Structuring targeted surveillance for monitoring disease emergence by mapping observational data onto ecological process

• Type of Material: Article
• Authors: Luca Gerardo-Giorda, Emory University; Gavino Puggioni, Emory University; Robert J. Rudd, New York State Department of Health; Lance Waller, Emory University; Leslie Real, Emory University
• Language: English
• Date: 2013-09-06
• Publisher: ROYAL SOC
• Publication Version: Final Published Version
• Copyright Statement: © 2013 The Author(s).
• License: Creative Commons Attribution 3.0 Unported
• Final Published Version (URL): http://dx.doi.org/10.1098/rsif.2013.0418
• Title of Journal or Parent Work: JOURNAL OF THE ROYAL SOCIETY INTERFACE
• Volume: 10
• Issue: 86
• Start Page: 20130418
• End Page: 20130418
• Grant/Funding Information: This research was supported by the National Institutes of Health grant RO1-AI047498 to L.A.R. and by the RAPIDD Program of the Science and Technology Directorate, Department of Homeland Security and the Fogarty International Center, National Institutes of Health.
• Keywords: Science & Technology; risk monitoring; public health; MEASLES; raccoon rabies; DYNAMICS; Multidisciplinary Sciences; RACCOONS; POPULATIONS; Science & Technology - Other Topics; EPIZOOTIC RABIES; RISK; PUBLIC-HEALTH; data assimilation; MODEL; modelling
• Research Categories: Health Sciences, Public Health

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.