York University researchers leading national infectious disease modelling efforts
Researchers in York University’s Faculty of Science have been awarded federal government funding to lead national disease modelling efforts that will help better predict, prevent and respond to emerging infectious disease.
The Minister of Innovation, Science and Industry, François-Philippe Champagne, and the Minister of Health Patty Hajdu, announced an investment of $10 million in funding on Friday, including $2.5 million over two years for the One Health Modelling Network, led by York University mathematics Professor Huaiping Zhu.
They also announced $3 million in funding for Mathematics for Public Health (MfPH) led by University of Toronto mathematics Professor V. Kumar Murty and co-led by York University mathematics Professor Jianhong Wu.
The projects are among several multidisciplinary infectious disease modelling networks being funded through the Emerging Infectious Diseases Modelling Initiative, established through a partnership between the Public Health Agency of Canada (PHAC) and Natural Sciences and Engineering Research Council of Canada (NSERC).
One Health Modelling Network
As the COVID-19 pandemic continues, Zhu is building a new network of researchers and collaborators who will bring a “One Health” approach to disease modelling to better predict, prevent and respond to emerging infectious diseases.
The One Health Modelling Network for Emerging Infections/Réseau Une Seule Santé sur le modélisation des Infections (OMNI/RÉUNIS) will use multidisciplinary knowledge about the connections between environmental, animal and human health to refine the disease modelling that is used to identify pathogens early.
“We are grateful for the federal government’s investment in the OMNI network, which will support researchers and collaborators from York University and institutions across the country as they work together to better predict, prevent and respond to emerging infectious diseases,” said York University President and Vice-Chancellor Rhonda L. Lenton. “The Canadian Centre for Disease Modelling, hosted by York University, is a leader in modelling emerging and infectious diseases, and will provide a strong foundation of expertise to support Professor Zhu and the other members of the OMNI network as they work to protect the health and well-being of our local and global communities.”
As principal investigator on the OMNI/RÉUNIS project, Zhu, a professor in the Department of Mathematics & Statistics in York’s Faculty of Science, will bring together 72 project co-applicants from 23 Canadian universities and 49 collaborators from 28 national and international organizations. Their expertise ranges from public health, infectious diseases and epidemiology, to human health, animal health and wildlife, as well as climate-related health outcomes. They will focus on five areas: early detection, early warning systems, early response, and mitigation and control of developing epidemics.
“We are in the midst of an unprecedented emerging infectious disease crisis with the spread of COVID-19, and we need to evolve accordingly,” said Zhu. “The OMNI network will focus on developing models and capacity to inform prevention, surveillance and response. We will ‘follow the bug’ from its place of origin to its introduction and establishment.”
The OMNI network will build on the strong modelling history and multi-disciplinary expertise of the Canadian Centre for Disease Modelling, based at York, and includes many collaborators from the university: Faculty of Science Professors Iain Moyles, Jude Kong, Hongmei Zhu, Jane Heffernan, Carly Rozins and Hanna Jankowski; Lassonde School of Engineering Professors Marina Freire-Gormaly, Manos Papagelis and Aijun An; and Professor Sean Hillier of the Faculty of Health.
Models developed from the new network are expected to lead to identification of critical data and modelling gaps from a One Health perspective. By identifying the gaps, the network will be able to target surveillance and data and use the data in the disease modelling. For example, the network, which includes Indigenous collaborators, will work with Indigenous communities to address their specific concerns in the modelling and improve early warning capacity.
The Mathematics for Public Health (MfPH) initiative
The Mathematics for Public Health (MfPH) initiative is a collaboration between The Fields Institute, the Atlantic Association for Research in Mathematical Sciences (AARMS), the Centre de Recherches Mathématiques (CRM), and the Pacific Institute for Mathematical Sciences (PIMS). It establishes a pan-Canadian, Emerging Infectious Disease Modelling (EIDM) network that aims to apply advanced mathematical techniques to help achieve public health objectives.
The MfPH group is comprised of 48 co-investigators, 21 Canadian institutions and more than 20 national and international collaborators in fields such as epidemiology, mathematical modelling, infectious disease, and public health. It will mobilize a national network that uses state-of-the-art techniques to advise on public health policy with the long-term goal of boosting future epidemic preparedness and improving Canada’s resilience in emergency situations.
“The establishment of this network is critical at this time,” says Wu. “It will accelerate our ability to respond to the current pandemic swiftly and accurately, and prepare for future public health emergencies.”
York University brings an interdisciplinary perspective to this national network and modelling platform, with expertise including mathematical modelling, disaster management and emergency operations, smart transportation systems, economic and financial risk assessment, and computational epidemiology.
Including Wu, there are eight York University co-applicants involved in this project: Professors Seyed Moghadas, Shengyuan (Michael) Chen, Ed Furman, and Jude Kong, all from the Department of Mathematics & Statistics; Professor Peter Park, Lassonde School of Engineering; and Ali Asgary, and Ida Ferrara, professors in the Faculty of Liberal Arts & Professional Studies.