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Volume 23, Number 4—April 2017
Dispatch

Design Strategies for Efficient Arbovirus Surveillance

Samuel V. Scarpino, Lauren Ancel Meyers, and Michael A. JohanssonComments to Author 
Author affiliations: University of Vermont, Burlington, Vermont, USA (S.V. Scarpino); Santa Fe Institute, Santa Fe, New Mexico, USA (S.V. Scarpino, L.A. Meyers); University of Texas at Austin, Austin, Texas, USA (L.A. Meyers); Centers for Disease Control and Prevention, San Juan, Puerto Rico, USA (M.A. Johansson); Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA (M.A. Johansson)

Main Article

Figure 1

Relative surveillance system performance. The performance of the 4 optimized surveillance systems (Island, Regional, Serotype, and Multi-objective) compared with 3 alternative designs (Population, Volume, and Diversity), with respect to estimating A) island-wide cases, B) serotype-specific cases, and C) regional cases. Each system contains 22 providers. Systems are ordered from highest to lowest performance in each graph. Performance is measured by average out-of-sample across 100 different 3-ye

Figure 1. Relative surveillance system performance. The performance of the 4 optimized surveillance systems (Island, Regional, Serotype, and Multi-objective) compared with 3 alternative designs (Population, Volume, and Diversity), with respect to estimating A) island-wide cases, B) serotype-specific cases, and C) regional cases. Each system contains 22 providers. Systems are ordered from highest to lowest performance in each graph. Performance is measured by average out-of-sample across 100 different 3-year periods, resulting from linear regression of target time series (e.g., island-wide cases) on time series of cases occurring within the specified surveillance system.

Main Article

Page created: April 06, 2017
Page updated: April 06, 2017
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