Affiliated Series
AGENT Based Modelling for Public Health (ABMfPH) Speaker Series
COVID-19 Task Force Investigators
Kumar Murty - The Fields Institute & University of Toronto
Jianhong Wu - York Unviersity
Charmaine Dean - University of Waterloo
Nicola Bragazzi - York University
Sanyi Tang - Tianyuan Mathematical Center
Julien Arino - Unviersity of Manitoba
Michael Li - University of Alberta
Ali Asgary - York University
Jane Heffernan - York University
Zack McCarthy - York Unviersity
Lydia Bourouiba - Massachusetts Institute of Technology
Adriano Solis - York University
MfPH MEMBERS
Julien Arino (University of Manitoba)
Ali Asgary (York University)
Jacques Bélair (University of Montreal, CRM)
Adalsteinn Brown (University of Toronto)
Jason Brown (Dalhousie University)
Arthur Charpentier (Université du Québec à Montréal)
James Colliander (University of British Columbia, PIMS)
Dongmei Chen (Queen’s University)
Morgan Craig (University of Montreal)
Shengyuan (Michael) Chen (York University)
Charmaine Dean (University of Waterloo)
Jonathan Dushoff (McMaster University)
Ida Ferrara (York University)
David Fisman (University of Toronto)
Ed Furman (York University)
Amy Greer (University of Guelph)
Hélène Guérin (Université du Québec à Montréal)
Jane Heffernan (York University)
Joan Hu (Simon Fraser University)
Amy Hurford (Memorial University of Newfoundland)
Jeanette Jansen (Dalhousie University)
Theodore Kolokolnikov (Dalhousie University)
Jude D. Kong (York University)
Manisha Kulkarni (University of Ottawa)
Patrick Leighton (University of Montreal)
Michael Li (University of Alberta)
Juxin Liu (University of Saskatchewan)
Felicia Magpantay (Queen’s University)
Doug Manuel (Ottawa Hospital Research Instititute)
Sharmistha Mishra (University of Toronto)
Swetaprovo Chaudhuri (University of Toronto)
Manuel Morales (University of Montreal, CRM)
Junling Ma (University of Victoria)
Sajjad Mohammad (National Research Council of Canada)
Seyed Moghadas (York University)
Bouchra Nasri (University of Montreal)
Nick Ogden (Public Health Agency of Canada)
James Ooi (National Research Council of Canada)
Nathaniel Osgood (University of Saskatchewan)
Peter Park (York University)
Lin Wang (University of New Brunswick)
Luc Vinet (University of Montreal, CRM)
Javier Sanchez (University of Prince Edward Island)
Sanjeev Seahra (University of New Brunswick, AARMS)
Luis Seco (University of Toronto)
Chris Soteros (University of Saskatchewan)
Ashleigh Tuite (University of Toronto)
Edward Thommes (Sanofi Pasteur, University of Guelph)
James Watmough (University of New Brunswick)
Cheryl Waldner (University of Saskatchewan)
Michael Wolfson (University of Ottawa)
Mamadou Yauck (Université du Québec à Montréal)
Xiaoqiang Zhao (Memorial University of Newfoundland)
Xingfu Zou (Western University)
Hao Wang (University of Alberta)
Monica Cojocaru (University of Guelph)
Venkata Duvvuri (University of Toronto)
Woldegebriel Assefa Woldegerima (York University)
Suzanna Shoush (University of Toronto)
Ed Furman (York University)
MfPH NEXT GENERATION MEMBERS
Mariah Ahmad (York University)
Mortaza Baky-Haskuee ( York University & The Fields Institute)
Hudson Blue (York University)
Korryn Bodner (University of Toronto)
Gabrielle Brankston (University of Guelph)
Jummy David (York University)
Felix Foutel-Roudier (Université du Québec à Montréal (UQÀM))
Martin Grunnill (York University)
Donglin Han (University of Alberta)
Francis Hu (University of Montreal)
Sana Jahedi (McMaster University)
Patrick Leighton (University of Montreal)
Ao Li (York University)
Xiaoyan Li (University of Saskatchewan)
Ankai Liu (Queen’s University)
Wade McDonald (University of Saskatchewan)
Zahra Mohammadi (University of Guelph)
Mohsen Mousavi (York University)
Dinh Toan Nguyen (Gustave Eiffel University)
Chelsea Nyarko (University of Waterloo)
Ken Peng (University of Waterloo)
Tanya Philippsen (University of Victoria)
Weston Roda (University of Alberta)
Idriss Sekkak (University of Montreal)
Yogita Sharma (University of Victoria)
Manting Wang (University of Victoria)
Richard Zhao (Queen’s University)
Korryn Bodner (University of Toronto)
Leila Amiri (York University)
Shelly Dixit (York University)
Bushra Majeed (York University)
Zach McCarthy (York University)
Tanjima Akhter (University of Alberta)
Xuyuan Wang (University of Alberta)
Russell Milne (University of Alberta)
Brandon Bellows (University of Saskatchewan)
Mohammadali Tofighi (York University)
Arnab Mukherjee (University of Toronto)
Sasha van Katwyk (University of Ottawa)
Oskar Laverny (York University)
Nushrat Nazia (University of Waterloo)
Isam Al-Darabsah (University of Manitoba)
Sungju Moon (McMaster University)
Qiuyi Su (York University)
Zeinab Jamali (University of Saskatchewan)
Yujie Pei (University of Saskatchewan)
Somoyeh Sepahrom (University of Saskatchewan)
Dinh Toan Nguyen (Université du Québec à Montréal)
INTERNATIONAL MEMBERS
Henri Berestycki, École des hautes études en sciences sociales, France
Chris Budd, University of Bath, United Kingdom
Eduardo Massadm, Fundação Getulio Vargas, Rio de Janeiro Brazil.
Alan Hastings, University of California, Davis, United States
Hiroshi Nishiura, Kyoto University, Japan
Jianguo Xu, China CDC and Institute of Public Health of Nankai University, China
STEERING COMMITTEE
Kumar Murty, Chair, Director Fields Institute
Jianhong Wu, Co-PI, LIAM Director, York University
Adalsteinn Brown, Dean, Dalla Lana School of Publich Health, University of Toronto
Jame Colliander, Director, PIMS
Octav Cornea, Director, CRM
Deirdre Haskell, Deputy Director, Fields Institute
Sanjeev Seahra, Director, AARMS
Carolyn Tuohy, University of Toronto
Luc Vinet, Director, CRM
SCIENTIFIC ADVISORY COMMITTEE
Jianhong Wu, Chair, LIAM, York University
Kumar Murty, Fields Institute, Universty of Toronto
Ali Asgary, York University
Julien Arino, University of Manitoba
Jacques Belair, University of Montreal
Michael Chen, York University
Charmaine Dean, University of Waterloo
Jude Dzevela Kong, York University
Jane Marie Heffernan, York University
Tom Hurd, McMaster University
Michael Li, University of Alberta
Junling Ma, University of Victoria
Seyed M Moghadas, York University
Nathaniel Osgood, University of Saskatchawan
James Watmough, University of New Brunswick
RESEARCH MANAGEMENT COMMITTEE
Deirdre Haskell, Chair, Deputy Director, Fields Institute
Marni Mishna, Deputy Director, PIMS
Morales Manuel, Deputy Director, CRM
Franklin Mendivil, Executive Committee, AARMS
France Gagnon, Dean of Research, Dalla Lana School of Public Health, University of Toronto
INAUGURAL PROJECTS
Project 1. Contact Mixing and Optimal Decision Making
Leads: Jianhong Wu (York University, Toronto), Kumar Murty (Fields Institute, Toronto) and Shengyuan Michael Chen (York University, Toronto)
Team Members: Amy Greer, Fred Brauer, Dongmei Chen, Jane Heffernan, Jude Kong, Doug Manuel, Ashleigh Tuite, Michael Wolfson
The project aims to develop a comprehensive modelling approach that integrates key heterogeneities by age, setting, immunization status, geographical locations and a generalized intervention package accounting for evolving pharmaceutical treatment and vaccination, non-pharmaceutical interventions, diagnostic testing, contact tracing, and case isolation. This approach will also be utilized for a broad spectrum of risk assessment, preparedness planning, reopening measures and optimization, scenario analysis and intervention evaluation.
