ABSTRACT
BACKGROUND: Malaria is still a public health threat. From 2015 to 2021, a total of 23,214 malaria cases were recorded in Malaysia. Thus, effective intervention and key entomological information are vital for interrupting or preventing malaria transmission. Therefore, the availability of malaria vector information is desperately needed. OBJECTIVE: The objective of our study is to update the list of human and zoonotic malaria vectors in Malaysia. This work will include (1) the characterization of the key behavioral traits and breeding sites of malaria vectors and (2) the determination of new and potential malaria vectors in Malaysia. The findings of our scoping review will serve as decision-making evidence that stakeholders and decision makers can use to strengthen and intensify malaria surveillance in Malaysia. METHODS: The scoping review will be conducted based on the following four electronic databases: Scopus, PubMed, Google Scholar, and Science Direct. A search strategy was conducted for articles published from database inception to March 2022. The criteria for article inclusion were any malaria vector-related studies conducted in Malaysia (with no time frame restrictions) and peer-reviewed studies. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) will be used to guide our systematic approach. Data from published research literature will be extracted by using a standardized data extraction framework, including the titles, abstracts, characteristics, and main findings of the included studies. To assess the risk of bias, articles will be screened independently by 2 reviewers, and a third reviewer will make the final decision if disagreements occur. RESULTS: The study commenced in June 2021, and it is planned to be completed at end of 2022. As of early 2022, we identified 631 articles. After accessing and evaluating the articles, 48 were found to be eligible. Full-text screening will be conducted in mid-2022. The results of the scoping review will be published as an open-access article in a peer-reviewed journal. CONCLUSIONS: Our novel scoping review of malaria vectors in Malaysia will provide a comprehensive evidence summary of updated, relevant information. An understanding of the status of Anopheles as malaria vectors and the knowledge generated from the behavioral characteristics of malaria vectors are the key components in making effective interventions for eliminating malaria. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39798.
ABSTRACT
Dengue is a harmful tropical disease that causes death to many people. Currently, the dengue vaccine development is still at an early stage, and only intervention methods exist after dengue cases increase. Thus, previously, two scientific experimental field studies were conducted in producing a dengue outbreak forecasting model as an early warning system. Successfully, an Autoregressive Distributed Lag (ADL) Model was developed using three factors: the epidemiological, entomological, and environmental with an accuracy of 85%; but a higher percentage is required in minimizing the error for the model to be useful. Hence, this study aimed to develop a practical and cost-effective dengue outbreak forecasting model with at least 90% accuracy to be embedded in an early warning computer system using the Internet of Things (IoT) approach. Eighty-one weeks of time series data of the three factors were used in six forecasting models, which were Autoregressive Distributed Lag (ADL), Hierarchical Forecasting (Bottom-up and Optimal combination) and three Machine Learning methods: (Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest). Five error measures were used to evaluate the consistency performance of the models in order to ensure model performance. The findings indicated Random Forest outperformed the other models with an accuracy of 95% when including all three factors. But practically, collecting mosquito related data (the entomological factor) was very costly and time consuming. Thus, it was removed from the model, and the accuracy dropped to 92% but still high enough to be of practical use, i.e., beyond 90%. However, the practical ground operationalization of the early warning system also requires several rain gauges to be located at the dengue hot spots due to localized rainfall. Hence, further analysis was conducted in determining the location of the rain gauges. This has led to the recommendation that the rain gauges should be located about 3-4 km apart at the dengue hot spots to ensure the accuracy of the rainfall data to be included in the dengue outbreak forecasting model so that it can be embedded in the early warning system. Therefore, this early warning system can save lives, and prevention is better than cure.
ABSTRACT
Objective: To assess the insecticide susceptibility status of Anopheles cracens (An. cracens) and Anopheles maculatus (An. maculatus) from knowlesi malaria endemic areas in Peninsular Malaysia towards DDT, malathion and deltamethrin and to determine the resistance mechanism involved. Methods: Adult and larval mosquitos were collected for surveillance. Susceptibility status of Anopheles was determined using the standard WHO adult bioassay, larval bioassay and biochemical enzyme assay. Results: WHO adult bioassay results indicated An. cracens collected from Kampung Sungai Ular, Pahang was resistant towards 4% DDT, while An. maculatus collected from Kampung Sokor, Kelantan and Kampung Sungai Lui, Selangor exhibited resistance towards 4% DDT. However, the enzyme activity profiles varied according to strains and species. The resistance ratio of larval bioassay, showed that all strains and species tested were susceptible to malathion and temephos. Conclusions: Since only a few anopheline strains exhibited low level of insecticide resistance towards malathion, DDT and temephos. These insecticides are still considered effective for vector control program towards An. cracens and An. maculatus.
