Title

Modeling in Real Time During the Ebola Response

Authors

Martin I. Meltzer, National Center for Emerging and Zoonotic Infectious DiseasesFollow
Scott Santibanez, National Center for Emerging and Zoonotic Infectious Diseases
Leah S. Fischer, National Center for Emerging and Zoonotic Infectious Diseases
Toby L. Merlin, National Center for Emerging and Zoonotic Infectious Diseases
Bishwa B. Adhikari, National Center for Emerging and Zoonotic Infectious Diseases
Charisma Y. Atkins, National Center for Emerging and Zoonotic Infectious Diseases
Caresse Campbell, National Center for Emerging and Zoonotic Infectious Diseases
Isaac Chun-Hai Fung, Georgia Southern UniversityFollow
Manoj Gambhir, National Center for Emerging and Zoonotic Infectious Diseases
Thomas Gift, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention
Bradford Greening, National Center for Emerging and Zoonotic Infectious Diseases
Weidong Gu, National Center for Emerging and Zoonotic Infectious Diseases
Evin U. Jacobson, National Center for Emerging and Zoonotic Infectious Diseases
Emily B. Kahn, National Center for Emerging and Zoonotic Infectious Diseases
Cristina Carias, National Center for Emerging and Zoonotic Infectious Diseases
Lina Nerlander, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention
Gabriel Rainisch, National Center for Emerging and Zoonotic Infectious Diseases
Manjunath Shankar, National Center for Emerging and Zoonotic Infectious Diseases
Karen Wong, National Center for Emerging and Zoonotic Infectious Diseases
Michael L. Washington, National Center for Emerging and Zoonotic Infectious Diseases

Document Type

Article

Publication Date

7-8-2016

Publication Title

Morbidity and Mortality Weekly Report

DOI

10.15585/mmwr.su6503a12

ISSN

1545-861X

Abstract

To aid decision-making during CDC’s response to the 2014–2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014–July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood.

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