Project 2. Integrative Modelling
Leads: Kumar Murty (Fields Institute, Toronto) and Jianhong Wu (York University, Toronto)
Team Members: Arthur Charpentier, Ida Ferrera, Ed Furman, Joan Hu, Jude Kong, Sharmistha Mishra, Manuel Morales, Bouchra Nasri, Luis Seco, Michael Wolfson, Xingfu Zou
This project aims to develop an integrative framework that explores the impact of public health interventions across a broad spectrum of societal and economic issues, through ‘stitching together’ the various individual models to determine the total effect of the virus on society.
Project 3. Risk Evaluation and Early Detection of Emerging Infectious Disease Outbreaks in Canada
Leads: Junling Ma (University of Victoria, Victoria) and Jude Kong (York University, Toronto)
Members: Arthur Charpentier, Thomas Hurd, Juxin Liu, Manuel Morales, Bouchra Nasri, Ashleigh Tuite, Jianhong Wu
This project will integrate multiple types of data such as environmental, epidemiological, news reports, and search data, and develop novel mathematical, statistical, and big data techniques to a) evaluate the risk of case importation into major Canadian cities though international travel; b) detect and give early warnings to domestic spread for cities with imported cases; and c) evaluate the risk of case spread from these to other regions in Canada through domestic travel.
Project 4. Robust Agent-Based and Network Infectious Disease Models.
Leads: Thomas Hurd (McMaster University, Hamilton) and Ali Asgary (York University, Toronto)
Team Members: Jason Brown, Arthur Charpentier, Helene Guerin, Jane Heffernan, Jeanette Jansen, Nathaniel Osgood, Sanjeev Seahra, Chris Soteros, James Watmough, Michael Wolfson
The “Robust IDM” project will build on the foundations of IDM by developing agent-based and network models. The goal is to develop, expand and refine the agent-based modeling framework, leading to families of models that depart from rigid assumptions like a well-mixed population as adopted in ODE models. To develop for a large scale initiative like MfPH, our agent-based models will follow templates that can share common features such as the underlying social network and transmission settings, and are extendible in many dimensions, as finer scale epidemiological data and new knowledge comes available. In addition to taking advantage of the intrinsic conceptual advantages of transparency, flexibility and scalability, we also develop agent-based methods to address the curse of dimensionality, by combining agent-based methods with a parallel development of network and ODE analytics which make certain kinds of assumptions that lead to dramatic shortcuts in computation time. A well-defined class of network models that can “simulate the agent-based simulations quickly and more accurately than ODE models will also be developed.
Project 5. Mobility Network and Patch Models.
Leads: Julien Arino (University of Manitoba, Winnipeg), Amy Hurford (Memorial University, Newfoundland)
Team Members: Peter Park, Javier Sanchez, Sanjeev Seahra, Lin Wang, Xiaoqiang Zhao, Xingfu Zou
The spatio-temporal spread of infectious diseases involves a succession of transport and importation events, so to better model global spread, we will develop models of both processes, in isolation and together. To do that, we will first constitute a geospatial database on movement, drawing in from a wide variety of public and private sources to obtain a global view of human mobility. We will then consider importation and patch models for infectious disease spread using this transportation data. We will in particular incorporate the multiple modalities that make up mobility, as well as consider the effect of various methods to slow spread.
Project 6. Infection Control during Mass Gathering Events
Leads: Jianhong Wu (York University, Toronto), Edward Thommes (Sanofi)
Team Members: Julien Arino, Ali Asgary, Lydia Bourouiba, Dongmei Chen, Thomas Hurd, Jude Kong, Felicia Magpantay, Ashleigh Tuite, Xiaoqiang Zhao and Sanofi mass gathering infection modeling team
Mass gatherings (MG) have the potential to facilitate global spread of infectious pathogens. Individuals from disease-free areas may acquire the pathogen while at the mass gathering site, which in turn could lead to its translocation in the originally disease-free zones when individuals return home. This project aims to develop model platforms, simulations and analyses, using Hajj and Olympics as case studies, for the need of immunization to ensure mass gathering events held with minimal COVID-19 infection risk. This project involve collaboration with Sanofi Pasteur for its expertise in Health Economics, Regional Disease Epidemiology.
Project 7. Antimicrobial Resistance
Leads: Seyed Moghadas (York University) and Jianhong Wu (York University)
Team members: Nathaniel Osgood, Cheryl Waldner
Infectious diseases may evolve to escape the preventative or therapeutic measures such as vaccines and antimicrobials. Reduced efficacy of vaccines and potentially increased severity of infections caused by these variants may contribute to the demand for patient management and further use of antimicrobial agents. Recent data indicate a significant use of antimicrobial agents for COVID-19 patients, even in the absence of secondary infections, sparking concerns over exacerbation of antimicrobial resistance (AMR). However, cancellations of elective and non-critical surgeries, and the implementation of non-pharmaceutical interventions that has led to the near disappearance of various seasonal infections (e.g., influenza), have collectively reduced the use of antimicrobial agents. The effect of these tradeoffs on the rate of antimicrobial use in different population settings remains unclear. We aim to quantify this effect by considering the role of new variants in the vaccine era of COVID-19 and the potential for altered rates of AMR post-pandemic. By the inclusion of an evolutionary framework into population models of AMR, we will aim to take advantage of linking genetic and epidemiological data, and investigate the effect of various exogenous factors on the secular trend.
Project 8. Contact Tracing
Lead: Jianhong Wu (York University)
Team Members: Helene Guerin, Jeanette Jansen, Kumar Murty, Juxin Liu, Felicia Magpantay, Manuel Morales, Ashleigh Tuite, Mamadou Yauck
Contact tracing has been used as one of the major non-pharmaceutical interventions to counteract the spread of SARS-CoV-2. Efficacy of contact tracing relies not only on the tracing protocol and infrastructure, but also on a concurrent program of diagnosis of symptomatic individuals, in order to detect as many infection chains as possible. This project aims to develop models and analyses that incorporates the processes of diagnosis of symptomatic individuals and contact tracing to address important issues relevant to outbreak control: tracing delays; tracing resource allocation among regions with different prevalence or growth rate; adherence of individuals to isolation and to disclosure of contacts; vaccine coverage levels.
Project 9. Joint Estimation of Parameters in Outbreak Models
Leads: Charmaine Dean (University of Waterloo, Waterloo) and Nathaniel Osgood University of Saskatchewan, Saskatoon)
Team members: Dongmei Chen, Joan Hu, Jeanette Jansen, Theodore Kolokolnikov, Juxin Liu, Felicia Magpantay, Bouchra Nasri, Chris Soteros
This project aims to address various issues relevant to joint estimation of parameters in epidemic models. We will 1). Compile, contrast and develop data fitting techniques to address common issue of incomplete and imperfect covariate information when fitting many types of mechanistic models to data; 2). Use a joint model framework to analyze the underlying correlation between key time series processes (such as daily number of cases, hospitalizations and deaths) and compare waves in a way that can give insight into how deaths and hospitalizations are changing in light of variants and vaccinations; 3). Develop change-point models to measure the effectiveness of public health interventions that changes over time according to intervention timelines; 4). Investigate the potential for using deep learning and ensemble classifier methods for classification of capacity utilization exceedance, when using Particle Markov Chain Monte Carlo methods to support joint estimation not only of model states over time, but also of parameter values.
Project 10. Dynamic Bifurcation and Scenario Analyses
Leads: Jacques Bélair (University of Montreal, Montreal) and Michael Li (University of Alberta, Edmonton)
Team Members: Julien Arino, Felicia Magpantay, Jianhong Wu, Xiaoqiang Zhao and Xingfu Zou
This project aims to deliver a MfPH Library of important model frameworks (discrete vs continuous, deterministic vs stochastic, homogeneous vs heterogeneous and structured); examine their respective strengths and limitations in association with those issues addressed in other MfPH projects; link the bifurcation phenomena to observed patterns of COVID-19 pandemic in Canada and globally; and distinguish finite-time behaviour optimisation from asymptotic behaviour (infinite time horizon). We will also identify and mitigate non identifiability to direct surveillance or model design to avoid the situation that a bifurcation parameter of importance for scenario analyses cannot be reliably estimated using current surveillances and models. Efficient software codes for model fitting with data that ensure convergence in the presence of non identifiability will also be developed.
