220817 Jude Kong
Estimation of COVID-19 ascertainment rates across Africa and drivers of transmission dynamics worldwide in the early stage.
  • Speaker: Jude Kong, York University
  • Date and Time: Wednesday, August 17, 2022 - 2:00pm to 3:00pm
  • Abstract: Disease outbreaks are increasing both in terms of severity and frequency, in part due to accelerating human encroachment into natural landscapes, urbanization, globalization, and climate change. These are exacerbating and worsening already existing health and social inequities by straining health systems and increasing the vulnerability of climate “hotspots” to the emergence and re-emergence of many infectious diseases. The One Health concept recognizes and responds to the reality that human health is interdependent with the health of animals and the environment. Addressing disease outbreaks that span the human-animal-environment interface requires intersectoral, multidisciplinary, and systems-oriented (process-, pattern-based, and participatory) approaches that can examine and manipulate large data sets to identify risks, conduct integrative, predictive modeling, and provide proactive, evidence-based recommendations for public health policy and action. My research program represents a step in this direction.
  • In this talk, I will share some of the work I have been doing: helping governments and communities to manage and contain the spread of COVId-19. In the first part, I will show some of the models that I designed and analyzed for early response and community-based risk mitigation and control of developing epidemics using COVID-19 as a case study. I will present the results I obtained from the models. In the second part, I will talk about some of my ongoing work on designing an early warning framework for emerging and re-emerging infectious diseases.
  • Bio: Dr. Jude Kong is a professor in the Mathematics & Statistics Department at York University and the founding Director of the Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC). Additionally, he is the Regional Node Liaison to the steering committee of the Canadian Black Scientist Network (CBSN), a member of the Scientific Advisory Committee of the Mathematics for Public Health Network, a member of the National COVID-19 Modelling Rapid Response Task Force and a member of the Canadian Centre for Disease Modelling. He obtained his Ph.D. in Mathematics from the University of Alberta, his MSc. in Mathematical Modelling from the University of Hamburg-Germany and the University of L'Aquila-Italy. His B.Sc. in Mathematics and Computer Science was acquired at the University of Buea-Cameroon and his Bachelor of Education (B.Ed) degree in Mathematics was earned at the University of Yaounde-Cameroon. Before joining York University, he did 2-years of postdoc at Princeton University. Dr. Kong is an expert in mathematical modelling, artificial intelligence, infectious disease modelling and mathematics education. His principal research program focuses on the use of mathematical modelling and other quantitative methods to improve decision-making for epidemic and pandemic prevention, preparedness and response. During the COVID-19 pandemic, he has been leading an interdisciplinary team of more than 52 researchers from key academic and government institutions in nine African countries that have been using Artificial intelligence to help government and local communities to contain and manage the spread of COVID-19. In 2020, he won a York Research Leader Award. In 2021 he was spotlighted among Canadian Innovation Research Leaders 2021 for his work with ACADIC. In 2022, he was spotlighted as a Change Maker by People of YU for his work in helping others learn mathematical concepts and encouraging them to find their passion and achieve more than they thought was possible. He is an Area Editor of the Data & Policy Journal where he focuses on Data Technologies and Analytics for Policy and Governance
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220817 Jude Kong
Jude Kong »Jude Kong
Climate change »Climate change
Covid-19 »Covid-19
Environment »Environment
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