title: Optimizing influenza sentinel surveillance at the state level.
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.
authors.affiliation: Division of Infectious Diseases, Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, Iowa 52242, USA. philip-polgreen@uiowa.edu
authors.forename: Philip M
authors.initials: PM
authors.lastname: Polgreen
authors.forename: Zunqui
authors.initials: Z
authors.lastname: Chen
authors.forename: Alberto M
authors.initials: AM
authors.lastname: Segre
authors.forename: Meghan L
authors.initials: ML
authors.lastname: Harris
authors.forename: Michael A
authors.initials: MA
authors.lastname: Pentella
authors.forename: Gerard
authors.initials: G
authors.lastname: Rushton
mesh_terms: D000465:Algorithms; D004812:Epidemiologic Methods; D014943:Global Health; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology*; D007484:Iowa / Q000453:epidemiology; D015233:Models, Statistical; D008962:Models, Theoretical; D011159:Population Surveillance; D011634:Public Health