2026
Modular arithmetic as an alternative to model seasonal time-varying transmission rates: Influenza as a case study
Mathematical Biosciences and Engineering 23(3): 547-566 January 2026
DIMMS Lab · York University, Toronto
Modelling infectious disease, from a single host to a whole population.
The Disease-Informed Modelling, Methods and Systems Laboratory builds mechanistic, statistical and machine-learning models of how infections spread, and uses them to inform vaccination, forecasting and public health decisions.
Fig. 1
Live SIR epidemic
Day 0
- Susceptible
- 0
- Infectious
- 0
- Recovered
- 0
- Vaccinated
- 0
Based in the Department of Mathematics and Statistics at York University, the DIMMS Lab works on practical questions about vaccination, forecasting and outbreak control. Current and recent work covers mpox, seasonal and avian influenza, dengue and Zika.
01 Research
What we work on
Most projects pair a mechanistic model of transmission with real data and a practical question: who to vaccinate first, when an outbreak will peak, or how a virus behaves inside the body.
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01
Transmission dynamics
Compartmental and age-structured models of mpox, influenza and vector-borne disease, used to test interventions before they are deployed.
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02
Disease-informed machine learning
Neural networks built around epidemiological structure, applied to forecasting the spread of avian influenza.
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03
Statistical inference
Bayesian methods and MCMC for estimating model parameters and quantifying their uncertainty.
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04
Within-host and immune dynamics
How viruses and parasites interact with the immune system inside a single host, from mpox to dengue.
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05
Spatial epidemiology
Mapping where cases occur and identifying the social and environmental factors linked to them.
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06
Multi-timescale analysis
Singular perturbation methods for systems in which fast and slow processes interact.
02 Publications
Recent papers
Peer-reviewed work from the lab, newest first. Lab members are shown in bold.
All publications2026
2025
Pre-exposure vaccination in the high-risk population is crucial in controlling mpox resurgence in Canada
BMC Infectious Diseases 26(1): 14 December 2025
2025
Uncovering the impact of infection routes on within-host MPXV dynamics: Insights from a mathematical modeling study
PLOS Computational Biology 21(5): e1013073 May 2025
Prof. Woldegerima receives tenure and promotion to Associate Professor
Our director has been granted tenure and promoted to Associate Professor at York University, effective July 1, 2026.
Read the storyDr. Andrew Omame at the Dynamics with Delay workshop in Kingston
A three-day workshop at Queen's University on mathematical modelling with time delays, held in honour of Professor Tony Humphries of McGill University.
Read the storyMSCA Global Postdoctoral Fellowships 2026: hosting at the DIMMS Lab
The lab can host the outgoing phase of a Marie Skłodowska-Curie Global Postdoctoral Fellowship, with Prof. Woldegerima as supervisor.
Read the storyNew paper: modular arithmetic for seasonal disease modelling
Prof. Woldegerima and Nickson Golooba introduce modular arithmetic as a compact way to model seasonal transmission rates, with influenza as a case study.
Read the story04 Team
Lab members
Led by Prof. Woldegebriel Assefa Woldegerima, with members ranging from undergraduate researchers to postdoctoral fellows.
Meet the team
- Atiqa Naeem Alam DinPhD Student
- Mahedi Hossain RafiMSc Student
- Shayne LitvakMSc Student
- Amanda AchiangiaUndergraduate Researcher
- Jieyu ZhengUndergraduate Researcher
