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Infectious Disease Modeling: Opportunities to Improve Coordination and Ensure Reproducibility

GAO-20-372 Published: May 13, 2020. Publicly Released: Jun 04, 2020.
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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

Staff, computers, monitors, and projected screens

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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

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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)
Open
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)
Open
The Centers for Disease Control and Prevention concurred with and has begun taking steps to implement this recommendation. As of February 2024, CDC stated it was making progress toward improving the speed, quality, and timeliness of its shared data. It stated it has worked to prioritize and drive high-impact, high quality science to better inform federal, state, and local decision-making efforts. Additionally, CDC stated it has implemented system efficiencies and process improvements to improve data clearance efficiency. To fully address this action, CDC needs to finish updating and provide its policies and guidelines and modernize its information sharing processes. This could help to ensure and maximize the quality, objectivity, utility, and integrity of information disseminated to the public, such as by modifying its guidelines to include language relating to model reproducibility, including, but not limited to, model code. Successful completion of this effort could help CDC ensure that its models are reproducible, a key characteristic of reliable, high-quality scientific research.

Full Report

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Topics

Disease controlDiseasesEmerging infectious diseasesEpidemicsHealth careInfectious diseasesInfluenzaInfluenza pandemicsMedical countermeasurespandemicsPathogensPublic healthPublic health emergenciesData collectionDecision making