Estimating sizes of hidden or hard-to-reach populations is an important problem in public health. For example, estimates of the sizes of populations at highest risk for HIV and AIDS are needed for designing, evaluating and allocating funding for treatment and prevention programmes. A promising approach to size estimation, relatively new to public health, is the network scale-up method (NSUM), involving two steps: estimating the personal network size of the members of a random sample of a total population and, with this information, estimating the number of members of a hidden subpopulation of the total population. We describe the method, including two approaches to estimating personal network sizes (summation and known population). We discuss the strengths and weaknesses of each approach and provide examples of international applications of the NSUM in public health. We conclude with recommendations for future research and evaluation.
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Gene A Shelley is now with the Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
In Memoriam: Peter D Killworth, oceanographer and social scientist.
The foundations of this work were presented at an Expert Symposium on Network Scale-Up Methods convened by UNAIDS, New York City, New York, September 2008.
Funding The preparation of this article was partially supported by UNAIDS. Work to develop the NSUM method was supported by the National Science Foundation. MJS acknowledges funding from the National Institutes of Health (NICHD), USA.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.
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