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Monica Cojocaru Person1 #715762 Professor in the Mathematics & Statistics Department at the University of Guelph. |
- I completed my B.Sc. and M.Sc. in Mathematics at the University of Bucharest (Romania) and my Ph.D. in Mathematics at Queen’s University in Kingston, Canada. I held an NSERC postdoctoral fellowship at the Centre des Researches Mathematiques (CRM) in Montreal in 2003. I held several visiting positions at the Centre des Researches Mathematiques, the Fields Institute, Harvard, and Northwestern Universities, at University of Brescia and most recently I hold a Senior Visiting Research Fellowship at Lehigh University in Pennsylvania, USA. I held one of only two Canada-US Fulbright Visiting Research Chair positions awarded in 2010 in the Department of Mathematics at the University of California at Santa Barbara.
- I conduct both independent and collaborative research that consolidates and furthers our understanding of the mathematical theory involved in the time-evolution of equilibrium problems, as they are formulated coming from applications. The main focus of my research lies in the general area of nonsmooth dynamical and complex systems - theory and applications. Some of the problems I study are the so-called equilibrium problems, which concern themselves with the mathematical modelling of economic (Wardrop), game theoretic (Nash), and physical equilibria. Theoretical research in this area answers questions about existence, uniqueness, stability and sensitivity of equilibria for a wide range of applied problems (transportation, Nash/Cournot, network (social and environmental), dynamic and evolutionary games). Other research questions refer to studying parallels between classic dynamical systems models and computational emergent dynamic systems for populations (where individuals can be thought of as consumers, voters, vaccinators, etc.).
Key areas of focus include: - Solutions, computation, and stability of solutions for Generalized Nash Games. Generalized Nash Games were introduced as far back as the 60's, however they are now coming to the forefront from a theoretical as well as an application perspective. These are games where, in addition to a player's payoff being dependent on other players choices, each player's strategy set is also dependent upon the other players' choices. Prof. Cojocaru is interested in the links between generalized Nash strategies and replicator dynamics in a math biological sense. She is currently collaborating with a group at the University of Limoges on AI methods in generalized Nash games.
- Dynamics of human behaviour at individual and population levels. Environmental issues are at the forefront of our social lives and most policy makers are studying the best policies and strategies towards a decrease in harmful emissions and in consumption of non-renewable resources. Such policies need solid models of individual and population behaviour, since no policy is successful unless it is adopted by a high enough population mass.
- Mathematical modelling, optimization, and game theory in population health. Prof. Cojocaru has examined applications of dynamic games in vaccination behaviour, and specifically, the problem of modelling strategic interactions of various groups within a population under voluntary vaccination policy. Cojocaru and her group are modelling infection spread in child care facilities and have contributed three publications on COVID-19's impact on the population of Ontario, Canada and specifically towards school reopening policies in pandemic times.
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+Citations (6) - CitationsAdd new citationList by: CiterankMapLink[2] Age-stratified transmission model of COVID-19 in Ontario with human mobility during pandemic’s first wave
Author: R. Fields, L. Humphrey D. Flynn-Primrose, Z. Mohammadi, M. Nahirniak, E.W. Thommes, M.G. Cojocaru Publication date: 1 September 2021 Publication info: Heliyon, 7(9), e07905. Cited by: David Price 4:43 PM 1 December 2023 GMT Citerank: (6) 701037MfPH – Publications144B5ACA0, 701624Zahra MohammadiPostdoctoral Fellow, Mathematics for Public health, Fields Institute, Department of Mathematics and Statistics, University of Guelph, Memorial University of Newfoundland.10019D3ABAB, 703963Mobility859FDEF6, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6, 715419Edward Thommes Edward W. Thommes is an Adjunct Professor of Mathematics at the University of Guelph and at York University. He is a Global Modeling Lead in the Modeling, Epidemiology and Data Science (MEDS) team of Sanofi Vaccines, an Affiliate Researcher in the Waterloo Institute for Complexity and Innovation (WICI), and a member of the Strategic Advisory Committee for the Mathematics for Public Health program at the Fields Institute.10019D3ABAB URL: DOI: https://doi.org/10.1016/j.heliyon.2021.e07905
| Excerpt / Summary [Heliyon, 1 September 2021]
