Both H1N1 and COVID-19 spread across the U.S. faster and more unpredictably than early detection systems could keep up.
Public health scientists at the Columbia University Mailman School of Public Health used advanced computer simulations to retrace how the 2009 H1N1 flu pandemic and the 2020 COVID-19 pandemic spread across the United States. Their analysis shows just how quickly respiratory pandemics can move and why stopping outbreaks early is so difficult. Published today (January 5) in the journal Proceedings of the National Academy of Sciences, the research is the first study to directly compare how these two major U.S. pandemics spread across metropolitan areas nationwide.
A Look Back at Two Major U.S. Pandemics
The impact of both outbreaks was severe. In the United States, the 2009 H1N1 flu pandemic led to 274,304 hospitalizations and 12,469 deaths. The COVID-19 pandemic has had an even greater toll, with 1.2 million confirmed deaths so far.
The research team set out to better understand how these pandemics traveled from place to place in order to improve preparedness for future outbreaks. To do this, they combined detailed information about how each disease spreads with computer models that incorporated air travel, daily commuting patterns, and the possibility of superspreading events. Their simulations covered more than three hundred metropolitan areas across the U.S.
Rapid Spread Before Detection
The results showed that both pandemics were already circulating widely in most major metro areas within just a few weeks. This rapid expansion often happened before early case detection or government response measures were in place. Although the exact routes of transmission differed between H1N1 and COVID-19, both relied on key urban hubs to fuel nationwide spread. Cities such as New York and Atlanta played major roles. Air travel emerged as the dominant factor driving spread, far more than commuting, but unpredictable transmission patterns made it extremely difficult to forecast where outbreaks would surge next.
“The rapid and uncertain spread of the 2009 H1N1 flu and 2020 COVID-19 pandemics underscores the challenges for timely detection and control. Expanding wastewater surveillance coverage coupled with effective infection control could potentially slow the initial spread of future pandemics,” says the study’s senior author, Sen Pei, PhD, assistant professor of environmental health sciences at Columbia Mailman School.
Previous research has already highlighted the value of wastewater surveillance programs for detecting outbreaks early. This new study adds further support, showing that broader wastewater monitoring could play a key role in strengthening pandemic preparedness and improving response times.
Lessons for Future Outbreaks
In addition to reconstructing how H1N1 and COVID-19 spread, the study introduces a flexible framework that can be used to study the early stages of other epidemics. While human movement, especially air travel, is a major driver of pandemic spread, the researchers emphasize that many other factors also influence outcomes. These include population demographics, school calendars, holiday travel, and weather conditions.
Research Team and Ongoing Work
The study’s first author is Renquan Zhang, Dalian University of Technology, Dalian, China. Additional contributors include Rui Deng and Sitong Liu from Dalian University of Technology; Qing Yao and Jeffrey Shaman from Columbia University; Bryan T. Grenfell from Princeton; and Cécile Viboud from the National Institutes of Health.
For more than ten years, Jeffrey Shaman and colleagues, including Sen Pei, have worked on improving methods to track and predict the spread of infectious diseases such as influenza and COVID-19. Their real-time forecasting tools estimate how fast outbreaks will grow, where they are likely to spread, and when they may peak, helping public health officials make more informed decisions.
Reference: “Reconstructing the early spatial spread of pandemic respiratory viruses in the United States” by Renquan Zhang, Rui Deng, Sitong Liu, Qing Yao, Jeffrey Shaman, Bryan T. Grenfell, Cécile Viboud and Sen Pei, 6 January 2026, Proceedings of the National Academy of Sciences.
DOI: 10.1073/pnas.2518051123
This study was supported by funding from the National Natural Science Foundation of China (12371516), U.S. National Science Foundation (DMS-2229605), the Centers for Disease Control and Prevention (U01CK000592, 75D30122C14289), National Institute of Allergy and Infectious Diseases (R01AI163023), Princeton Catalysis Initiative, Princeton Precision Health, and High Meadows Environmental Institute. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the U.S. National Institutes of Health, Centers for Disease Control and Prevention, or Department of Health and Human Services.
Shaman and Columbia University disclose partial ownership of SK Analytics. Other authors declare no competing interests.
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1 Comment
If one could measure selfishness and the refusal to consider others, one would certainly have the model as to how rapidly a pandemic can spread. Australia is worth such a retrospective study as State governments were controlling who and what could cross State boundaries. And also how State governments responded to the anti-vax and anti-mask lunatics who wanted an open-slather pandemic across Australia.