Loss of Data: Lehigh University Scholar Examines Implications of Restricting Access to Public Health Details
During peak flu seasons, Pennsylvania sadly witnesses around 1,000 hospitalizations weekly, mentioned Tom McAndrew, a computational scientist and associate professor at Lehigh's College of Health. Last year, this number skyrocketed to an alarming 4,000 per week, causing what's believed to be the worst U.S. flu season in over a decade.
As cases reached their zenith, doctors and researchers faced obstacles making informed public health decisions. This was due to President Donald Trump signing multiple executive orders that limited the capacity of public health entities, including the U.S. Department of Health and Human Services - which encompasses the Centers for Disease Control and Prevention (CDC) - to release crucial public health data.
By early February, over 8,000 web pages were taken down from more than a dozen government websites as federal agencies hastily implemented Trump's orders on diversity initiatives and gender ideology. The pages included vital information about vaccines, veterans' care, hate crimes, scientific research, and more, according to a New York Times report. These executive orders also delayed the release of several routine CDC data sources, such as the Morbidity and Mortality Weekly Report, a critical resource providing flu stats from around the U.S. and globally.
Associate Professor Tom McAndrew still feels uncertainty as a researcher. In the seven years since he started flu forecasting, it's the first time he's witnessed public information withheld by the federal government.
"Knowing these kinds of things can happen makes me anxious about what could potentially happen in the future in the U.S.," he said. "The fact that it happened and some stuff has been coming back online makes me wonder how we can better prepare if it happens again. We shouldn’t just ignore what happened in January and pretend it will never happen again."
What's in a Flu Forecast?
Researchers like McAndrew rely on the data to provide real-time and future insights about the influenza season for public health officials. The forecasts help predict the timing of peak influenza transmission, the overall number of cases and hospitalizations, and the effectiveness of preventative measures. They guide decisions on the optimal timing and locations for vaccine clinics and sending alerts to hospitals about the onset of the flu season.
McAndrew and his doctoral student Garrik Hoyt recently published a paper in The Lancet, a weekly peer-reviewed medical journal, titled "When Data Disappear: Public Health Pays As U.S. Policy Strays." The article uses empirical data to demonstrate how the rollback of public health datasets diminishes the ability to forecast flu-related hospitalizations, and it illustrates the broader risks of limiting data access during public health crises.
Currently, no statutes mandate the collection or reporting of crucial epidemiological data sources. McAndrew and Hoyt began working on the paper in February, examining stats from October 2023 - the start of the official 2023-2024 influenza season. The paper was published May 21, 2025.
"I think the biggest reason people should care about this is that the datasets produced by the government allow transparent analysis to be conducted, and transparency tends to lead to better decisions," McAndrew said. "Having open, transparent datasets like this allows for better public health decision making, which leads to better public health."
The Data-Rich Model Versus The Data-Poor Model
To show how data surveillance enhances public health practice, McAndrew and Hoyt's paper analyzed stats from seven U.S. government-maintained sources associated with seasonal influenza. They created two models: A data-rich model incorporating stats from all seven government sources, and a model relying solely on a single data source on hospitalizations and the census. The second model represented the minimal required information needed to produce a forecast of influenza hospitalizations.
The data-rich model produced reliable forecasts beneficial for public health decision making, whereas predictions using the second model were highly uncertain, making them impractical. The findings suggest that a plan should be developed to safeguard public health data.
"If the federal government were to cease the collection or maintenance of public health datasets, we might consequently witness a drastic increase in influenza-related morbidity and mortality," the report says. "An average of 400,000 hospitalizations and 20,000 deaths occur during a typical influenza season in the USA, with an estimated direct-medical cost of approximately $10 billion."
In addition, the withholding of previously public data comes at a time when the U.S. is experiencing an outbreak of avian flu, also known as H5N1. While it primarily infects birds, it can also affect humans and other animals.
"H5N1 is no laughing matter. If the current administration is restricting or pausing the dissemination of data related to that, then officials at the state level won't be able to prepare or react," McAndrew said. "It has the potential to have dire consequences, in the U.S. and globally."
Protecting the Data
McAndrew believes those in academia, industry, local government, and health should collaborate to increase local control over government-hosted datasets. While the cost would be minimal, the greater challenge would be supporting and coordinating the data collection process.
"We advocate for a strategic national plan, informed by diverse stakeholders, including those who generate, store, use, and maintain public health data and are involved in data infrastructure," the report says. "Representatives from private industry and academia should be included to develop a robust and feasible plan."
It's about more than just flu forecasting, said Dominic Packer, Lehigh's associate vice provost for research.
"The United States government has been so fundamentally important in collecting and making available vast amounts of data that impact any number of things, such as health, the economy, education, how well students are doing in school," Packer said. "Federal agencies are pulling back in many cases, either because they are losing relevant staff or they are losing funding to collect and establish these kinds of data, and it will have an impact on researchers and universities such as Lehigh."
When data started disappearing from federal websites, Lehigh researchers, especially those from the College of Health, acted quickly to archive any remaining information they could, Packer said.