In this work, we employ a data-fitted compartmental model to visualize the progression and behavioral response to COVID-19 that match provincial case data in Ontario, Canada from February to June of 2020. This is a “rear-view mirror” glance at how this region has responded to the 1st wave of the pandemic, when testing was sparse and NPI measures were the only remedy to stave off the pandemic. We use an SEIR-type model with age-stratified subpopulations and their corresponding contact rates and asymptomatic rates in order to incorporate heterogeneity in our population and to calibrate the time-dependent reduction of Ontario-specific contact rates to reflect intervention measures in the province throughout lockdown and various stages of social-distancing measures. Cellphone mobility data taken from Google, combining several mobility categories, allows us to investigate the effects of mobility reduction and other NPI measures on the evolution of the pandemic. Of interest here is our quantification of the effectiveness of Ontario's response to COVID-19 before and after provincial measures and our conclusion that the sharp decrease in mobility has had a pronounced effect in the first few weeks of the lockdown, while its effect is harder to infer once other NPI measures took hold. |
Link[3] Meaningful Contact Estimates among Children in a Childcare Centre with Applications to Contact Matrices in Infectious Disease Modelling
Author: Darren Flynn-Primrose, Nickolas Hoover, Zahra Mohammadi, Austin Hung, Jason Lee, Miggi Tomovici, Edward W. Thommes, Dion Neame, Monica G. Cojocaru Publication date: 18 May 2022 Publication info: Journal of Applied Mathematics and Physics, 2022, 10, 1525-1546 Cited by: David Price 4:43 PM 1 December 2023 GMT Citerank: (4) 701037MfPH – Publications144B5ACA0, 701624Zahra MohammadiPostdoctoral Fellow, Mathematics for Public health, Fields Institute, Department of Mathematics and Statistics, University of Guelph, Memorial University of Newfoundland.10019D3ABAB, 708813Agent-based models859FDEF6, 715419Edward Thommes Edward W. Thommes is an Adjunct Professor of Mathematics at the University of Guelph and at York University. He is a Global Modeling Lead in the Modeling, Epidemiology and Data Science (MEDS) team of Sanofi Vaccines, an Affiliate Researcher in the Waterloo Institute for Complexity and Innovation (WICI), and a member of the Strategic Advisory Committee for the Mathematics for Public Health program at the Fields Institute.10019D3ABAB URL: DOI: https://doi.org/10.4236/jamp.2022.105107
| Excerpt / Summary [Journal of Applied Mathematics and Physics, 18 May 2022]
We present a mathematical model of a day care center in a developed country (such as Canada), in order to use it for the estimation of individual-to-individual contact rates in young age groups and in an educational group setting. In our model, individuals in the population are children (ages 1.5 to 4 years) and staff, and their interactions are modelled explicitly: person-to-person and person-to-environment, with a very high time resolution. Their movement and meaningful contact patterns are simulated and then calibrated with collected data from a child care facility as a case study. We present these calibration results as a first part in the further development of our model for testing and estimating the spread of infectious diseases within child care centers. |
Link[4] Importation models for travel-related SARS-CoV-2 cases reported in Newfoundland and Labrador during the COVID-19 pandemic
Author: Zahra Mohammadi, Monica Cojocaru, Julien Arino, Amy Hurford Publication date: 12 June 2023 Publication info: medRxiv 2023.06.08.23291136 Cited by: David Price 4:43 PM 1 December 2023 GMT
Citerank: (7) 679752Amy HurfordAmy Hurford is an Associate Professor jointly appointed in the Department of Biology and the Department of Mathematics and Statistics at Memorial University of Newfoundland and Labrador. 10019D3ABAB, 679817Julien ArinoProfessor and Faculty of Science Research Chair in Fundamental Science with the Department of Mathematics at the University of Manitoba.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 701148Implementation of mobility restrictionsThe implementation of mobility restrictions, in combination with vaccination and non-pharmaceutical interventions, to meet the needs of small communities during a pandemic.859FDEF6, 701624Zahra MohammadiPostdoctoral Fellow, Mathematics for Public health, Fields Institute, Department of Mathematics and Statistics, University of Guelph, Memorial University of Newfoundland.10019D3ABAB, 703963Mobility859FDEF6, 704045Covid-19859FDEF6 URL: DOI: https://doi.org/10.1101/2023.06.08.23291136
| Excerpt / Summary [medRxiv, 12 June 2023]
During the COVID-19 pandemic there was substantial variation between countries in the severity of the travel restrictions implemented suggesting a need for better importation models. Data to evaluate the accuracy of importation models is available for the Canadian province of Newfoundland and Labrador (NL; September 2020 to June 2021) as arriving travelers were frequently tested for SARS-CoV-2 and travel-related cases were reported. Travel volume to NL was estimated from flight data, and travel declaration forms completed at entry to Canada, and at entry to NL during the pandemic. We found that during the pandemic travel to NL decreased by 82%, the percentage of travelers arriving from Québec decreased (from 14 to 4%), and from Alberta increased (from 7 to 17%). We derived and validated an epidemiological model predicting the number of travelers testing positive for SARS-CoV-2 after arrival in NL, but found that statistical models with less description of SARS-CoV-2 epidemiology, and with parameters fitted from the validation data more accurately predicted the daily number of travel-related cases reported in NL originating from Canada (R2 = 0.55, ΔAICc = 137). Our results highlight the importance of testing travelers and reporting travel-related cases as these data are needed for importation models to support public health decisions. |
