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Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations.

ABSTRACT: The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies.

SUBMITTER: Feehan DM

PROVIDER: S-EPMC5783650 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations.

Feehan Dennis M DM Salganik Matthew J MJ

Sociological methodology 20160801 1

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new esti ...[more]

PMID: 29375167

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Project description:IntroductionCorrect estimation of the size of key and bridge populations is crucial for an efficient HIV/AIDS response in resource-limited settings, enabling efficient program planning and resource allocation. The hidden nature of these groups poses challenges to traditional methods, leading to the adoption of innovative approaches like the network scale-up method (NSUM). In this article we present the results of a NSUM study conducted in 2020 in Ukraine, focusing on four key populations and three bridge populations, highlighting challenges and contributions to development of the method.MethodsFrom July to September 2020, we conducted a nationally representative survey in Ukraine via computer-assisted telephone interviews, and applied the known population method and summation method to estimate social networks sizes. Results were weighted based on individual sampling probability and adjusted for social respect and visibility factors to address potential limitations.ResultsOur study achieved a 20% response rate with 10,000 completed interviews. The social network size, using the known population method, was 213 people, and 125 using the summation method. Adjusting for the social respect and visibility, estimated key populations sizes were 295,857 [248,714-343,001] people who inject drugs, 152,267 [109,960-194,573] men who have sex with men, 78,385 [57,146-99,619] sex workers, and 9,963 [7,352-12,571] transgender people, detailed by age and gender. Bridge populations were estimated at 62,162 [50,445-73,879] sexual partners of people who inject drugs, 284,348 [233,113-335,583] clients of sex workers, and 13,697 [7,370-20,026] female partners of men who have sex with men.ConclusionsNSUM proves reliable for estimating key populations size with appropriate corrections. It shows promise for further use in Ukraine, considering limited geographic coverage of the integrated bio-behavioral studies to use multiplier-based methods. However, the validity concerns persist for estimating bridge populations size, emphasizing the need for further method refinement and addressing implementation issues, particularly those related to data collection.

Dataset Information

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations.

Publications

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations.

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