Optimizing influenza sentinel surveillance at the state level - PubMed (original) (raw)

Comparative Study

. 2009 Nov 15;170(10):1300-6.

doi: 10.1093/aje/kwp270. Epub 2009 Oct 12.

Affiliations

Comparative Study

Optimizing influenza sentinel surveillance at the state level

Philip M Polgreen et al. Am J Epidemiol. 2009.

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.

PubMed Disclaimer

Figures

Figure 1.

Figure 1.

A) The population distribution for the state of Iowa. B) The 143 different possible locations for influenza-like illness sentinel sites. C) The 22 influenza-like illness sentinel locations (based on the 143 sentinel locations) chosen by the authors’ maximal coverage model. The numbers represent the order in which the sites were chosen by the model. D) The 22 Iowa Department of Public Health influenza-like illness sentinel locations for the 2006–2007 influenza season. The numbers represent the order in which the existing sites should have been chosen to maximize coverage.

Figure 2.

Figure 2.

Population coverage (proportion) as a function of additional hospital surveillance units for a fixed, prespecified distance of 20 miles (32.2 km). The upper, solid curve represents the proportion of population coverage as each new surveillance site is added if the sites are selected de novo; the lower, dashed curve represents the proportion of population coverage when new surveillance sites are added incrementally to the 22 original 2006–2007 Iowa Department of Public Health–influenza-like illness surveillance locations.

Figure 3.

Figure 3.

The 22 Iowa influenza-like illness sentinel locations chosen by the maximal coverage model when considering the border population in neighboring states. Numbers correspond to the selection order.

Figure 4.

Figure 4.

Population coverage (proportion) as a function of additional health care provider surveillance units, for a fixed, prespecified distance of 20 miles (32.2 km), considering the population adjacent to Iowa's border. The upper, solid curve represents the proportion of population coverage as each new surveillance site is added if the sites are selected by the algorithm; the lower, dashed curve represents the proportion of population coverage starting from the 22 currently selected surveillance sites.

Similar articles

Cited by

References

    1. Thompson WW, Shay DK, Weintraub E, et al. Mortality associated with influenza and respiratory syncytial virus in the United States. JAMA. 2003;289(2):179–186. - PubMed
    1. Centers for Disease Control and Prevention. Atlanta, GA: CDC; 2008. National Notifiable Diseases Surveillance System. ( http://www.cdc.gov/ncphi/disss/nndss/nndsshis.htm). (Accessed September 29, 2008)
    1. Thompson WW, Comanor L, Shay DK. Epidemiology of seasonal influenza: use of surveillance data and statistical models to estimate the burden of disease. J Infect Dis. 2006;194(suppl 2):S82–S91. - PubMed
    1. Current J, Min H, Schilling D. Multiobjective analysis of facility location decisions. Eur J Oper Res. 1990;49(3):295–307.
    1. Love RF, Morris JG, Wesolowsky GO. Facilities Location: Models and Methods. New York, NY: Appleton & Lange; 1988.

Publication types

MeSH terms

LinkOut - more resources