My current research focuses on mathematical epidemiology. I use mathematical modeling, asymptotic and rigorous analysis, optimal control, and scientific computing to understand epidemic dynamics and to design effective interventions. The program builds on questions, modeling experience, and a public-health perspective developed through intensive work on COVID-19, and has expanded into several connected research directions since 2022.
Epidemics at high transmission levels
Classical epidemic theory is often developed for moderate reproduction numbers. Highly transmissible SARS-CoV-2 variants raised a different set of questions: How do epidemic dynamics and optimal vaccination change when transmission is very intense? When do familiar approximations or intervention strategies cease to be informative?
My work studies sharp transitions in these regimes, counter-intuitive vaccine allocations, and competition between strains when one has a large transmission advantage. This direction includes “Optimal vaccination at high reproductive numbers: sharp transitions and counterintuitive allocations”, published in Proceedings of the Royal Society B (2022), and “Revisiting the exclusion principle in epidemiology at the limit of a large competitive advantage”, published in the Journal of Theoretical Biology 600, 112045 (2025).
Multi-strain epidemic dynamics
Interacting strains can display dynamics that are absent from single-strain models. I study how partial cross-immunity, waning immunity, immune boosting, and differences in competitive advantage can generate coexistence, oscillations, and complex outbreak patterns.
The mathematical goal is to identify mechanisms that destabilize apparently simple epidemic models and to construct analytically tractable descriptions of their dynamics. Recent work includes “Hidden Oscillations: How Minimal Immunological Interactions Destabilize Two-Strain Epidemic Models”, published in the SIAM Journal on Life Sciences (2026), as well as ongoing work on oscillatory multi-strain epidemics.
Seasonal vaccination and intervention
This research considers how vaccination and other controls should be timed when transmission varies seasonally and immunity wanes. The central problem is to choose a periodic intervention under limited annual resources while accounting for the nonlinear epidemic dynamics.
The program combines optimal-control questions with analytical characterization of effective policies. It includes the Israel Science Foundation project “Optimal vaccination in seasonal epidemics,” conducted with Prof. Guy Katriel, and the papers “Optimal Regulation in a Time-Periodic Environment: Insights from a Simple Model”, published in Applied Mathematics and Optimization (2026), and “Optimal Vaccination for Contagious Diseases with Seasonal Transmission”, published in the Bulletin of Mathematical Biology (2026).
Pandemic preparedness and public-health collaboration
During COVID-19, I worked closely with Israel’s Ministry of Health on data analysis and mathematical modeling. I led the development of a central epidemic model used in Israel and connected it to real-time data. The work supported analysis of the epidemic, the national vaccination campaign, and decisions concerning non-pharmaceutical interventions.
This collaboration led to “Population-level implications of the Israeli booster campaign to curtail COVID-19 resurgence”, published in Science Translational Medicine (2022). By fitting a mathematical model to detailed national data, the study evaluated the timing and breadth of alternative booster campaigns and quantified both direct and indirect protection. It was selected as the online-cover feature of the journal’s 1 June 2022 issue.
Pandemic preparedness plans
I study how pandemic planning can move from inventory-based stockpiling targets to strategies designed around healthcare-system capacity; read about our new PLOS Medicine study.
Earlier research
Before turning to mathematical epidemiology, I developed research programs in mathematical physics and applied analysis. This work includes continuum models of electrolyte solutions and ionic liquids, phase-field descriptions of nanostructure formation, singularity formation in nonlinear Schrödinger equations and nonlinear optics, numerical methods for singular problems, and asymmetric auction theory. Across these subjects, a consistent theme is the combination of mathematical modeling, asymptotic analysis, rigorous analysis, and scientific computation to address concrete scientific questions.