Welcome to join Columbia Mailman seminar series on infectious disease modeling featuring Prof. Pejman Rohani from the University of Georgia on 4/21 Tue at 2 pm ET! Open to the public over Zoom.
For information and registration: events.columbia.edu/cal/event/ev...
Welcome to join Columbia Mailman seminar series on infectious disease modeling featuring Prof. Jeff Imai-Eaton
@jeff-imai-eaton.bsky.social from Harvard @hsph.harvard.edu on 4/7 Tue at 12 pm ET! Open to the public over Zoom.
For information and registration: events.columbia.edu/cal/event/ev...
Really enjoyed presenting at the Columbia Global Research Stabilization Fund Spring Showcase today. RSF’s support last year was critical in keeping our epidemic forecasting work moving. Inspired by the breadth of research and looking forward to what comes next!
Join ESPIDAM 2026 — the European Summer Program in Infectious Disease Analysis & Modelling!
A unique training opportunity for early-career researchers in epidemic modelling 🦠📊
⏳ Early bird deadline: March 31
www.su.se/english/divi...
Come work with me at Penn State on the dynamics of pathogen elimination. We're hiring up to two positions to support our work on measles/rubella and foot and mouth disease elimination @ciddpsu.bsky.social
It was a great pleasure to host a visit by @theferrarilab.bsky.social ! Super interesting talk and tons of impactful works on measles and rubella.
Honored to be elected as a Steering Committee Member of the MIDAS network @midas-network.bsky.social
Grateful to give back to a community that has shaped my career, and looking forward to supporting early-career investigators and strengthening engagement with international scholars.
Two postdoc positions open at SUMOC (Sorbonne Université | INSERM), Paris, within the EPIcx lab.
🦠 Network epidemiology of healthcare-associated infections (ARCANE)
🧠 Coupled behavior–disease modeling (PREVIX)
2-y positions | Start June 2026
#epidemiology #networks #matrices
Welcome to join Columbia Mailman seminar series on infectious disease modeling featuring Prof. Matthew Ferrari @theferrarilab.bsky.social from Penn State on 3/17 Tue at 12 pm EST! Open to the public over Zoom.
For more information and registration: events.columbia.edu/cal/event/ev...
Welcome to join Columbia Mailman seminar series on infectious disease modeling featuring Prof. Virginia Pitzer from Yale on 2/10 Tue at 12 pm EST! Open to the public over Zoom. For more information and registration: events.columbia.edu/cal/event/ev...
Presymptomatic transmission is a key determinant of the controllability of respiratory viruses. This nice study used household data to quantify presymptomatic transmission of influenza and Omicron. Important findings with implications for modeling and control.
www.nature.com/articles/s44...
Dont miss the ESPIDAM summer program in June 2026 in Stockholm, covering many key concepts for ID modelling:
stochastic models, AI for ID control, nowcasting and forecasting, phylodynamics, data analysis, network models, within-host models, health economics www.statistics.su.se/english/divi...
Takeaway: Pandemic respiratory viruses spread fast and stochastically, often before we can clearly detect them.
Preparedness needs to plan for uncertainty, and surveillance must be broad, not just focused on a few major hubs.
Grateful to an amazing group of collaborators across institutions!
We also ran simulations for future pandemics. Results suggest that wastewater surveillance limited to a few major hubs isn’t enough - broader coverage is needed to meaningfully slow early geographic spread.
Main finding: both pandemics spread to most US metro areas within weeks, leaving a very narrow window for early detection and containment.
The two viruses followed different transmission routes, but shared key spread hubs.
Key question: How fast did the last two pandemics spread in the US? Did they follow the same spatial transmission routes?
Using high-resolution disease data and human mobility, we built an ensemble inference framework that explicitly accounts for stochasticity and superspreading in early outbreaks.
Excited to share a new study published in PNAS! @pnas.org
We reconstructed the early, cryptic spatial spread of 2009 H1N1 influenza and SARS-CoV-2 across US metropolitan areas.
Link👉https://www.pnas.org/doi/10.1073/pnas.2518051123
#PandemicPreparedness #InfectiousDisease #HumanMobility
2025 was a challenging year for many of us. As the year comes to a close, let's pause to recognize and celebrate every accomplishment and milestone, big or small. Each step forward matters.
As we head into 2026, let’s keep climbing with aspiration, resilience, and strength!
This approach helps address common issues like filter divergence and underestimation of uncertainty in data assimilation. More importantly, we can reconstruct epidemic curves with time-varying Rt using forward simulations, which are essential for running counterfactual analyses.
Our results show that ensemble filter/smoother methods with adaptive inflation give more accurate and robust Rt estimates, especially around sudden changes in transmission dynamics.
Accurately estimating Rt and its uncertainty is central to understanding infectious disease dynamics and informing public health decisions. We systematically evaluated multiple data assimilation methods for estimating Rt using both synthetic epidemic simulations and real COVID-19 case data.
Glad to share our latest study, led by Han Yong Wunrow
@hwunrow.bsky.social, on estimating time-varying reproduction numbers (Rt) using data assimilation methods, now published in the Journal of the Royal Society Interface!
Link: royalsocietypublishing.org/rsif/article...
I am teaching Introduction to Network Science for a third year at Columbia Mailman! @cupublichealth.bsky.social Very grateful to have positive evaluations from students with diverse backgrounds. Welcome to join this small-size, engaged course if you are interested in networks and systems thinking!
Very interesting study on respiratory virus transmission in schools!
"Prolonged exposure in shared, poorly ventilated spaces, which potentially includes several infectious sources, drives respiratory virus transmission more than close contact."
www.nature.com/articles/s41...
Welcome to join Columbia Mailman @cupublichealth.bsky.social seminar series on infectious disease modeling featuring Prof. Mark Jit @markjit.bsky.social from NYU on 12/16 Tue at 12 pm EST! Open to the public over Zoom.
For more information and registration: 👉
events.columbia.edu/cal/event/ev...
Grateful to @natcomms.nature.com for featuring our AMRO inference study as one of the Editors’ Highlights in #PublicHealth: www.nature.com/collections/...
Safe travels! What a heavy snow ❄️
