Fall is coming. Enjoy a warm and colorful afternoon in the woods. 🍁

This study was led by Dr. Qing Yao, with great collaboration with Victoria Lynch, Molei Liu, @wuxiao1993.bsky.social and @robbieparks.bsky.social.

Check out the press release from Columbia Mailman. www.publichealth.columbia.edu/news/hurrica...

As hurricanes are becoming stronger and expanding their reach due to climate change, people need to be prepared for disasters they've never experienced before.

The analysis informed a feature story in the Washington Post earlier this year 👉 www.washingtonpost.com/climate-envi...

Hurricanes don’t stop at the coast. Our recent study, published in Environ Res Lett, shows inland communities are less likely to evacuate, leaving them more vulnerable as storms like Helene bring historic flooding and loss of life.

Paper 👉 doi.org/10.1088/1748...

This is a great opportunity to join an interdisciplinary team in NYC working on infectious diseases, modeling, and health. The position will remain open until filled. The first round review will begin on November 15th. The starting time is flexible. Please reach out if you have any questions!

🚨 JOB ALERT! Our group is recruiting a postdoc to develop novel methodologies for early outbreak detection and inference using AI/ML, modeling, and data science. This is a multi-year position providing stable research support. Welcome to apply and share with others!

👉 apply.interfolio.com/173722

So proud to support Nidhi Ram’s presentation in the Science Research Fellows program! Nidhi is a freshman and an SFR fellow, a prestigious four-year designation for some of Columbia’s most promising science students. Truly impressed by the intellect, maturity and academic ability of all fellows.

A small team of us at Columbia (Sen Pei, Qing Yao, and me) collaborated with @washingtonpost.com to create a data-driven story about Hurricane Helene flooding and lack of evacuation added to the severe impacts:

www.washingtonpost.com/climate-envi...

This study is led by Dr. Qing Yao, in collaboration with Victoria Lynch, Molei Liu, ‪@wuxiao1993.bsky.social‬, and @robbieparks.bsky.social‬. Great pleasure discussing our findings with Sarah Kaplan and Kevin Crowe at the Washington Post. The preprint has not been peer-reviewed. ‪End/

Within the Helene-affected regions, coastal counties showed stronger evacuation than inland counties, which suffered the most devastating damages and losses. There is an urgent need to increase awareness and develop evacuation plans in places that are unprepared for impending climate threats. 4/

Milton primarily impacted coastal areas and prompted sharp increases in out-region travel prior to landfall and sustained elevated mobility in the post-disaster period. In contrast, Helene affected mostly inland areas, where mobility changes were modest and largely within natural variation. 3/

Using over 300M cellphone foot-traffic records, we analyzed human mobility during Hurricanes Helene and Milton in 2024. We observed marked differences in adaptive mobility responses across locations with varying levels of historical hurricane exposure. 2/

Preprint: www.medrxiv.org/content/10.1...

Are we prepared for intensifying and expanding disasters caused by climate change? How to plan for floods that we’ve never seen in our lives? Read this fantastic story in the Washington Post, including our mobility analysis during Hurricane Helene in 2024. 1/

www.washingtonpost.com/climate-envi...

First day at SMB 2025 @smbmathbiology.bsky.social in the beautiful city of Edmonton! Today, we have a minisymposium "Scenario Modeling to Inform Public Policymaking" (10:20 am and 4 pm) with excellent talks on bridging mathematical models and policymaking. Welcome to stop by and join the discussion!

Excited to see this paper out in Science Advances, led by Prof. Alan Cohen @cusciofhealth.bsky.social. The definition of health should go beyond being free of disease. Our human body works as a complex dynamical system, and measuring health requires a perspective from complex systems.

Model fitting suggests a sublinear increase in force of infection with crowdedness and dwell time. The model can also generate improved short-term predictions in retrospective forecasts, suggesting that aggregated mobility data are sufficient to support high-resolution epidemic forecasting.

We developed a model incorporating place-specific mobility, indoor crowdedness & dwell time, and seasonality of virus transmissibility. This model explained the heterogeneous transmission of SARS-CoV-2 across NYC neighborhoods in 2020.

Using aggregated mobile foot-traffic data, we measured the daily connectivity across 42 NYC neighborhoods in different activities. We also quantified contact patterns using indoor crowdedness and dwell time for each place category.

Daily activities like dining & shopping create opportunities for human contact, facilitating respiratory virus spread. Different contact patterns may lead to differential outcomes across neighborhoods, as seen in NYC. But can we use foot-traffic data to predict epidemics in each neighborhood?

Sharing our new study out in PLoS Comput Biol.

We developed a behavior-driven epidemic model to generate neighborhood-level COVID-19 forecasts across NYC. We used mobile foot traffic data to measure how and where people mix and forecast local spread.

Read here: doi.org/10.1371/jour...

So glad to have @jgyou.bsky.social give an intriguing lecture on contagion modeling and network inference in our network science class!

We are Science of Health, a collaborative initiative led by faculty from Columbia University—scientists, physicians, and theorists transforming how we understand health, from cellular biology to daily life.
Our aim: nothing less than a revolution in biomedicine.
#SystemsOfHealth #HealthRevolution

It was great to have @danielmalinsky.bsky.social give an excellent lecture on casual graph discovery in my network science class today!

Huge congrats Chadi!