Project 11. Immune response, immune memory and cross-immunity
Leads: Jane Heffernan (York University), James Watmough (University of New Brunswick) and Jianhong Wu (York University)
Team Members: Jacque Bélair, Morgan Craig, Jonathan Dushoff, Thomas Hurd, Jude Kong, Sajjad Mohammad, James Ooi, and Lin Wang.
This project aims to develop and analyze a suite of models of an immune response to an emergent infectious pathogen incorporating immune memory generated by prior infection by related pathogens. Such pre-existing immunity has a large influence on the potential for EID spread. Previous infection by one of the common coronaviruses is expected to reduce susceptibility to SARS-CoV-2, and previous infection by SARS-CoV-2 is known to influence a person's response to vaccination and their susceptibility to emerging variants.
Project 12. Pathogen Contamination and Spread Control during Food-Processing
Lead: Hao Wang (University of Alberta) and Jianhong Wu (York University)
Pathogens causing infectious diseases can originate from food products and/or wastewater, and pathogen cross-contamination and spread within the food-processing facilities and during the food-processing and transportation can potentially lead to a disease outbreak and costly product recalls. We will develop and analyze novel deterministic and stochastic simulation models to investigate necessary conditions under which an infectious disease has emerged from food or wastewater to humans and investigate its initial and transient dynamics to inform policy makers in public health to make necessary interventions. We will also develop machine learning techniques to train these models on data of food-borne disease to predict critical transition patterns and detect early warning signals around transition boundaries for suggesting early intervention strategies of food safety and disease control.
Project 13. Phylodynamic Modelling of Infectious Diseases
Lead: Venkata R. Duvvuri (Public Health Ontario)
Team Members: Samir Patel (Public Health Ontario), Jianhong Wu (York University)
The COVID-19 pandemic highlighted a myriad of opportunities and challenges in practicing public health genomics. The use of pathogen genomic data coupled with phylodynamic approaches in understanding infectious disease outbreaks has received greater attention. In this project, we aim to develop phylodynamic and phylogeographic models to a) characterize the early spread of the epidemic that include insights into the origin, transmission potential, transmission routes, and genetic diversity of the pathogen; b) understand pathogen spread across spatiotemporal scales within and between geographical locations, and determine the factors that have driven pathogen spread. These phylodynamic approaches utilize time-stamped pathogen genomic sequences; and associated meta-data. Overall, the project's goal is to translate pathogen surveillance into effective public health responses and interventions.
Project 14. Long-Term Effects of Infectious Diseases
Lead: Nathaniel Osgood (University of Saskatchewan)
TBA
Project 15. Human Behaviour in Epidemiological Modeling
Lead: Jacques Belair (University of Montreal), Joan Hu (Simon Fraser University)
Team Members: Roxane de la Sablonnière (University of Montreal)
This project aims to understand the impact of the COVID-19 pandemic on the Canadian population through 3 aspects: adherence to health measures (including NPIs), social cohesion and well-being. Participants were asked about more than a hundred variables covering concepts as diverse as emotions, behaviors, attitudes and cognitions related to the COVID-19 pandemic. The goal of the present project is to develop compartmental mathematical models of SEAIRV type incorporating behavioural parameters and to identify the motivating factors leading to either persistent adherence or "waning" over time of this adherence. Factors such as attitude towards NPIs and perceived levels of risks (either in neighboring communities, or as perceived through media reports) will be used to stratify a population along the most homogeneous classes (reflecting, e.g., a stronger and more persistent adherence in elderly individuals).
EOC Modeling. Simulations and Exercises
Lead: Ali Asgary (York University, Toronto)
Team members: David Fisman, Amy Greer, Nathaniel Osgood, Ashleigh Tuite, Jianhong Wu
MfPH will utilize the Advanced Disaster, Emergency and Rapid Simulation Facility (ADERSIM) facility housed at York University to develop Emergency Operations Center (EOC) modeling, simulation and exercises. The Network will organize EOC-level expert panel reviews (EPR) for some thematic research projects in general, and COVID-19 modeling in particular. These EPRs will be similar to the decision making process at a typical public health EOC Center (EOC). Network members not participating in the project and experts outside the MfPH network will be brought together with decision makers and relevant end-users to test if thematic project outcomes can be incorporated into public health decision making processes. The first year will focus on: 1) examining how the EOC at different public health agencies were activated and operated during the pandemic; 2) how decisions were made, publicized and so on; 3) developing sample standard exercise scenarios based on the current situation for future training and applications.
PUBLICATIONS:
Full List
Publication Count: 137
Ahmed, H., Cargill, T., Nicola Luigi Bragazzi, & Jude Dzevela Kong. (2022). Dataset of non-pharmaceutical interventions and community support measures across Canadian universities and colleges during COVID-19 in 2020. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1066654
Alavinejad, M., Mellado, B., Asgary, A., Mbada, M., Mathaha, T., Lieberman, B., Stevenson, F., Tripathi, N., Swain, A. K., Orbinski, J., Wu, J., & Kong, J. D. (2022). Management of hospital beds and ventilators in the Gauteng province, South Africa, during the COVID-19 pandemic. PLOS Global Public Health, 2(11), e0001113. https://doi.org/10.1371/journal.pgph.0001113
Alavinejad, M., Mellado, B., Asgary, A., Mbada, M., Mathaha, T., Lieberman, B., Stevenson, F., Tripathi, N., Swain, A. K., Orbinski, J., Wu, J., & Kong, J. D. (2022). Management of Healthcare Resources in the Gauteng Province, South Africa, During the COVID-19 Pandemic. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4049177
Arino, J., & Milliken, E. (2022). Bistability in deterministic and stochastic SLIAR-type models with imperfect and waning vaccine protection. Journal of Mathematical Biology, 84(7). https://doi.org/10.1007/s00285-022-01765-9
Arino, J., & Milliken, E. (2022). Effect of Movement on the Early Phase of an Epidemic. Bulletin of Mathematical Biology, 84(11). https://doi.org/10.1007/s11538-022-01077-5
