A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.

Airline traffic forecasting is important to airlines and regulatory authorities. This paper examines a number of approaches to forecasting short-to medium-term air traffic flows. It contributes as a rare replication, testing a variety of alternative modelling approaches. The econometric models employed include autoregressive distributed lag (ADL) models, time-varying parameter (TVP) models and an automatic method for econometric model specification. A vector autoregressive (VAR) model and various univariate alternatives are also included to deliver unconditional forecast comparisons. Various approaches for taking into account interactions between contemporaneous air traffic flows are examined, including pooled ADL models and the enhanced models with the addition of a "world trade" variable. Based on the analysis of a number of forecasting error measures, it is concluded that pooled ADL models that include the "world trade" variable outperform the alternatives, and in particular univariate methods; and, second, that automatic modelling procedures are enhanced through judgmental intervention. In contrast to earlier results, the TVP models do not improve accuracy. Depending on the preferred error measure, the difference in accuracy may be substantial. c

Since 2000, human malaria cases in Malaysia were rapidly reduced with the use of insecticides in Indoor Residual Spray (IRS) and Long-Lasting Insecticide Net (LLIN). Unfortunately, monkey malaria in humans has shown an increase especially in Sabah and Sarawak. The insecticide currently used in IRS is deltamethrin K-Othrine ® WG 250 wettable granule, targeting mosquitoes that rest and feed indoor. In Sabah, the primary vector for knowlesi malaria is An. balabacensis a species known to bite outdoor. This study evaluates an alternative method, the Outdoor Residual Spray (ORS) using a novel formulation of deltamethrin K-Othrine ® (PolyZone) to examine it suitability to control knowlesi malaria vector in Sabah, compared to the current method. The study was performed at seven villages in Sabah having similar type of houses (wood, bamboo and concrete). Houses were sprayed with deltamethrin K-Othrine ® (PolyZone) at two different dosages, 25 mg/m 2 and 30 mg/m 2 and deltamethrin K-Othrine ® WG 250 wettable granule at 25 mg/m 2 , sprayed indoor and outdoor. Residual activity on different walls was assessed using standard cone bioassay techniques. For larval surveillances, potential breeding sites were surveyed. Larvae were collected and identified, pre and post spraying. Adult survey was done using Human Landing Catch (HLC) performed outdoor and indoor. Detection of malaria parasite in adults was conducted via microscopy and molecular methods. Deltamethrin K-Othrine ® (PolyZone) showed higher efficacy when sprayed outdoor. The efficacy was found varied when sprayed on different types of wall surfaces. Deltamethrin K-Othrine ® (PolyZone) at 25 mg/m 2 was the most effective with regards to ability to high mortality and effective knock down (KD). The vector population was reduced significantly post-spraying and reduction in breeding sites as well. The number of simian malaria infected vector, human and simian malaria transmission were also greatly reduced.

In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data. Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated. The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters. The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme. The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model. The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.

Adult mosquito sampling techniques are essential for monitoring transmission of malaria and other mosquito borne infections. Preference for any sampling technique depends on both its field efficiency and the characteristics of local vector populations. Surveys on adult mosquitoes using Human Landing Catch (HLC) and CO2-baited CDC light trap (CDC-LT) techniques were conducted in several knowlesi malaria endemic areas between the months of March to December 2012 in several states of Peninsula Malaysia. These two techniques were relatively compared to determine the preferences of anopheline mosquitoes towards CO2-baited CDC-LT technique using HLC technique as the reference method. Cx. gelidus, An. maculates and An. introlatus were the main three species collected by HLC technique, whereas the species collected by CO2-baited CDC-LT technique were mostly An. cracens, Ar. durhami and Coquillettidia species. Most of the Anopheles species were collected almost exclusively by the human collectors except for An. cracens and An. introlatus which were collected using both techniques. Anopheles cracens was the most dominant species captured using CO2-baited CDC-LT technique. This is the first report showing An. cracens was caught using CO2-baited CDC-LT technique in Malaysia.