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Optimizing influenza sentinel surveillance at the state level
Journal article   Open access   Peer reviewed

Optimizing influenza sentinel surveillance at the state level

Philip M Polgreen, Zunqui Chen, Alberto M Segre, Meghan L Harris, Michael A Pentella and Gerard Rushton
American journal of epidemiology, Vol.170(10), pp.1300-1306
11/15/2009
DOI: 10.1093/aje/kwp270
PMCID: PMC2800268
PMID: 19822570
url
https://doi.org/10.1093/aje/kwp270View
Published (Version of record) Open Access

Abstract

Influenza-like illness data are collected via an Influenza Sentinel Provider Surveillance Network at the state level. Because participation is voluntary, locations of the sentinel providers may not reflect optimal geographic placement. The purpose of this study was to determine the "best" locations for sentinel providers in Iowa by using a maximal coverage model (MCM) and to compare the population coverage obtained with that of the current sentinel network. The authors used an MCM to maximize the Iowa population located within 20 miles (32.2 km) of 1-143 candidate sites and calculated the coverage provided by each additional site. The first MCM location covered 15% of the population; adding a second increased coverage to 25%. Additional locations provided more coverage but with diminishing marginal returns. In contrast, the existing 22 Iowa sentinel locations covered 56% of the population, the same coverage achieved with just 10 MCM sites. Using 22 MCM sites covered more than 75% of the population, an improvement over the current site placement, adding nearly 600,000 Iowa residents. Given scarce public health resources, MCMs can help surveillance efforts by prioritizing recruitment of sentinel locations.
 Models, Theoretical Public Health Algorithms Global Health Epidemiologic Methods Humans Influenza, Human - epidemiology Iowa - epidemiology Models, Statistical Population Surveillance

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