Aruffo, E., Yuan, P., Tan, Y., Evgenia Gatov, Gournis, E., Collier, S. M., Ogden, N., eacutelair, J. B., & Zhu, H. (2021). Community structured model for vaccine strategies to control COVID19 spread: a mathematical study. MedRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2021.01.25.21250505
Aruffo, E., Yuan, P., Tan, Y., Gatov, E., Moyles, I., Bélair, J., Watmough, J., Collier, S., Arino, J., & Zhu, H. (2022). Mathematical modelling of vaccination rollout and NPIs lifting on COVID-19 transmission with VOC: a case study in Toronto, Canada. BMC Public Health, 22(1). https://doi.org/10.1186/s12889-022-13597-9
Asgary, A., Blue, H., Cronemberger, F., & Ni, M. (2022). Simulating a Hockey Hub COVID-19 Mass Vaccination Facility. Healthcare, 10(5), 843. https://doi.org/10.3390/healthcare10050843
Asgary, A., Blue, H., Solis, A. O., McCarthy, Z., Najafabadi, M., Tofighi, M. A., & Wu, J. (2022). Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach. International Journal of Environmental Research and Public Health, 19(5), 2635. https://doi.org/10.3390/ijerph19052635
Asgary, A., Solis, A. O., Khan, N., Janithra Wimaladasa, & Maryam Shafiei Sabet. (2023). Spatiotemporal Analysis of Emergency Calls during the COVID-19 Pandemic: Case of the City of Vaughan. Urban Science, 7(2), 62–62. https://doi.org/10.3390/urbansci7020062
Avusuglo, W. S., Mosleh, R., Tedi Ramaj, Li, A., Sileshi Sintayehu Sharbayta, Abdoul Aziz Fall, Srijana Ghimire, Shi, F., Lee, J. K. H., Thommes, E. W., Shin, T., & Wu, J. (2023). Workplace absenteeism due to COVID-19 and influenza across Canada: A mathematical model. Journal of Theoretical Biology, 111559–111559. https://doi.org/10.1016/j.jtbi.2023.111559
Avusuglo, W., Han, Q., Woldegerima, W. A., Bragazzi, N. L., Ahmadi, A., Asgary, A., Wu, J., Orbinski, J., & Kong, J. D. (2022). COVID-19 and Malaria Co-Infection: Do Stigmatization and Self-Medication Matter? A Mathematical Modelling Study for Nigeria. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4090040
Baky Haskuee, M., Efendiev, M., Murty, VK. (2024). Containment Policies, Behaviour and Dynamics of the Pandemic. Advances in Mathematical Sciences and Applications, 33(2), pp. 419-457. https://mcm-www.jwu.ac.jp/~aikit/AMSA/pdf/abstract/2024/Top_2024_026.pdf
Bednarski, S., Cowen, L., Ma, J., Philippsen, T., van, & Wang, M. (2022). A contact tracing SIR model for randomly mixed populations. Journal of Biological Dynamics, 16(1), 859–879. https://doi.org/10.1080/17513758.2022.2153938
Behzadifar, M., Aalipour, A., Kehsvari, M., Darvishi Teli, B., Ghanbari, M. K., Gorji, H. A., Sheikhi, A., Azari, S., Heydarian, M., Ehsanzadeh, S. J., Kong, J. D., Ahadi, M., & Bragazzi, N. L. (2022). The effect of COVID-19 on public hospital revenues in Iran: An interrupted time-series analysis. PLOS ONE, 17(3), e0266343. https://doi.org/10.1371/journal.pone.0266343
Bragazzi, N. L., Garbarino, S., Puce, L., Trompetto, C., Marinelli, L., Currà, A., Jahrami, H., Trabelsi, K., Mellado, B., Asgary, A., Wu, J., & Kong, J. D. (2022). Planetary sleep medicine: Studying sleep at the individual, population, and planetary level. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1005100
Bragazzi, N. L., Kong, J. D., & Wu, J. (2022). Integrated epidemiological, clinical, and molecular evidence points to an earlier origin of the current monkeypox outbreak and a complex route of exposure. Journal of Medical Virology. https://doi.org/10.1002/jmv.28244
Bragazzi, N. L., Kong, J. D., & Wu, J. (2022). Is monkeypox a new, emerging sexually transmitted disease? A rapid review of the literature. Journal of Medical Virology. https://doi.org/10.1002/jmv.28145
Bragazzi, N. L., Kong, J. D., Mahroum, N., Tsigalou, C., Khamisy-Farah, R., Converti, M., & Wu, J. (2022). Epidemiological trends and clinical features of the ongoing monkeypox epidemic: a preliminary pooled data analysis and literature review. Journal of Medical Virology. https://doi.org/10.1002/jmv.27931
Bragazzi, N. L., Woldegerima, W. A., Iyaniwura, S. A., Han, Q., Wang, X., Shausan, A., Badu, K., Okwen, P., Prescod, C., Westin, M., Omame, A., Converti, M., Mellado, B., Wu, J., & Kong, J. D. (2022). Knowing the unknown: The underestimation of monkeypox cases. Insights and implications from an integrative review of the literature. Frontiers in Microbiology, 13. https://doi.org/10.3389/fmicb.2022.1011049
Chen, R., Saeid Safiri, Masoud Behzadifar, Jude Dzevela Kong, Mohamed Sami Zguira, Nicola Luigi Bragazzi, Zhong, W., & Zhang, W. (2022). Health Effects of Metabolic Risks in the United States From 1990 to 2019. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.751126
Choi, Y.-J., Leung, K., Wu, J. S., Lin, L., & Larson, H. (2023). Identifying Vaccine-hesitant Subgroups in the Western Pacific: A Latent Class Analysis. Research Square (Research Square). https://doi.org/10.21203/rs.3.rs-2702702/v1
Coudeville, L., Amiche, A., Rahman, A., Arino, J., Tang, B., Jollivet, O., Dogu, A., Thommes, E., & Wu, J. (2022). Disease transmission and mass gatherings: a case study on meningococcal infection during Hajj. BMC Infectious Diseases, 22(1). https://doi.org/10.1186/s12879-022-07234-4
David, J., Bragazzi, N. L., Scarabel, F., McCarthy, Z., & Wu, J. (2022). Non-pharmaceutical intervention levels to reduce the COVID-19 attack ratio among children. Royal Society Open Science, 9(3). https://doi.org/10.1098/rsos.211863
Dushoff, C., Dushoff, D. J., Dushoff, J., Ogden, N. H., Li, M., Knox, N., Van Domselaar, G., Franklin, K., Jolly, G., & Otto, S. P. (2022). The need for linked genomic surveillance of SARS-CoV-2. Canada Communicable Disease Report, 48(4), 131–139. https://doi.org/10.14745/ccdr.v48i04a03
E. Joe Moran, Martignoni, M. M., Lecomte, N., Leighton, P., & Hurford, A. (2023). When host populations move north, but disease moves south: Counter-intuitive impacts of climate change on disease spread. Theoretical Ecology, 16(1), 13–19. https://doi.org/10.1007/s12080-022-00551-z
Estimating the transmission dynamics of Omicron in Beijing, November to December 2022
Fan, G., Li, J., Bélair, J., & Zhu, H. (2023). Delayed Model for the Transmission and Control of COVID-19 with Fangcang Shelter Hospitals. Siam Journal on Applied Mathematics, 83(1), 276–301. https://doi.org/10.1137/21m146154x
Feng, S., Zhang, J., Li, J., Luo, X.-F., Zhu, H., Li, M. Y., & Jin, Z. (2022). The Impact of Quarantine and Medical Resources on the Control of COVID-19 in Wuhan based on a Household Model. Bulletin of Mathematical Biology, 84(4), 47. https://doi.org/10.1007/s11538-021-00989-y
Fields, R., Humphrey, L., Flynn-Primrose, D., Mohammadi, Z., Nahirniak, M., Thommes, E. W., & Cojocaru, M. G. (2021). Age-stratified transmission model of COVID-19 in Ontario with human mobility during pandemic’s first wave. Heliyon, 7(9), e07905. https://doi.org/10.1016/j.heliyon.2021.e07905
Fitzpatrick MC, Moghadas SM, Vilches TN, Shah A, Pandey A, Galvani AP, Estimated US pediatric hospitalizations and school absenteeism associated With accelerated COVID-19 bivalent booster vaccination, JAMA Network Open 2023; 6(5): e2313586.
