Infectious Disease Modeling: Opportunities to Improve Coordination and Ensure Reproducibility
Fast Facts
Outbreaks of infectious diseases—such as novel coronavirus and pandemic flu—have raised concerns about how federal agencies use modeling to predict a disease’s course. Models can help decision makers set disease control policies and allocate resources. If models are unsound, they may not produce the reliable predictions needed to make good decisions.
We examined how Health and Human Services, which includes the Centers for Disease Control and Prevention, uses and assesses models. We recommended that HHS improve coordination of modeling across agencies and ensure models are reproducible, which helps build confidence in their results.
An HHS employee working on Infectious Disease Planning and Response
Staff, computers, monitors, and projected screens
Highlights
What GAO Found
Within the Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention (CDC) and the Office of the Assistant Secretary for Preparedness and Response (ASPR) used models to inform decision-making during and after outbreaks of Ebola, Zika, and pandemic influenza. These agencies' modeling efforts informed public health planning, outbreak response, and, to a limited extent, resource allocation. Four CDC centers perform modeling.
HHS agencies reported using multiple mechanisms to coordinate modeling efforts across agencies, but they do not routinely monitor, evaluate, or report on the extent and success of coordination. Consequently, they risk missing opportunities to identify and address modeling challenges—such as communicating clearly, and obtaining adequate data and resources—before and during an outbreak. As a result, agencies may be limiting their ability to identify improvements in those and other areas. Further, there is potential for overlap and duplication of cross-agency modeling efforts, which could lead to inefficiencies.
Office of the Assistant Secretary for Preparedness and Response's Visualization Hub, which Can Be Used for Infectious Disease Planning and Response
CDC and ASPR generally developed and assessed their models in accordance with four steps GAO identified as commonly-recognized modeling practices: (1) communication between modeler and decision maker, (2) model description, (3) verification, and (4) validation. However, for four of the 10 models reviewed, CDC did not provide all details needed to reproduce model results, a key step that lets other scientists confirm those results. GAO found that CDC's guidelines and policy do not address reproducibility of models or their code. This is inconsistent with HHS guidelines and may jeopardize the reliability of CDC's research.
This report also identifies several modeling-related challenges, along with steps agencies have taken to address them.
Why GAO Did This Study
Outbreaks of infectious diseases—such as Ebola, Zika, and pandemic influenza—have raised concerns from Congress about how federal agencies use modeling to, among other things, predict disease distribution and potential impacts. In general, a model is a representation of reality expressed through mathematical or logical relationships. Models of infectious diseases can help decision makers set policies for disease control and may help to allocate resources.
GAO was asked to review federal modeling for selected infectious diseases. This report examines (1) the extent to which HHS used models to inform policy, planning, and resource allocation for public health decisions; (2) the extent to which HHS coordinated modeling efforts; (3) steps HHS generally takes to assess model development and performance; and (4) the extent to which HHS has addressed challenges related to modeling. GAO reviewed documents and interviewed HHS officials, state officials, and subject matter experts. GAO identified practices commonly used to assess infectious disease model performance and reviewed 10 selected modeling efforts to see if they followed these practices.
Recommendations
GAO recommends that HHS (1) develop a way to routinely monitor, evaluate, and report on modeling coordination efforts across multiple agencies and (2) direct CDC to establish guidelines to ensure full reproducibility of its models. HHS agreed with GAO's recommendations.
Recommendations for Executive Action
| Agency Affected | Recommendation | Status |
|---|---|---|
| Department of Health and Human Services |
Priority Rec.
The Secretary of Health and Human Services should develop a mechanism to routinely monitor, evaluate, and report on coordination efforts for infectious disease modeling across multiple agencies. (Recommendation 1) |
HHS agreed with and has begun taking steps to implement this recommendation. HHS stated that, as of February 2024, it is developing a process whereby it will coordinate its efforts in infectious disease modeling across its components, which will include monitoring, evaluating, and reporting on such coordination. To fully address this action, HHS needs to finish developing and implementing this process, and provide relevant documentation, while ensuring that the process routinely monitors, evaluates, and reports on coordination of infectious disease modeling efforts across multiple agencies. Successful completion of this effort could help HHS better identify any duplication and overlap among agencies, which could help them to better plan for and respond to disease outbreaks.
|
| Department of Health and Human Services |
Priority Rec.
The Secretary of Health and Human Services should direct CDC to establish guidelines that ensure full reproducibility of CDC's research by sharing with the public all permissible and appropriate information needed to reproduce research results, including, but not limited to, model code. (Recommendation 2) |
The Centers for Disease Control and Prevention concurred with this recommendation and has developed open source practices and made improvements to its processes. In April 2022, CDC launched an agency review designed to identify ways to improve how CDC develops and deploys its science, among other things. This review identified the need to share science and data faster, and prioritize public health communications, among other things. As a result, CDC shifted to a concurrent review process, updated its clearance routing process to reduce reviews. In August 2022, CDC launched an internal clearance transformation initiative to improve clearance process efficiency and in January 2024, published a framework for developing high-quality publications. Further, In January 2023, CDC launched the Center for Forecasting and Outbreak Analytics which maintains a public first approach and follows CDC's code publication open source practices, such as on GitHub. For example, Center for Forecasting and Outbreak Analytics code has been moved into shared spaces, thereby allowing others to review and use Center for Forecasting and Outbreak Analytics developed tools. CDC also maintains Open CDC, an open technology platform that shares public health data sets; code repositories; and rules that enable software applications to exchange data, among other things. We consider CDC's actions to meet the intention of our recommendation and are closing the recommendation as implemented.
|