Tom McAndrew, a computational scientist and associate professor in Lehigh’s College of Health, recently published a paper in The Lancet Digital Health, exploring the repercussions of restricting public health data that is essential for researchers and healthcare providers in making informed decisions during the influenza season.
During the peak flu season, Pennsylvania witnesses around 1,000 hospitalizations per week. However, last year saw a significant surge in this number, with 4,000 hospitalizations per week recorded, marking it as one of the worst U.S. flu seasons in over a decade.
When President Donald Trump signed executive orders limiting public health entities’ capacity, including the U.S. Department of Health and Human Services and the Centers for Disease Control and Prevention (CDC), the availability of crucial public health data was significantly impacted. This move hindered the accurate assessment and decision-making process for doctors and researchers.
The removal of over 8,000 web pages from various government websites and the delay in releasing routine CDC data sources like the “Morbidity and Mortality Weekly Report” further exacerbated the situation. This unprecedented rollback of public information by the federal government left researchers like McAndrew feeling uncertain and concerned about future occurrences.
McAndrew’s research, along with doctoral student Garrik Hoyt, delves into the significance of public health datasets in flu forecasting and decision-making for public health officials. Their study, titled “When data disappear: Public health pays as US policy strays,” underscores the critical role of transparent and accessible datasets in enhancing public health decision-making processes.
The analysis conducted by McAndrew and Hoyt showcases the stark contrast between a data-rich model incorporating multiple government sources and a data-poor model relying on minimal information. The findings emphasize the dire consequences of limiting access to public health data, especially during public health crises like the flu season.
In response to the challenges posed by the reduction in public health data availability, McAndrew advocates for a strategic national plan involving diverse stakeholders to safeguard and enhance data collection efforts. The collaboration of academia, industry, local government, and health sectors is essential in ensuring the continuity of vital public health datasets.
Beyond flu forecasting, the broader impact of diminishing public health data availability on research, the economy, and society is a cause for concern. The need for empirical research to highlight the repercussions of such actions is crucial in guiding future policy decisions and resource allocation.
Hoyt’s forthcoming research focuses on the repercussions of reducing the number of public health officials and expert opinions in flu forecasting. By highlighting the human aspect of research and the tangible benefits it brings to vulnerable populations, Hoyt aims to underscore the importance of preserving expertise in public health decision-making processes.
As researchers and institutions like Lehigh University navigate the evolving landscape of public health data availability, the call for proactive measures to protect and enhance data access remains paramount. By emphasizing the value of transparent and data-driven decision-making, researchers like McAndrew and Hoyt strive to ensure the resilience of public health systems in the face of uncertainty and challenges.