Flynn-Primrose, D. , Hoover, N. , Mohammadi, Z. , Hung, A. , Lee, J. , Tomovici, M. , Thommes, E. , Neame, D. and Cojocaru, M. (2022) Meaningful Contact Estimates among Children in a Childcare Centre with Applications to Contact Matrices in Infectious Disease Modelling. Journal of Applied Mathematics and Physics, 10, 1525-1546. doi: 10.4236/jamp.2022.105107
Foutel-Rodier, F., Charpentier, A., & Guérin, H. (2023, June 23). Optimal Vaccination Policy to Prevent Endemicity: A Stochastic Model. ArXiv.org. https://doi.org/10.48550/arXiv.2306.13633
G. Wade McDonald, & Osgood, N. D. (2023). Agent-Based Modeling and its Tradeoffs: An Introduction & Examples. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.2304.08497
Grunnill, M., Arino, J., McCarthy, Z., Nicola Luigi Bragazzi, Laurent Coudeville, Thommes, E. W., Amine Amiche, Ghasemi, A., Bourouiba, L., Mohammadali Tofighi, Asgary, A., Mortaza Baky-Haskuee, & Wu, J. (2023). Modelling Disease Mitigation at Mass Gatherings: A Case Study of COVID-19 at the 2022 FIFA World Cup. MedRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2023.03.27.23287214
Guérin, H., Nguyen, D.-T., & Tran, V.-C. (2022, December 20). Strong uniform convergence of Laplacians of random geometric and directed kNN graphs on compact manifolds. ArXiv.org. https://doi.org/10.48550/arXiv.2212.10287
He, G., Zeng, F., Xiao, J., Zhao, J., Liu, T., Hu, J., Zhang, S., Lin, Z., Zhu, H., Liu, D., Kang, M., Zhong, H., Li, Y., Sun, L., Yang, Y., Li, Z., Rong, Z., Zeng, W., Li, X., & Zhu, Z. (2022). When and How to Adjust Non-Pharmacological Interventions Concurrent with Booster Vaccinations Against COVID-19 — Guangdong, China, 2022. China CDC Weekly, 4(10), 199–206. https://doi.org/10.46234/ccdcw2022.048
Hempel, K., McDonald, W., Osgood, N. D., Fisman, D., Halperin, S. A., Crowcroft, N., Klein, N. P., Rohani, P., & Doroshenko, A. (2023). Evaluation of the effectiveness of maternal immunization against pertussis in Alberta using agent-based modeling: A Canadian immunization research network study. Vaccine. https://doi.org/10.1016/j.vaccine.2022.12.071
Hillmer, M. P., Feng, P., McLaughlin, J. R., Murty, V. K., Sander, B., Greenberg, A., & Brown, A. D. (2021). Ontario’s COVID-19 Modelling Consensus Table: mobilizing scientific expertise to support pandemic response. Canadian Journal of Public Health. https://doi.org/10.17269/s41997-021-00559-8
Hu, L., Shi, M., Li, M., & Ma, J. (2023). The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China. PLOS ONE, 18(5), e0285937–e0285937. https://doi.org/10.1371/journal.pone.0285937
Hurford, A., & Watmough, J. (2020). Don’t wait, re-escalate: delayed action results in longer duration of COVID-19 restrictions. MedRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2020.11.04.20226316
Hurford, A., Martignoni, M. M., Loredo-Osti, J. C., Anokye, F., Arino, J., Husain, B. S., Gaas, B., & Watmough, J. (2023). Pandemic modelling for regions implementing an elimination strategy. Journal of Theoretical Biology, 561, 111378. https://doi.org/10.1016/j.jtbi.2022.111378
Hurford, A., Rahman, P., & Loredo-Osti, J. C. (2021). Modelling the impact of travel restrictions on COVID-19 cases in Newfoundland and Labrador. Royal Society Open Science, 8(6), 202266. https://doi.org/10.1098/rsos.202266
Idriss Sekkak, Jude Dzevela Kong, & Mohamed El Fatini. (2022). Containing and Managing an Emerging Disease Outbreak: A Stochastic Modelling Approach. Social Science Research Network. https://doi.org/10.2139/ssrn.4040246
Idriss Sekkak, Nasri, B., Rémillard, B., Jude Dzevela Kong, & Mohamed El Fatini. (2022). A Stochastic Analysis of a Siqr Epidemic Model With Short and Long-term Prophylaxis. Research Square (Research Square). https://doi.org/10.21203/rs.3.rs-1762043/v1
Iyaniwura, S. A., Musa Rabiu, & Jude Dzevela Kong. (2023). A generalized distributed delay model of COVID-19: An endemic model with immunity waning. Mathematical Biosciences and Engineering, 20(3), 5379–5412. https://doi.org/10.3934/mbe.2023249
Iyaniwura, S. A., Rabiu, M., David, J. F., & Kong, J. D. (2022). The basic reproduction number of COVID-19 across Africa. PLOS ONE, 17(2), e0264455. https://doi.org/10.1371/journal.pone.0264455
Jalal Possik, Asgari, A., Solis, A. O., Zacharewicz, G., Shafiee, M., Najafabadi, M. M., Nazanin Nadri, Guimaraes, A. S., Hossein Iranfar, Ma, P., Lee, C. M., Mohammadali Tofighi, Mahmoud Aarabi, Gorecki, S., & Wu, J. (2023). An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive Care Unit. IEEE Transactions on Engineering Management, 70(8), 2931–2943. https://doi.org/10.1109/tem.2022.3195813
Jalal Possik, Azar, D., Solis, A. O., Asgary, A., Zacharewicz, G., Karami, A., Mohammadali Tofighi, Najafabadi, M. M., Shafiee, M., Merchant, A. A., Mahmoud Aarabi, & Wu, J. (2022). A distributed digital twin implementation of a hemodialysis unit aimed at helping prevent the spread of the Omicron COVID-19 variant. HAL (Le Centre Pour La Communication Scientifique Directe). https://doi.org/10.1109/ds-rt55542.2022.9932047
Jing, S., Milne, R., Wang, H., & Xue, L. (2023). Vaccine hesitancy promotes emergence of new SARS-CoV-2 variants. 570, 111522–111522. https://doi.org/10.1016/j.jtbi.2023.111522
Kaur, M., Nicola Luigi Bragazzi, Heffernan, J. M., Tsasis, P., Wu, J., & Jude Dzevela Kong. (2023). COVID-19 in Ontario Long-term Care Facilities Project, a manually curated and validated database. Frontiers in Public Health, 11. https://doi.org/10.3389/fpubh.2023.1133419
Kazemi, M., Bragazzi, N. L., & Kong, J. D. (2021). Assessing Inequities in COVID-19 Vaccine Roll-Out Strategy Programs: A Cross-Country Study Using a Machine Learning Approach. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3914835
Kim, S., Athar, S., LI, Y., S. Koumarianos, Cheng, T., Amiri, L., W. Avusuglo, W.A. Woldegerima, Fall, A., John-Baptiste, A., Diener, A., & Wu, J. (2022). Assessing the epidemiological and economic impact of alternative vaccination strategies: a modeling study. International Journal of Infectious Diseases, 116, S60–S60. https://doi.org/10.1016/j.ijid.2021.12.142
Kolokolnikov, T., & Iron, D. (2021). Law of mass action and saturation in SIR model with application to Coronavirus modelling. Infectious Disease Modelling, 6, 91–97. https://doi.org/10.1016/j.idm.2020.11.002
Kong, Jude & Bragazzi, Nicola & Movhedi, Zahra & Wu, Jianhong. (2022). The monkeypox outbreak and the risk of a racist media coverage. Journal of Medical Virology
Lee, K.Y., Dabak, S.V., Kong, V.H. et al. Effectiveness of chatbots on COVID vaccine confidence and acceptance in Thailand, Hong Kong, and Singapore. npj Digit. Med. 6, 96 (2023). https://doi.org/10.1038/s41746-023-00843-6
Leung, K., Lam, T. T. Y., & Wu, J. T. (2023). Controlling avian influenza. BMJ, 380, p560. https://doi.org/10.1136/bmj.p560
Leung, K., Lin, L., Elad Yom-Tov, Karolien Poels, Lee, K., Larson, H. J., Leung, G. M., & Wu, J. T. (2023). Volatility and heterogeneity of vaccine sentiments means continuous monitoring is needed when measuring message effectiveness. Research Square (Research Square). https://doi.org/10.21203/rs.3.rs-2590646/v1
Li A, Wang Z, Moghadas SM, Modelling the impact of timelines of testing and isolation on disease control, Infectious Disease Modelling 8: 58-71.