"There are a lot of opinion pieces out there currently about how various actions by the executive branch will affect research, the economy, and society in different ways. What I like about Tom's article is that it goes beyond opinion to show empirically, by analyzing data, what the effects are likely to be," Packer said. "Everyone is entitled to their opinion, but at the end of the day, there are some facts, and research helps us get to those facts. Researchers apply methods that rigorously work through things to get you closer to reality."
The Human Aspect of Research
Hoyt, who is studying computer science, is working on a follow-up paper focusing on the effects of reducing the number of public health officials. Since the beginning of the year, thousands of federal employees from the Department of Health and Human Services have been terminated from their positions. Recently, a fraction of CDC employees had their jobs reinstated, according to news reports, although this figure is still far less than those who were originally let go.
"We want to show the value of having expert opinion and emphasize the danger of minimizing the amount of expertise," Hoyt said.
The follow-up paper examines data on expert opinions about the upcoming flu season and uses those opinions to build a model of the season. The fewer opinions available, the more biased the data, Hoyt explained. For example, if you are only keeping senior officials, you lose the expertise and opinion of different generations. Hoyt hopes to publish his findings later this summer.
Hoyt's interest in flu forecasting is deeply personal. He is inspired by his dad, who has genetic diabetes and is more susceptible to complications from the flu. In the future, Hoyt hopes to become a professor and inspire other students to pursue data science.
"I like that this work has a real-world application. I can easily think of people I know who have had really bad flu. We live in a community with a lot of elderly people and those who have chronic health conditions. Flu is a much larger threat to them than to someone my age," Hoyt said. "I just really like the human aspect of doing research and having someone benefit from it."
Lehigh has been named an R1 research university by the Carnegie Classification of Institutions of Higher Education. Universities with this designation conduct the highest level of research activity within the Carnegie Classification. Lehigh is the only university in the Lehigh Valley to have this designation, and one of seven in Pennsylvania. Learn more.
- The College of Health at Lehigh, as headed by computational scientist and associate professor Tom McAndrew, contributes to the field of education through research in science.
- During peak flu seasons, Pennsylvania witnesses around 1,000 hospitalizations weekly, a number that grew to a concerning 4,000 per week last year.
- Limited public health data release due to executive orders has caused uncertainties for researchers like McAndrew.
- By February, over 8,000 web pages were removed from government sites as federal agencies implemented Trump's orders on diversity initiatives and gender ideology.
- The removed pages included crucial information about vaccines, veterans' care, hate crimes, scientific research, and more.
- The delayed release of data sources like the Morbidity and Mortality Weekly Report hindered public health decisions.
- McAndrew and his doctoral student, Garrik Hoyt, published a paper in The Lancet titled "When Data Disappear: Public Health Pays As U.S. Policy Strays."
- The paper shows that the rollback of public health datasets impacts the ability to forecast flu-related hospitalizations.
- Currently, there are no statutes mandating the collection or reporting of crucial epidemiological data sources.
- McAndrew and Hoyt started the paper in February, examining stats from October 2023, the start of the official 2023-2024 influenza season.
- The paper was published on May 21, 2025.
- The importance of transparency in decisions is highlighted in the paper, as it enables better public health decision making.
- The paper created two models for flu forecasting: a data-rich model and a model relying on minimal required information.
- The data-rich model proved beneficial for public health decision making, while the minimal model produced highly uncertain predictions.
- McAndrew believes that collaboration among academia, industry, local government, and health can help increase local control over government-hosted datasets.
- Dominic Packer, Lehigh's associate vice provost for research, emphasizes the potential impact on universities such as Lehigh due to the government's data-pullback.
- Lehigh researchers took swift action to archive any remaining data once data started disappearing from federal websites.
- The article, written by McAndrew and Hoyt, goes beyond opinions to empirically show the effects of limiting data access during public health crises.
- Hoyt is working on a follow-up paper focusing on the effects of reducing the number of public health officials.
- Thousands of federal employees from the Department of Health and Human Services have been terminated from their positions since the beginning of the year.
- A fraction of CDC employees have had their jobs reinstated, but the figure is still far less than the original number let go.
- Hoyt hopes to showcase the value of expert opinions in the upcoming follow-up paper.
- The fewer opinions available, the more biased the data, as demonstrated in Hoyt's research.
- Hoyt's father, who has genetic diabetes, inspires his interest in flu forecasting as he is more susceptible to complications from the flu.
- Hoyt's ultimate goal is to become a professor and inspire other students to pursue data science.
- Hoyt finds the human aspect of research appealing, as it benefits real-world individuals such as his own family.
- Flu is a significant threat to elderly individuals and those with chronic health conditions in the community where Hoyt lives.
- McAndrew and Hoyt's research addresses key issues related to health, health and wellness, and workplace-wellness.
- Avian flu, also known as H5N1, is a pressing concern, especially given the current administration's approach to data dissemination.
- H5N1 can affect not only humans but also other animals, posing global concerns if the current administration restricts or delays data related to this strain.
- McAndrew and Hoyt advocate for a strategic national plan to safeguard public health data involving diverse stakeholders such as private industry, academia, and those responsible for data infrastructure.
