Quantity Versus Quality: A Survey Experiment to Improve the Network Scale-up Method

Dennis M. Feehan, Aline Umubyeyi, Mary Mahy, Wolfgang Hladik, Matthew J. Salganik

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

The network scale-up method is a promising technique that uses sampled social network data to estimate the sizes of epidemiologically important hidden populations, such as sex workers and people who inject illicit drugs. Although previous scale-up research has focused exclusively on networks of acquaintances, we show that the type of personal network about which survey respondents are asked to report is a potentially crucial parameter that researchers are free to vary. This generalization leads to a method that is more flexible and potentially more accurate. In 2011, we conducted a large, nationally representative survey experiment in Rwanda that randomized respondents to report about one of 2 different personal networks. Our results showed that asking respondents for less information can, somewhat surprisingly, produce more accurate size estimates. We also estimated the sizes of 4 key populations at risk for human immunodeficiency virus infection in Rwanda. Our estimates were higher than earlier estimates from Rwanda but lower than international benchmarks. Finally, in this article we develop a new sensitivity analysis framework and use it to assess the possible biases in our estimates. Our design can be customized and extended for other settings, enabling researchers to continue to improve the network scale-up method.

Original languageEnglish (US)
Pages (from-to)747-757
Number of pages11
JournalAmerican Journal of Epidemiology
Volume183
Issue number8
DOIs
StatePublished - Apr 15 2016

All Science Journal Classification (ASJC) codes

  • Epidemiology

Keywords

  • HIV
  • acquired immunodeficiency syndrome
  • epidemiologic methods
  • network sampling
  • population size estimation
  • social networks
  • survey research

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