Li, M., Dushoff, J., David, & Bolker, B. M. (2022). Evaluating undercounts in epidemics: response to Maruotti et al. 2022. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.2209.11334
Li, M., Ling, Y., & Ma, J. (2023). The dynamics of the risk perception on a social network and its effect on disease dynamics. Infectious Disease Modelling, 8(3), 632–644. https://doi.org/10.1016/j.idm.2023.05.006
Li, M., Zhai, R., & Ma, J. (2023). The effects of disease control measures on the reproduction number of COVID-19 in British Columbia, Canada. Mathematical Biosciences and Engineering, 20(8), 13849–13863. https://doi.org/10.3934/mbe.2023616
Li, Z., Zhao, J., Zhou, Y., Liu, T., Liu, Q., Zhu, H., & Zhu, G. (2023). Adaptive behaviors and vaccination on curbing COVID-19 transmission: Modeling simulations in eight countries. Journal of Theoretical Biology, 559, 111379–111379. https://doi.org/10.1016/j.jtbi.2022.111379
Lieberman, B., Kong, J.D., Gusinow, R. et al. Big data- and artificial intelligence-based hot-spot analysis of COVID-19: Gauteng, South Africa, as a case study. BMC Med Inform Decis Mak 23, 19 (2023). https://doi.org/10.1186/s12911-023-02098-3
Liu, A., & Magpantay, G. (2022). A Quantification of Long Transient Dynamics. QSpace (Queen’s University Library), 82(2), 381–407. https://doi.org/10.1137/20m1367131
Liu, A., Magpantay, G., & Abdella, K. (2023). A framework for long-lasting, slowly varying transient dynamics. Mathematical Biosciences and Engineering, 20(7), 12130–12153. https://doi.org/10.3934/mbe.2023540
Majeed, B., Jummy Funke David, Nicola Luigi Bragazzi, McCarthy, Z., Grunnill, M., Heffernan, J. M., Wu, J., & Woldegebriel Assefa Woldegerima. (2023). Mitigating co-circulation of seasonal influenza and COVID-19 pandemic in the presence of vaccination: A mathematical modeling approach. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1086849
Martignoni, M. M., Mohammadi, Z., J. Concepción Loredo-Osti, & Hurford, A. (2023). Extensive SARS-CoV-2 testing reveals BA.1/BA.2 asymptomatic rates and underreporting in school children. MedRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2023.01.15.23284579
Martignoni, M. M., Rahman, P., & Hurford, A. (2021). Rotational worker vaccination provides indirect protection to vulnerable groups in regions with low COVID-19 prevalence. MedRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2021.10.05.21264557
Martignoni, M. M., Renault, J., Baafi, J., & Hurford, A. (2022). Downsizing of COVID-19 contact tracing in highly immune populations. PLOS ONE, 17(6), e0268586–e0268586. https://doi.org/10.1371/journal.pone.0268586
McCarthy, Z., Xiao, Y., Scarabel, F., Tang, B., Bragazzi, N. L., Nah, K., Heffernan, J. M., Asgary, A., Murty, V. K., Ogden, N. H., & Wu, J. (2020). Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions. Journal of Mathematics in Industry, 10(1). https://doi.org/10.1186/s13362-020-00096-y
Mohammadi, Z., Cojocaru M, Arino, J., & Hurford, A. (2023). Importation models for travel-related SARS-CoV-2 cases reported in Newfoundland and Labrador during the COVID-19 pandemic. https://doi.org/10.1101/2023.06.08.23291136
Mohammadi, Z., Cojocaru, M. G., & Thommes, E. W. (2022). Human behaviour, NPI and mobility reduction effects on COVID-19 transmission in different countries of the world. BMC Public Health, 22(1). https://doi.org/10.1186/s12889-022-13921-3
Moyles, I., Heffernan, J. M., & Korosec, C. S. (2022). Determination of significant immunological timescales from mRNA-LNP-based vaccines in humans. MedRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2022.07.25.22278031
Nguyen, D.-T. (2022, March 16). Scaling limit of the collision measures of multiple random walks. ArXiv.org. https://doi.org/10.48550/arXiv.2203.08523
Nia, Z. M., Ahmadi, A., Bragazzi, N. L., Woldegerima, W. A., Mellado, B., Wu, J., Orbinski, J., Asgary, A., & Kong, J. D. (2022). A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments. PLOS ONE, 17(8), e0272208. https://doi.org/10.1371/journal.pone.0272208
Nia, Z. M., Asgary, A., Bragazzi, N., Mellado, B., Orbinski, J., Wu, J., & Kong, J. (2022). Nowcasting unemployment rate during the COVID-19 pandemic using Twitter data: The case of South Africa. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.952363
Nia, Z. M., Bragazzi, N. L., Wu, J., & Kong, J. D. (2023). A Twitter dataset for Monkeypox, May 2022. Data in Brief, 48, 109118. https://doi.org/10.1016/j.dib.2023.109118
Nicola Luigi Bragazzi, Qing Kai Han, Iyaniwura, S. A., Omame, A., Aminath Shausan, Wang, X., Woldegebriel Assefa Woldegerima, Wu, J., & Jude Dzevela Kong. (2023). Adaptive changes in sexual behavior in the high‐risk population in response to human monkeypox transmission in Canada can help control the outbreak: insights from a two‐group, two‐route epidemic model. Journal of Medical Virology, 95(4). https://doi.org/10.1002/jmv.28575
Nicola Luigi Bragazzi, Qing Kai Han, Iyaniwura, S. A., Omame, A., Aminath Shausan, Wang, X., Woldegebriel Assefa Woldegerima, Wu, J., & Jude Dzevela Kong. (2023). Adaptive changes in sexual behavior in the high‐risk population in response to human monkeypox transmission in Canada can help control the outbreak: insights from a two‐group, two‐route epidemic model. Journal of Medical Virology, 95(4). https://doi.org/10.1002/jmv.28575
Nicola Luigi Bragazzi, Qing Kai Han, Iyaniwura, S. A., Omame, A., Aminath Shausan, Wang, X., Woldegebriel Assefa Woldegerima, Wu, J., & Jude Dzevela Kong. (2023). Adaptive changes in sexual behavior in the high‐risk population in response to human monkeypox transmission in Canada can help control the outbreak: insights from a two‐group, two‐route epidemic model. Journal of Medical Virology, 95(4). https://doi.org/10.1002/jmv.28575
Nourbakhsh, S., Fazil, A., Li, M., Mangat, C. S., Peterson, S. W., Daigle, J., Langner, S., Shurgold, J., D’Aoust, P., Delatolla, R., Mercier, E., Pang, X., Lee, B. E., Stuart, R., Wijayasri, S., & Champredon, D. (2022). A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities. Epidemics, 39, 100560. https://doi.org/10.1016/j.epidem.2022.100560
Pandey A, Wells CR, StadnytskyiV, Sah P, Moghadas SM, Marathe M, Singer BH, Nesterova O, Galvani AP, Disease burden among Ukrainians forcibly displaced by the 2022 Russian invasion, Proceedings of the National Academy of Sciences USA 120(8): e2215424120.
Parker, M. R. P., Li, Y., Elliott, L. T., Ma, J., & Cowen, L. L. E. (2021). Under‐reporting of COVID‐19 in the Northern Health Authority region of British Columbia. Canadian Journal of Statistics, 49(4), 1018–1038. https://doi.org/10.1002/cjs.11664
Pavithra Daulagala, Mann, B. R., Leung, K., Lau, E. H. Y., Yung, L., Lei, R., Nizami, S. I. N., Wu, J. T., Chiu, S. S., Daniels, R. S., Wu, N. C., Wentworth, D. E., Peiris, M., & Yen, H.-L. (2023). Imprinted Anti-Hemagglutinin and Anti-Neuraminidase Antibody Responses after Childhood Infections of A(H1N1) and A(H1N1)pdm09 Influenza Viruses. MBio, 14(3). https://doi.org/10.1128/mbio.00084-23
Peng, K., Renouf, E., Dean, C. B., Hu, X., Delatolla, R., & Manuel, D. (2023). An exploration of the relationship between wastewater viral signals and COVID-19 hospitalizations in Ottawa, Canada. Infectious Disease Modelling, 8(3), 617–631. https://doi.org/10.1016/j.idm.2023.05.011
Penney, M. D., Yargic, Y., Smolin, L., Thommes, E. W., Anand, M., & Bauch, C. T. (2021). “Hot-spotting” to improve vaccine allocation by harnessing digital contact tracing technology: An application of percolation theory. PLOS ONE, 16(9), e0256889. https://doi.org/10.1371/journal.pone.0256889
Puce, L., Trabelsi, K., Ammar, A., Jabbour, G., Marinelli, L., Mori, L., Kong, J. D., Tsigalou, C., Cotellessa, F., Schenone, C., Samanipour, M. H., Biz, C., Ruggieri, P., Trompetto, C., & Bragazzi, N. L. (2022). A tale of two stories: COVID-19 and disability. A critical scoping review of the literature on the effects of the pandemic among athletes with disabilities and para-athletes. Frontiers in Physiology, 13, 967661. https://doi.org/10.3389/fphys.2022.967661
Qian, W., Stanley, K. G., & Osgood, N. D. (2023). Impacts of observation frequency on proximity contact data and modeled transmission dynamics. PLOS Computational Biology, 19(2), e1010917–e1010917. https://doi.org/10.1371/journal.pcbi.1010917
Qing Kai Han, Nicola Luigi Bragazzi, Asgary, A., Orbinski, J., Wu, J., & Jude Dzevela Kong. (2022). Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa. Research Square (Research Square). https://doi.org/10.21203/rs.3.rs-1708820/v1
Rong, X., Chu, H., Yang, L., Tan, S., Yang, C., Yuan, P., Tan, Y., Zhou, L., Liu, Y., Zhen, Q., Wang, S., Fan, M., & Zhu, H. (2023). Recursive Zero-COVID model and quantitation of control efforts of the Omicron epidemic in Jilin province. Infectious Disease Modelling, 8(1), 11–26. https://doi.org/10.1016/j.idm.2022.11.007
Rong, X., Chu, H., Yang, L., Tan, S., Yang, C., Yuan, P., Tan, Y., Zhou, L., Liu, Y., Zhen, Q., Wang, S., Fan, M., & Zhu, H. (2023). Recursive Zero-COVID model and quantitation of control efforts of the Omicron epidemic in Jilin province. Infectious Disease Modelling, 8(1), 11–26. https://doi.org/10.1016/j.idm.2022.11.007
Sah P, Fitzpatrick MC, Zimmer CF, Abdollahi E, Juden-Kelly L, Moghadas SM, Singer BH, Galvani AP, Asymptomatic COVID-19 infection: a systematic review and meta-analysis, Proceedings of the National Academy of Sciences USA 118; 34:e2109229118.