Link[5] Human behaviour, NPI and mobility reduction effects on COVID-19 transmission in different countries of the world
Author: Zahra Mohammadi, Monica Gabriela Cojocaru, Edward Wolfgang Thommes Publication date: 22 August 2022 Publication info: BMC Public Health volume 22, Article number: 1594 (2022) Cited by: David Price 4:44 PM 1 December 2023 GMT
Citerank: (9) 701037MfPH – Publications144B5ACA0, 701624Zahra MohammadiPostdoctoral Fellow, Mathematics for Public health, Fields Institute, Department of Mathematics and Statistics, University of Guelph, Memorial University of Newfoundland.10019D3ABAB, 703963Mobility859FDEF6, 704036Immunology859FDEF6, 704041Vaccination859FDEF6, 704045Covid-19859FDEF6, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6, 715419Edward Thommes Edward W. Thommes is an Adjunct Professor of Mathematics at the University of Guelph and at York University. He is a Global Modeling Lead in the Modeling, Epidemiology and Data Science (MEDS) team of Sanofi Vaccines, an Affiliate Researcher in the Waterloo Institute for Complexity and Innovation (WICI), and a member of the Strategic Advisory Committee for the Mathematics for Public Health program at the Fields Institute.10019D3ABAB URL: DOI: https://doi.org/10.1186/s12889-022-13921-3
| Excerpt / Summary [BMC Public Health, 22 August 2022]
Background: The outbreak of Coronavirus disease, which originated in Wuhan, China in 2019, has affected the lives of billions of people globally. Throughout 2020, the reproduction number of COVID-19 was widely used by decision-makers to explain their strategies to control the pandemic.
Methods: In this work, we deduce and analyze both initial and effective reproduction numbers for 12 diverse world regions between February and December of 2020. We consider mobility reductions, mask wearing and compliance with masks, mask efficacy values alongside other non-pharmaceutical interventions (NPIs) in each region to get further insights in how each of the above factored into each region’s SARS-COV-2 transmission dynamic.
Results: We quantify in each region the following reductions in the observed effective reproduction numbers of the pandemic: i) reduction due to decrease in mobility (as captured in Google mobility reports); ii) reduction due to mask wearing and mask compliance; iii) reduction due to other NPI’s, over and above the ones identified in i) and ii).
Conclusion: In most cases mobility reduction coming from nationwide lockdown measures has helped stave off the initial wave in countries who took these types of measures. Beyond the first waves, mask mandates and compliance, together with social-distancing measures (which we refer to as other NPI’s) have allowed some control of subsequent disease spread. The methodology we propose here is novel and can be applied to other respiratory diseases such as influenza or RSV. |
Link[6] Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data
Author: Svetozar Zarko Valtchev, Ali Asgary, Michael Chen, Felippe A. Cronemberger, Mahdi M. Najafabadi, Monica Gabriela Cojocaru, Jianhong Wu Publication date: 7 July 2021 Publication info: Electronics, 10(14), 1626–1626. Cited by: David Price 4:45 PM 1 December 2023 GMT
Citerank: (7) 679750Ali AsgaryAssociate Professor and Associate Director, Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM) in the School of Administrative Studies, and Adjunct Professor in the School of Information Technology, at York University.10019D3ABAB, 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 701037MfPH – Publications144B5ACA0, 704019Artificial intelligence859FDEF6, 704045Covid-19859FDEF6, 708812Simulation859FDEF6, 715617Schools859FDEF6 URL: DOI: https://doi.org/10.3390/electronics10141626
| Excerpt / Summary [Electronics, 7 July 2021]
Research on SARS-CoV-2 and its social implications have become a major focus to interdisciplinary teams worldwide. As interest in more direct solutions, such as mass testing and vaccination grows, several studies appear to be dedicated to the operationalization of those solutions, leveraging both traditional and new methodologies, and, increasingly, the combination of both. This research examines the challenges anticipated for preventative testing of SARS-CoV-2 in schools and proposes an artificial intelligence (AI)-powered agent-based model crafted specifically for school scenarios. This research shows that in the absence of real data, simulation-based data can be used to develop an artificial intelligence model for the application of rapid assessment of school testing policies. |
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