Bio
Bryan Lewis is a research associate professor in the Network Systems Science and Advanced Computing division. His research has focused on understanding the transmission dynamics of infectious diseases within specific populations through both analysis and simulation. Lewis is a computational epidemiologist with more than 15 years of experience in crafting, analyzing, and interpreting the results of models in the context of real public health problems.
As a computational epidemiologist, Lewis acts as a liaison between the computer scientists and mathematicians designing and building simulation software and decision makers who want answers to pressing public policy questions. For more than a decade, Lewis has been heavily involved in a series of projects forecasting the spread of infectious disease as well as evaluating the response to them in support of the federal government. These projects have tackled diseases from ebola to pandemic influenza and melioidosis to cholera.
-
Public health and epidemiology, epidemiologic modeling, social network construction, and graph measures and dynamic networks
-
Virginia Tech, Genetics, Bioinformatics, and Computational Biology, Ph.D., 2011
University of California - Berkeley, Infectious Diseases, M.P.H., 2001
Carnegie Mellon University, Computational Biology, B.S., 1997 -
California Department of Health Services, Tuberculosis Control Branch, Surveillance and Epidemiology Section, 2001-2003
Modeling targeted layered containment of an influenza pandemic in the United States
Since early July, Virginia’s COVID-19 case counts have remained relatively stable, with an average of around 3,000 new infections reported every day. But over the same time period, hospitalizations have risen, with more than 800 inpatients as of Wednesday, according to data from the Virginia Hospital and Healthcare Association.

A bridge-builder in the health district, a pair of professors who helped wrongfully convicted persons and a trio of scientists who analyzed the coronavirus early in the pandemic have been awarded this year’s University of Virginia public service awards.

A research team from the University of Virginia’s Biocomplexity Institute was recognized with the UVA Provost’s Office Award for Collaborative Excellence in Public Service. As representatives of the Biocomplexity Institute’s COVID-19 Response Team, Jiangzhuo Chen, Bryan Lewis, and Srini Venkatramanan were recognized for their service to the University, the Commonwealth of Virginia and federal authorities during the pandemic, and which continues today.
The question on everyone's mind is whether the U.S. will have an easy, COVID-free spring, or if we're in for a resurgence in cases as the BA.2 variant of Omicron becomes dominant. Bryan Lewis, MPH, PhD, of the University of Virginia's Biocomplexity Institute, uses sequencing data and other information from COVID-19's past trajectory to model and project various scenarios for case rates, variants, and more.

While sequencing efforts are better than before, experts say there's a long way to go. The only certain thing about the future of SARS-CoV-2 variants is that nothing is certain -- but researchers are doing their best to keep an eye out for the next troublesome variant, even in the face of numerous challenges.

The continued uncertainty means there’s a range of potential outcomes for the pandemic. The Biocomplexity Institute, which has been modeling COVID-19 in Virginia since the early days of the virus, separated them into several categories based on immunity and the potential for new viral variants.

VDH and the UVA Biocomplexity Institute both suggest we may have just passed the peak of the omicron variant. This is based on past models that have been accurate on predicting trends, but not exact numbers.

Researchers from UVA’s Biocomplexity Institute and School of Engineering and Applied Science, working with a team of multi-disciplinary scientists from around the world, have spent the last two years developing highly advanced computational models designed to inform policy makers, save lives and prepare for future global epidemics.
Data models from the University of Virginia Biocomplexity Institute are suggesting the peak of the omicron variant is near. All 35 health districts across Virginia are currently reporting a surge in this variant of the coronavirus.

Bryan Lewis, a research associate professor at the Biocomplexity Institute and Initiative at the University of Virginia, has used models to predict future COVID-19 cases. From recent model runs, Lewis believes the omicron variant will become the dominant strain in the state before the end of the year.

For much of the pandemic, the Biocomplexity Institute has been modeling the likely trajectory of COVID-19 in Virginia using mobility data, case rates, vaccination numbers and a slew of other statistics that can predict how, where and how fast the virus will continue to spread. With many Virginians — and public health officials — already preparing for holiday gatherings, understanding potential risks could be crucial for decision-making.

This article discusses how the University of Virginia’s Biocomplexity Institute is helping local health officials select mobile vaccine sites. Our data dashboards and reports include information on mobility, drawn from anonymized cell phone data collected by a company called SafeGraph, showing where and when Virginians were traveling to help understand the impact of safety restrictions.

Rather than a shut-down, what if we knew which places to close during a pandemic to curtail the spread of a virus and lessen the economic impact to a locality? A model showing how this can be done, created by researchers at the University of Virginia Biocomplexity Institute and Stanford and Northwestern universities, has won a Best Paper Award in the Applied Research track at the recently concluded ACM KDD conference.
When the coronavirus reached Virginia, public health officials worried there would be so many patients, they would need to start building field hospitals right away. But a team of University of Virginia scientists, part of the Biocomplexity Institute, told the state to wait. The governor’s stay-at-home order, quarantines and social distancing that began in March 2020 could slow the disease’s spread.

COVID-19 modeling from the University of Virginia predicts a potential spike in cases in Virginia in September.

The Delta variant could drive Virginia’s coronavirus case count past levels seen during January’s peak, but more than 60,000 cases could be prevented if vaccinations rise, the University of Virginia’s COVID-19 model projects.

Public health officials were already struggling with how to persuade coronavirus vaccination holdouts to get the shot. But declining case rates and a highly contagious variant have made their work at once more difficult — and more urgent.

Researchers predict another surge in COVID-19 cases will strike Charlottesville and the surrounding health district at the end of April and continue through May.