Sah P, MoghadasSM, Vilches TN, ShoukatA, SingerBH, HotezPJ, SchneiderEC, Galvani AP, Implications of suboptimal COVID-19 vaccination coverage in Florida and Texas, Lancet Infectious Diseases https://doi.org/10.1016/S1473-3099(21)00620-4
Sah P, VilchesTN,MoghadasSM, Gondi S, SchneiderEC, SingerJ, Chokshi DA, Galvani AP, Return on investment of the COVID-19 vaccination campaign in New York City, JAMA Network Open 5(11):e2243127.
Sah P, Vilches TN, Pandey A, SchneiderEC,MoghadasSM, Galvani AP, Estimating the impact of vaccination on reducing COVID-19 burden in the United States: December 2020 to March 2022, Journal of Global Health 12:03062.
Solis, A. O., Asgary, A., Khan, N., Janithra Wimaladasa, & Maryam Shafiei Sabet. (2022). Emergency Calls in the City of Vaughan (Canada) During the COVID-19 Pandemic: A Spatiotemporal Analysis. RiuNet (Universitat Politècnica de València). https://doi.org/10.4995/carma2022.2022.15087
Song, H., Liu, F., Li, F., Cao, X., Wang, H., Jia, Z., Zhu, H., Li, M. Y., Lin, W., Yang, H., Hu, J., & Jin, Z. (2021). Modeling the second outbreak of COVID-19 with isolation and contact tracing. Discrete & Continuous Dynamical Systems - B, 0(0), 0. https://doi.org/10.3934/dcdsb.2021294
Svetozar Zarko Valtchev, Asgary, A., Chen, M., Felippe Cronemberger, Najafabadi, M. M., Cojocaru, M., & Wu, J. (2021). Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data. Electronics, 10(14), 1626–1626. https://doi.org/10.3390/electronics10141626
Tan, Y., Yuan, P., Moyles, I., Heffernan, J. M., Watmough, J., Tang, S., & Zhu, H. (2023). The stochasticity in adherence to nonpharmaceutical interventions and booster doses and the mitigation of COVID-19. 16(3&4), 602–626. https://doi.org/10.3934/dcdss.2023044
Tang, B., Zhang, X., Li, Q., Bragazzi, N. L., Golemi-Kotra, D., & Wu, J. (2022). The minimal COVID-19 vaccination coverage and efficacy to compensate for a potential increase of transmission contacts, and increased transmission probability of the emerging strains. BMC Public Health, 22(1). https://doi.org/10.1186/s12889-022-13429-w
Tao, S., Bragazzi, N. L., Wu, J., Mellado, B., & Kong, J. D. (2022). Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world. Scientific Reports, 12(1), 944. https://doi.org/10.1038/s41598-021-04731-5
Tao, S., Bragazzi, N. L., Wu, J., Mellado, B., & Kong, J. D. (2022). Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world. Scientific Reports, 12(1), 944. https://doi.org/10.1038/s41598-021-04731-5
Tian, Y., Basran, J., Stempien, J., Danyliw, A., Fast, G., Falastein, P., & Osgood, N. D. (2023). Participatory Modeling with Discrete-Event Simulation: A Hybrid Approach to Inform Policy Development to Reduce Emergency Department Wait Times. Systems, 11(7), 362–362. https://doi.org/10.3390/systems11070362
Tian, Y., Zhang, W., Duan, L., McDonald, W., & Osgood, N. D. (2023). Comparison of pretrained transformer-based models for influenza and COVID-19 detection using social media text data in Saskatchewan, Canada. Frontiers in Digital Health, 5. https://doi.org/10.3389/fdgth.2023.1203874
Tofighi, M., Asgary, A., Merchant, A. A., Shafiee, M. A., Najafabadi, M. M., Nadri, N., Aarabi, M., Heffernan, J., & Wu, J. (2021). Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices. PLOS ONE, 16(11), e0259970. https://doi.org/10.1371/journal.pone.0259970
Tofighi, M., Asgary, A., Tofighi, G., Najafabadi, M. M., Arino, J., Amiche, A., Rahman, A., McCarthy, Z., Bragazzi, N. L., Thommes, E., Coudeville, L., Grunnill, M. D., Bourouiba, L., & Wu, J. (2022). Estimating social contacts in mass gatherings for disease outbreak prevention and management: case of Hajj pilgrimage. Tropical Diseases, Travel Medicine and Vaccines, 8(1). https://doi.org/10.1186/s40794-022-00177-3
Tosato, M., Zhang, X., & Wu, J. (2022). A patchy model for tick population dynamics with patch-specific developmental delays. Mathematical Biosciences and Engineering, 19(5), 5329–5360. https://doi.org/10.3934/mbe.2022250
Tuite, A. R., Fisman, D. N., Odutayo, A., Bobos, P., Allen, V., Bogoch, I. I., Brown, A. D., Evans, G. A., Greenberg, A., Hopkins, J., Maltsev, A., Manuel, D. G., McGeer, A., Morris, A. M., Mubareka, S., Munshi, L., Murty, V. K., Patel, S. N., Razak, F., & Reid, R. J. (2021). COVID-19 Hospitalizations, ICU Admissions and Deaths Associated with the New Variants of Concern. https://doi.org/10.47326/ocsat.2021.02.18.1.0
Vaziry, Kolokolnikov, T., & Kevrekidis, P. G. (2022). Modelling of spatial infection spread through heterogeneous population: from lattice to partial differential equation models. Royal Society Open Science, 9(10). https://doi.org/10.1098/rsos.220064
Vilches TN,Abdollahi E, Cipriano LE, Haworth-Brockman M, Keynan Y, Sheffield H, Langley JM,Moghadas SM, Impact of non-pharmaceutical interventions and vaccination on COVID-19 outbreaks in Nunavut, Canada: a Canadian Immunization Research Network (CIRN) study, BMC Public Health 22:1042.
Vilches TN, Moghadas SM, Sah P, Fitzpatrick MC, Shoukat A, Pandey A, Singer BH, Schneider EC, Galvani AP, Estimating COVID-19 infections, hospitalizations, and deaths following the US vaccination campaigns during the pandemic, JAMA Network Open 5(1):e2142725.
Vilches TN, RaffertyE, WellsCR, GalvaniAP, Moghadas SM, Economic evaluation of COVID-19 rapid antigen screening programs in the workplace, BMC Medicine 20:452.
