KAUST is increasing campus population due to repatriation flights and additional students coming to campus. There has been a noticeable uptick in new cases of COVID-19, with some presenting with symptoms. KAUST emphasizes the importance of wearing face coverings, observing physical distance, washing hands, avoiding groups of more than 10 people and restricting social networks. Why it matters: This update provides insight into the university's health and safety protocols, reflecting broader trends in managing public health within research institutions in the GCC.
KAUST reflects on its COVID-19 response, highlighting community efforts, research contributions, and partnerships. Faculty are leveraging expertise in diagnostics, AI therapeutics, genomics, and epidemiology. KAUST is collaborating with the Saudi CDC, Ministry of Health, and other institutions. Why it matters: This demonstrates KAUST's role as a hub for research and innovation, contributing to both national and global health challenges during a crisis.
KAUST's president addressed the community regarding the university's response to COVID-19 since January, detailing the formation of a Coronavirus Task Force and Crisis Management Team. The university has issued 25 announcements, and the Saudi government's response was lauded. KAUST is balancing community health protection and minimizing disruptions with no confirmed cases at KAUST. Why it matters: This address highlights the proactive measures taken by a leading Saudi institution to manage a global health crisis, reflecting the Kingdom's broader efforts and KAUST's commitment to its community's well-being.
A KAUST Rapid Research Response Team (R3T) is collaborating with healthcare stakeholders to combat COVID-19. Xin Gao and his Structural and Functional Bioinformatics (SFB) Group are developing an AI-based diagnosis pipeline from CT scans of COVID-19 patients. The AI pipeline aims to address the high false negative rates associated with nucleic acid detection. Why it matters: This research could improve COVID-19 diagnostics and potentially inform understanding of viral pathogenesis.
KAUST professor David Ketcheson uses mathematical modeling to understand COVID-19 transmission. He applies differential equations to explain the progression of SARS-CoV-2, utilizing the SIR model to predict the spread. Ketcheson's analysis suggests that the reproduction number for COVID-19 could be as high as 5, emphasizing the need for social distancing. Why it matters: This highlights the role of mathematical modeling and data analysis in understanding and predicting the spread of infectious diseases, particularly in the context of pandemic response.
KAUST researchers are analyzing the SARS-CoV-2 genome to identify potential targets for treatment and vaccine development. They are using the KAUST Metagenome Analysis Platform (KMAP) and the university's supercomputer to compare and analyze genomic data. The research focuses on identifying key genes for detection and treatment of COVID-19. Why it matters: This research contributes to the global effort to combat the pandemic and highlights KAUST's capabilities in genomic data analysis and computational bioscience.
An article from KAUST discusses the impact of COVID-19 on automation, material science, and VR. It suggests increased automation, voice activation, and motion detection to reduce transmission in public spaces. KAUST faculty member Derya Baran is working on antimicrobial materials for high-touch locations, and KAUST is exploring VR for virtual labs. Why it matters: The pandemic is accelerating the adoption of AI-driven solutions and advanced materials research within Saudi Arabia to address public health challenges.
A KAUST research team is using cellphone mobility data, Google searches, and social media to model and predict COVID-19 spread. The models aim to forecast cases in the coming weeks and inform resource allocation, including hospital beds and medical staff. The team is using aggregated and anonymized data from cellphone companies to respect people's privacy. Why it matters: Integrating real-time digital data with epidemiological modeling can improve the speed and effectiveness of public health responses in the region and globally.