Early detection of a dengue outbreak is an important first step towards implementing effective dengue interventions resulting in reduced mortality and morbidity. A dengue mathematical model would be useful for the prediction of an outbreak and evaluation of control measures. However, such a model must be carefully parameterized and validated with epidemiological, ecological and entomological data. A field study was conducted to collect and analyse various parameters to model dengue transmission and outbreak. Dengue prone areas in Kuala Lumpur, Pahang, Kedah and Johor were chosen for this study. Ovitraps were placed outdoor and used to determine the effects of meteorological parameters on vector breeding. Vector population in each area was monitored weekly for 87 weeks. Weather stations, consisting of a temperature and relative humidity data logger and an automated rain gauge, were installed at key locations in each study site. Correlation and Autoregressive Distributed Lag (ADL) model were used to study the relationship among the variables. Previous week rainfall plays a significant role in increasing the mosquito population, followed by maximum humidity and temperature. The secondary data of rainfall, temperature and humidity provided by the meteorological department showed an insignificant relationship with the mosquito population compared to the primary data recorded by the researchers. A well fit model was obtained for each locality to be used as a predictive model to foretell possible outbreak.
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.
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/m2 and 30 mg/m2 and deltamethrin K-Othrine® WG 250 wettable granule at 25 mg/m2, 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/m2 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.