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ISPRS Int. J. Geo-Inf. 2014, 3(2), 764-780; doi:10.3390/ijgi3020764

Modeling Properties of Influenza-Like Illness Peak Events with Crossing Theory

Department of Geography, University of Florida, Gainesville, FL 32611, USA
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Received: 6 February 2014 / Revised: 17 April 2014 / Accepted: 15 May 2014 / Published: 26 May 2014
(This article belongs to the Special Issue Remote Sensing and Geospatial Technologies in Public Health)
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Abstract

The concept of “peak event” has been used extensively to characterize influenza epidemics. Current definitions, however, could not maximize the amount of pertinent information about the probabilities of peak events that could be extracted from the generally limited available records. This study proposes a new method of defining peak events and statistically characterizing their properties, including: annual event density, their timing, the magnitude over prescribed thresholds and duration. These properties of peak events are analyzed in five counties of Florida using records from the Influenza-Like Illness Surveillance Network (ILINet). Further, the identified properties of peak events are compared between counties to reveal the geographic variability of influenza peak activity. The results of this study illustrate the proposed methodology’s capacity to aid public health professionals in supporting influenza surveillance and implementing timely effective intervention strategies. View Full-Text
Keywords: influenza-like illness (ILI); peak event; properties of peak events; crossing theory; generalized Pareto distribution (GPD) influenza-like illness (ILI); peak event; properties of peak events; crossing theory; generalized Pareto distribution (GPD)
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Wang, Y.; Waylen, P.R.; Mao, L. Modeling Properties of Influenza-Like Illness Peak Events with Crossing Theory. ISPRS Int. J. Geo-Inf. 2014, 3, 764-780.

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