Vilches TN, Sah P, Abdollahi E, Moghadas SM, Galvani AP, Importance of non-pharmaceutical interventions in the COVID-19 vaccination era: a case study of the Seychelles, Journal of Global Health 11: 03104.
Vilches TN, Sah P, Moghadas SM, Shoukat A, Fitzpatrick MC, Hotez PJ, Schneider EC, Galvani AP, COVID-19 hospitalizations and deaths averted under an accelerated vaccination program in northeastern and southern regions of the USA, The Lancet Regional Health - Americas 6: 100147.
Wang, X., Han, Q., & Kong, J. D. (2022). Studying the mixed transmission in a community with age heterogeneity: COVID-19 as a case study. Infectious Disease Modelling, 7(2), 250–260. https://doi.org/10.1016/j.idm.2022.05.006
Wells CR, Pandey A, Gokcebel S, Krieger G, Donoghue M, Singer BH, Moghadas SM, Galvani AP, Townsend JP, Quarantine and serial testing for variants of SARS-CoV-2 with benefits of vaccination and boosting on consequent control of COVID-19, Proceedings of the National Academy of Sciences USA - NEXUS 1(3):1-6.
Wells CR, Pandey A, Moghadas SM, Singer BH, Krieger G, Heron RJL, Turner DE, Abshire JP, Phillips KM, Donoghue AM, Galvani AP, Townsend JP, Comparative analyses of eighteen rapid antigen tests and RT-PCR for COVID-19 quarantine and surveillance-based isolation, Communications Medicine 2(84):1-12.
Wells CR, Townsend JP, Pandey A, Fitzpatrick MC, Crystal WC, Moghadas SM, Galvani AP, Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic, The Lancet Regional Health - Europe 00:100304.
Wu, T., Imrit, M. A., Movahedinia, Z., Kong, J., Woolway, R. I., & Sharma, S. (2022). Climate tracking by freshwater fishes suggests that fish diversity in temperate lakes may be increasingly threatened by climate warming. Diversity and Distributions. https://doi.org/10.1111/ddi.13664
Xie, R., Edwards, K.M., Adam, D.C. et al. Resurgence of Omicron BA.2 in SARS-CoV-2 infection-naive Hong Kong. Nat Commun 14, 2422 (2023). https://doi.org/10.1038/s41467-023-38201-5
Xu, W., Shu, H., Wang, L., Wang, X., & Watmough, J. (2023). The importance of quarantine: modelling the COVID-19 testing process. Journal of Mathematical Biology, 86(5). https://doi.org/10.1007/s00285-023-01916-6
Yi, W., Ma, J., & Cao, J. (2022). Basic reproduction number for the SIR epidemic in degree correlated networks. Physica D: Nonlinear Phenomena, 433, 133183–133183. https://doi.org/10.1016/j.physd.2022.133183
Yuan, P., Aruffo, E., Gatov, E., Tan, Y., Li, Q., Ogden, N., Collier, S., Nasri, B., Moyles, I., & Zhu, H. (2022). School and community reopening during the COVID-19 pandemic: a mathematical modelling study. Royal Society Open Science, 9(2). https://doi.org/10.1098/rsos.211883
Yuan, P., Aruffo, E., Tan, Y., Yang, L., Ogden, N. H., Fazil, A., & Zhu, H. (2022). Projections of the transmission of the Omicron variant for Toronto, Ontario, and Canada using surveillance data following recent changes in testing policies. Infectious Disease Modelling, 7(2), 83–93. https://doi.org/10.1016/j.idm.2022.03.004
Yuan, P., Li, J., Aruffo, E., Gatov, E., Li, Q., Zheng, T., Ogden, N. H., Sander, B., Heffernan, J., Collier, S., Tan, Y., Li, J., Arino, J., Bélair, J., Watmough, J., Kong, J. D., Moyles, I., & Zhu, H. (2022). Efficacy of a “stay-at-home” policy on SARS-CoV-2 transmission in Toronto, Canada: a mathematical modelling study. Canadian Medical Association Open Access Journal, 10(2), E367–E378. https://doi.org/10.9778/cmajo.20200242
Yuan, P., Tan, Y., Yang, L., Aruffo, E., Ogden, N. H., Bélair, J., Arino, J., Heffernan, J., Watmough, J., Carabin, H., & Zhu, H. (2022). Modeling vaccination and control strategies for outbreaks of monkeypox at gatherings. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1026489
Yuan, P., Tan, Y., Yang, L., Aruffo, E., Ogden, N. H., Bélair, J., Heffernan, J., Arino, J., Watmough, J., Carabin, H., & Zhu, H. (2022). Assessing transmission risks and control strategy for monkeypox as an emerging zoonosis in a metropolitan area. Journal of Medical Virology. https://doi.org/10.1002/jmv.28137
Yuan, P., Tan, Y., Yang, L., Aruffo, E., Ogden, N. H., Bélair, J., Heffernan, J., Arino, J., Watmough, J., Carabin, H., & Zhu, H. (2022). Assessing transmission risks and control strategy for monkeypox as an emerging zoonosis in a metropolitan area. Journal of Medical Virology. https://doi.org/10.1002/jmv.28137
Yuan, P., Tan, Y., Yang, L., Aruffo, E., Ogden, N. H., Yang, G., Lu, H., Lin, Z., Lin, W., Ma, W., Fan, M., Wang, K., Shen, J., Chen, T., & Zhu, H. (2022). Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic. Infectious Diseases of Poverty, 11(1). https://doi.org/10.1186/s40249-022-01030-7
Zahra Movahedi Nia, Nicola Luigi Bragazzi, Asgary, A., Orbinski, J., Wu, J., & Jude Dzevela Kong. (2022). Mpox panic, infodemic, and stigmatization of the 2SLGBTQIAP+ community: geospatial analysis, topic modeling, and sentiment analysis of a large, multilingual social media database (Preprint). 25, e45108–e45108. https://doi.org/10.2196/45108
Zhang, W., Liu, S., Osgood, N., Zhu, H., Qian, Y., & Jia, P. (2022). Using simulation modelling and systems science to help contain COVID‐19: A systematic review. Systems Research and Behavioral Science. https://doi.org/10.1002/sres.2897
Zheng, T., Zhu, H., Teng, Z., Nie, L., & Luo, Y. (2023). Patch model for border reopening and control to prevent new outbreaks of COVID-19. Mathematical biosciences and engineering : MBE, 20(4), 7171–7192. https://doi.org/10.3934/mbe.2023310
Zhou, L., Rong, X., Fan, M., Yang, L., Chu, H., Xue, L., Hu, G., Liu, S., Zeng, Z., Chen, M., Sun, W., Liu, S., Liu, Y., Wang, S., & Zhu, H. (2022). Modeling and Evaluation of the Joint Prevention and Control Mechanism for Curbing COVID-19 in Wuhan. Bulletin of Mathematical Biology, 84(2). https://doi.org/10.1007/s11538-021-00983-4
Zhou, S., Lin, W., & Wu, J. (2022). Generalized invariance principles for discrete-time stochastic dynamical systems. Automatica, 143, 110436. https://doi.org/10.1016/j.automatica.2022.110436
Zhou, S., Lin, W., Mao, X., & Wu, J. (2023). Generalized Invariance Principles for Stochastic Dynamical Systems and Their Applications. IEEE Transactions on Automatic Control, 1–15. https://doi.org/10.1109/tac.2023.3274215
Zhu, H., Liu, S., Li, X., Zhang, W., Osgood, N. D., & Jia, P. (2023). Using a hybrid simulation model to assess the impacts of combined COVID-19 containment measures in a high-speed train station. Journal of Simulation, 1–25. https://doi.org/10.1080/17477778.2023.2189027
Zhu, Y., Wang, Y., Li, C., Li, L., Chang, Q., Jia, Y., She, K., Liu, T., Zhu, H., & Li, X. (2022). A Network Dynamics Model for the Transmission of COVID-19 in Diamond Princess and a Response to Reopen Large-Scale Public Facilities. Healthcare, 10(1), 139–139. https://doi.org/10.3390/healthcare10010139
FUNDED BY:
