Dengue fever is a major public health issue and a leading cause of illness and death worldwide. Although the government has implemented various initiatives for dengue surveillance, prevention, and control, AI and machine learning can be utilized to help public health authorities proactively mitigate outbreaks. To address these challenges, it is essential to develop an early warning system capable of predicting dengue outbreaks. This keynote presents our proposed Early Warning System to predict dengue outbreaks that integrates multiple data sources including epidemiological onset dengue data, microclimate data and machine learning model to anticipate potential outbreaks, enabling timely interventions. The system utilizes real-time microclimatic data captured using IoT sensors, incorporating automated data extraction and pre-processing procedures coupled with an advanced machine learning classifier focusing on micro-level data and analysis. Emerging technologies like IoT with sensors-based devices enable the designed system to record a variety of real- time microclimatic behaviour data which are used to develop the dengue outbreak early warning prediction at the local level that enables targeted and effective intervention. This keynote is aimed to demonstrate a comprehensive approach to this data-driven solution for dengue outbreak prediction. It provides near real-time prediction of dengue outbreaks and instant information to public health officials in monitoring the risk of dengue outbreaks to enable quick decision-making response.
Wan Fairos Wan Yaacob is an Associate Professor at the College of Computing, Informatics, and Mathematics, UiTM and an Associate Research Fellow at the Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), UiTM. She earned her PhD in Statistics from UiTM, Master of Science in Statistics from UKM and Degree in Statistics from UiTM. Her research interests focus on statistical modelling, data mining, predictive modelling and machine learning. Her research works span the fields of dengue disease, water quality, road accidents and education. Dr Wan Fairos’s passion for research is evident when she secured a number of national and international grants in collaboration with UMT, MOH, ITB, USM, UMK, MAIK and FAMA and a number of research consultation projects. She published many articles in various well-known journals and collaborates with researchers from USA, Mexico, India, Turkey and Indonesia. She has been invited as a keynote, and plenary speaker for intensive courses on panel count model and data mining workshops by Institute Teknologi Bandung, PT Komatsu, Jakarta, Kasetsart University, UCSI, MIROS, ARI and IBDAAI and as a plenary speaker for conferences in ITB.