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A review of methods to estimate the visibility factor for bias correction in network scale-up studies
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Aliakbar Haghdoost, Milad Ahmadi Gohari, Ali Mirzazadeh, Farzaneh Zolala, Mohammad Reza Baneshi
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Epidemiol Health. 2018;40:e2018041. Published online August 16, 2018
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DOI: https://doi.org/10.4178/epih.e2018041
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Abstract
Network scale-up is an indirect size estimation method, in which participants are questioned on sensitive behaviors of their social network members. Therefore, the visibility of the behavior affects the replies and estimates. Many attempts to estimate visibility have been made. The aims of this study were to review the main methods used to address visibility and to provide a summary of reported visibility factors (VFs) across populations. We systematically searched relevant databases and Google. In total, 15 studies and reports that calculated VFs were found. VF calculation studies have been applied in 9 countries, mostly in East Asia and Eastern Europe. The methods applied were expert opinion, comparison of NSU with another method, the game of contacts, social respect, and the coming-out rate. The VF has been calculated for heavy drug users, people who inject drugs (PWID), female sex workers (FSWs) and their clients, male who have sex with male (MSM), alcohol and methamphetamine users, and those who have experienced extra-/pre-marital sex and abortion. The VF varied from 1.4% in Japan to 52.0% in China for MSM; from 34.0% in Ukraine to 111.0% in China for FSWs; and from 12.0% among Iranian students to 57.0% in Ukraine for PWID. Our review revealed that VF estimates were heterogeneous, and were not available for most settings, in particular the Middle East and North Africa region, except Iran. More concrete methodologies to estimate the VF are required.
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Citations
Citations to this article as recorded by  - An Empirical Comparison of a Traditional Strategy and Network Scale-Up Method for Prevalence Estimation of Child Trafficking in Sierra Leone
Hui Yi, Kyle Vincent, David Okech, Jody Clay-Warner, Jiacheng Li, Tenshi Kawashima, Timothy G. Edgemon, Lydia Aletraris, Fred Hassan Konteh
Crime & Delinquency.2023; : 001112872311701. CrossRef - Thirty Years of The Network Scale-up Method
Ian Laga, Le Bao, Xiaoyue Niu
Journal of the American Statistical Association.2021; 116(535): 1548. CrossRef - Using Social Networks to Estimate the Number of COVID-19 Cases: The Incident (Hidden COVID-19 Cases Network Estimation) Study Protocol
Honoria Ocagli, Danila Azzolina, Giulia Lorenzoni, Silvia Gallipoli, Matteo Martinato, Aslihan Acar, Paola Berchialla, Dario Gregori
International Journal of Environmental Research and Public Health.2021; 18(11): 5713. CrossRef - Novel approaches to estimating abortion incidence
Gilda Sedgh, Sarah C. Keogh
Reproductive Health.2019;[Epub] CrossRef
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