Monitoring Short Term Changes of Malaria Incidence in Uganda with Gaussian Processes

A method to monitor communicable diseases based on health records is proposed. The method is applied to health facility records of malaria incidence in Uganda. This disease represents a threat for approximately 3.3 billion people around the globe. We use Gaussian processes with vector-valued kernels to analyze time series components individually. This method allows not only removing the effect of specific components, but studying the components of interest with more detail. The short term variations of an infection are divided into four cyclical phases. Under this novel approach, the evolution of a disease incidence can be easily analyzed and compared between different districts. The graphical tool provided can help quick response planning and resources allocation.

• Type: Journal
• Year: 2015
• Where: PKDD
• Authors: Ricardo Andrade Pacheco, Martin Gordon Mubangizi, John A. Quinn, Neil D. Lawrence
• Keywords: Data Mining, PKDD 2015