Measles outbreak response decision-making under uncertainty: a retrospective analysis

Author:

Fonnesbeck Christopher J.1ORCID,Shea Katriona23,Carran Spencer3,Cassio de Moraes Jose4,Gregory Christopher5,Goodson James L.6,Ferrari Matthew J.23

Affiliation:

1. Department of Biostatistics, Vanderbilt University Medical Center, Eleventh Floor, Suite 11000, 2525 West End Avenue, Nashville, TN, USA

2. Department of Biology and Intercollege Graduate Degree Program in Ecology, 208 Mueller Laboratory, The Pennsylvania State University, University Park, PA, USA

3. Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, USA

4. Faculdade de Ciencias Medicas da Sanda Casa de São Paulo, São Paulo, Brazil

5. Arboviral Diseases Branch, Division of Vector-Borne Diseases, National Center for Emerging and Zoonotic Infectious Diseases, US Centers for Disease Control and Prevention, Fort Collins, CO, USA

6. Accelerated Disease Control and Vaccine Preventable Disease Surveillance Branch, Global Immunization Division, Center for Global Health, US Centers for Disease Control and Prevention, Atlanta, GA, USA

Abstract

Resurgent outbreaks of vaccine-preventable diseases that have previously been controlled or eliminated have been observed in many settings. Reactive vaccination campaigns may successfully control outbreaks but must necessarily be implemented in the face of considerable uncertainty. Real-time surveillance may provide critical information about at-risk population and optimal vaccination targets, but may itself be limited by the specificity of disease confirmation. We propose an integrated modelling approach that synthesizes historical demographic and vaccination data with real-time outbreak surveillance via a dynamic transmission model and an age-specific disease confirmation model. We apply this framework to data from the 1996–1997 measles outbreak in São Paulo, Brazil. To simulate the information available to decision-makers, we truncated the surveillance data to what would have been available at 1 or 2 months prior to the realized interventions. We use the model, fitted to real-time observations, to evaluate the likelihood that candidate age-targeted interventions could control the outbreak. Using only data available prior to the interventions, we estimate that a significant excess of susceptible adults would prevent child-targeted campaigns from controlling the outbreak and that failing to account for age-specific confirmation rates would underestimate the importance of adult-targeted vaccination.

Funder

Ecology and Evolution of Infectious Disease program of the NSF/NIH

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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