The objective of pandemic surveillance is to monitor and detect potential infectious diseases outbreak by collecting and analyzing health data related to infected people. Typically, data collection focuses on pre-diagnosis information collected from patients admitted to emergency rooms and urgent care. Such information is insufficient for a full understanding of the dynamics of the disease outbreak. In such cases, it is important to immediately collect information about potentially infected people who came in contact with the admitted patient. This process is known as Contact Tracing. Manual contact tracing is labor intensive and prone to error. Due to the vast impact of COVID-19 on health and economy worldwide, it is important to develop a robust surveillance systems for real-time monitoring of the infected cases. To address this challenge, we developed a Real-time Pandemic Surveillance System (RPSS) that will provides timely collection, analysis and visualization of infectious pandemic disease data. In addition, RPSS is integrated to contact tracing applications that provide a scalable solution to monitor and notify exposed people in timely manner. The system provides a robust and privacy-preserving platform for modeling and simulating various epidemiology models. In addition, it provides an infrastructure for the stakeholders to exercise planning capabilities in various aspects, including health response, logistics planning, and long-time strategy planning to confine COVID-19.

(This project is funded by KACST Fast Track Funding Path for COVID-19 Research Projects, project number 5-20-01-003-0003)