Mutant strains of the coronavirus are spreading through the world’s population even as we vaccinate more people. Here's a look at how it's all playing out in Virginia.

COVID-19 variants, such as the B.1.1.7 and B.1.351, are increasing in Virginia and may be contributing to the cases seen in younger populations. Bryan Lewis explains that due to the lag in identifying these strains, real numbers of the variants are likely much higher.

Bryan Lewis, a computational epidemiologist at UVA’s Biocomplexity Institute, said the plummeting numbers were a surprise to scientists analyzing the data. “There are about 30 or 40-odd academic groups participating in the CDC’s forecasting hub, and I don’t think any of them predicted the cliff we fell off there,” Lewis said, adding that cases dropped dramatically not just in Virginia, but across the country.

While the flu season is far from over and flu cases have been reported year-round in the United States in the past, during a typical year, influenza cases would likely ramp up during the fall and winter, peaking in February. Not this year.

In this paper, researchers focus on a machine-learned anonymized mobility map aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics, specifically the flu.

The model predicts that under conditions of “strong control” the number of statewide cases could instead peak around Jan. 10.

Traffic planners, securities traders and military strategists all use it. Simulating the behavior of millions of idiosyncratic individuals also may be the best way to understand complex phenomena like pandemics.

New tool provides projections of critical data on bed capacity and hospitalization rates.
Hospitalizations from coronavirus are at a new high this week in Virginia. Meanwhile, one model projects some regions could run out of bed space by January if the current growth rate continues.

Researchers across Grounds joined the effort to defeat COVID-19—even as the world plunged abruptly into a new reality of shutdowns and social distancing—bringing their expertise together to understand the virus and prevent and treat infection.

Mallory Noe-Payne, Jeff Bossert, and researcher Bryan Lewis discuss the status of Virginia's fight against COVID-19 as we head toward the Thanksgiving holiday.

Bryan Lewis and Stephen Eubank share their experiences mentoring Caitlin Rivers, a young epidemiologist helping to inform policy.

The UVA Biocomplexity Institute has received a $1.44M award from the National Science Foundation for a Virtual Organization (VO) that will facilitate communication and collaboration among CISE scientists currently involved in pandemic research through the NSF RAPID program.

As the COVID-19 pandemic continues to escalate in the United States and in many locations around the world, countless questions remain about next steps for mitigation and response. How will various mitigation methods affect the spread? How will those change as the pandemic progresses or regresses?
Christopher Barrett, executive director, Madhav Marathe, division director, and Bryan Lewis, research associate professor, spoke to S&P Global Market Intelligence about the abilities and limitations of their COVID analytical models.

New data gathered and models created by the University of Virginia Biocomplexity Institute predict the Commonwealth is creeping closer and closer to a surge.

Researchers have developed a model that uses social-media and search data to forecast outbreaks of Covid-19 well before they occur.
The United States coronavirus death toll eclipsed the 100,000 milestone on May 27 and, as of early June, is nearing a figure that few may have expected or feared at the start of the novel coronavirus outbreak.

Health experts are encouraging people to pick lighter colored face masks made of cotton for the hot and humid summer months.

Governor Ralph Northam, in partnership with researchers from the University of Virginia’s Biocomplexity Institute and the nonprofit RAND Corporation, released new infectious disease modeling on the impact of COVID-19 mitigations in Virginia.
The good news from University of Virginia experts is that efforts to combat the coronavirus thus far indicate that the growth rate for new cases is not just slowing but leveling off almost entirely.

Madhav Marathe, Bryan Lewis and Chris Barrett, researchers and leaders at the UVA Biocomplexity Institute, developed a model for the Commonwealth of Virginia to project COVID-19 infection trends.

People are taking social distancing seriously – even when it comes to their health care decisions. The Centers for Disease Control and Prevention (CDC) reported Friday that influenza-like illness (ILI) activity decreased by 14 percent for the week ending March 28 compared to the prior week.

As the world deals with the unrelenting daily spread of the novel coronavirus, the World Health Organization (WHO), among its many other initiatives at this time, also looked farther down the road.

As the COVID-19 global health crisis continues to unfurl worldwide, the questions around global pandemics are no longer “if” they will occur, but how frequent, widespread, and severe those that come next will become.
A third spike in influenza-like illness (ILI) activity in the United States now puts the 2019-20 flu season on track to be perhaps the longest in at least the last 20 years of record-keeping by the Centers for Disease Control and Prevention (CDC).

Infectious disease experts working on the coronavirus, or COVID-19, warn that the outbreak could have a historically unprecedented impact on life across the globe.

Researchers at the University of Virginia Biocomplexity Institute have collected data on the coronavirus and turned it into interactive dashboards online.

The 2019-20 flu season is beginning its predicted decline as the second wave of flu activity decreases, according to the Centers for Disease Control and Prevention (CDC).

The end of this flu season is still more active than even the highest peak of last year's difficult season.

Are influenza outbreaks and weather patterns connected? Researchers have long known that flu season occurs in the colder months, and that infection rates drop dramatically as the weather warms.

UVA researchers at the Biocomplexity Institute and Initiative are developing computational models to estimate and manage the biological, social and economic impacts of influenza.

While vaccination is the primary and most effective way to prevent sickness and death caused by flu, the CDC reports that less than 40 percent of Americans age 18 and older typically receive a flu shot. This begs the question: what additional mitigation and prevention methods might improve the public health response and policy development for the flu?
Research Associate Professor Bryan Lewis Featured at NASEM Workshop