What to know
- CFA worked alongside ÐÇ¿ÕÓéÀÖ¹ÙÍø's National Center for Immunization and Respiratory Diseases (NCIRD) to support the Chicago and Illinois Departments of Public Health in a measles outbreak response.
- They collaboratively applied modeling approaches to answer questions from decision-makers that helped guide their response planning and resource allocation.
Background
Measles is a highly infectious virus that can cause severe symptoms but can be prevented with the measles-mumps-rubella (MMR) vaccine. Measles cases have increased in recent years worldwide, heightening the chances of measles in the U.S. The overall risk of measles outbreaks in the U.S. is low because of ; however, vaccine coverage rates vary across the U.S.
In March 2024, a measles outbreak involving 57 cases occurred in Chicago. The (CDPH) initiated outbreak control and mitigation measures, including active case-finding, contact tracing, and a mass vaccination campaign at a shelter.
Additionally, CDPH and the Illinois Department of Public Health (IDPH) requested outbreak analytics assistance from ÐÇ¿ÕÓéÀÖ¹ÙÍø to understand the outbreak in real time and take steps to mitigate its spread.
Outbreak Response Questions and Modeling Insights
In March 2024, a resident of a migrant shelter in Chicago was diagnosed with measles. CDPH and IDPH requested assistance from ÐÇ¿ÕÓéÀÖ¹ÙÍø to apply modeling to understand the scope and size of the outbreak and to recommend interventions. ÐÇ¿ÕÓéÀÖ¹ÙÍø analyzed data from Chicago and developed a variety of models to answer key public health questions, such as:
- How big can we expect this outbreak to be?
- Have we missed any cases?
- How effective was our public health response?
NCIRD, CFA, and CDPH used compartmental and agent-based models to answer these questions and assess the accuracy of the model output. These models were developed and refined in real time to provide key insights for decision-makers regarding the outbreak trajectory, set expectations about the outbreak size, compare different vaccination campaign scenarios, and assess the impacts of active case finding.
ÐÇ¿ÕÓéÀÖ¹ÙÍø's outbreak support informed an evidence-based, resource-appropriate response, and validated the outbreak control and mitigation measures used in Chicago.
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Lessons Learned
Dynamic disease models can be updated in real-time during outbreak responses and tailored to the infectious disease, impacted population, outbreak setting, and other key parameters. Public health decision-makers can use these models to understand the course of an outbreak and explore the impact of interventions, therefore allowing them to make better decisions as they allocate resources and determine the extent and timing of public health responses.
Acknowledgments
- NCIRD works to prevent disease, disability, and death through immunization and by surveillance and control of respiratory and related diseases.
- CFA aims to use data, modeling, and analytics to respond to outbreaks in real time to inform effective decision-making.
- works with communities and partners to create an equitable, safe, resilient and Healthy Chicago.
- is an advocate for and partner with the people of Illinois to re-envision health policy and promote health equity, prevent and protect against disease and injury, and prepare for health emergencies.