Document Type

Article

Date of Original Version

9-6-2013

Abstract

An efficient surveillance system is a crucial factor in identifying, monitoring and tackling outbreaks of infectious diseases. Scarcity of data and limited amounts of economic resources require a targeted effort from public health authorities. In this paper, we propose a mathematical method to identify areas where surveillance is critical and low reporting rates might leave epidemics undetected. Our approach combines the use of reference-based susceptible-exposed-infectious models and observed reporting data;We propose two different specifications, for constant and time-varying surveillance, respectively. Our case study is centred around the spread of the raccoon rabies epidemic in the state of New York, using data collected between 1990 and 2007. Both methods offer a feasible solution to analyse and identify areas of intervention. © 2013 The Author(s).

Publication Title, e.g., Journal

Journal of the Royal Society Interface

Volume

10

Issue

86

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

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