In response to the Covid-19 emerging as a global pandemic in March, NTNU formed an transdisciplinary team to develop an epidemiological model and provide additional insights on risk factors and strategies for mitigation. This lecture, by André Voigt, will give insight into this work.
This lecture in the Digital frukost seminar series is open for everyone. You can participate either:
Breakfast and coffee will be served to participants at the physical meeting in Bergen.
Deadline for registration: October 21
Register here to join the meeting either digitally or in Bergen.
In response to the Covid-19 emerging as a global pandemic in March, NTNU formed an interdisciplinary team to develop an epidemiological model and provide additional insights on risk factors and strategies for mitigation. Andrè Voigt, who has been part of the NTNU Covid-19 Taskforce, will give us insight into their work. They developed a detailed individual-based model for the municipalities in Norway, which they calibrated according to hospitalization data, achieving an accurate fit. As both vaccine and treatment are currently unavailable, they decided to explore the effectiveness of various testing strategies for infection control. Observing that intra-household spread seems to be a major driver of the pandemic, and that intra-household spread increases with increasing household size, they propose a strategy of regularized testing of larger households, which results in a markedly stronger reduction in epidemic reproduction number R compared to less targeted approaches.
"Digital frukost" is an open breakfast seminar series focusing on research activities at the interface between the biological sciences and that of mathematics, computer science, physics, engineering or social sciences. Examples of such research activities could be mathematical or computational modeling of biological systems, application of engineering/control systems theory on biological systems or inspired by biological systems, application of mathematics/statistics/machine learning to analyze big data in health or marine sector; from sensor systems, imaging, omics technologies, policy making based on scientific models etc.
We look forward to your participation!