria incidence in the months with the highest rainfall recorded (June–August). Based on the negative binomial model, every unit increase in humidity corresponds to about 1.010 (95% confidence interval (CI), 1.005–1.015) times increase in malaria cases while the odds of having malaria decreases by 5.8% for every extra unit increase in temperature: 0.942 (95% CI, 0.928–0.956). At lag 1 month, there was a significant positive effect of rainfall on malaria incidence while at lag 4, temperature and humidity had significant influences. Conclusions: malaria remains a widespread infectious disease among the local subjects in the study area. Relative humidity was identified as one of the factors that influence a malaria epidemic at lag 0 while the biggest significant influence of temperature was observed at lag 4. Therefore, emphasis should be given to vector control activities and to create public health awareness on the proper usage of intervention measures such as indoor residual sprays to reduce the epidemic especially during peak periods with suitable weather conditions.