Sampling biases and missing data in explorations of sexual partner networks for the spread of sexually transmitted diseases

• Published in: Statistics in medicine Vol. 17; no. 18; pp. 2079 - 2097
• Main Authors: Ghani, A. C., Donnelly, C. A., Garnett, G. P.
• Format: Journal Article
• Language: English
• Published: Chichester Wiley Subscription Services, Inc., A Wiley Company 30.09.1998; Wiley
• Subjects: AIDS/HIV; Bias; Biological and medical sciences; Contact Tracing; Data Collection; Female; Gonorrhea - transmission; Human viral diseases; Humans; Infectious diseases; Male; Medical sciences; Models, Statistical; Monte Carlo Method; Probability; Sampling Studies; Sexual Partners; Sexually Transmitted Diseases - transmission; Stochastic Processes; Viral diseases; Viral diseases of the lymphoid tissue and the blood. Aids; Human; Immunopathology; Monte Carlo method; Bias; AIDS; Statistical estimation; Immune deficiency; Contamination; Infection; Missing data; Sexually transmitted disease; Simulation; Viral disease; Sex partner; Sampling
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/(SICI)1097-0258(19980930)17:18<2079::AID-SIM902>3.0.CO;2-H

The structures of sexual partner networks are important in determining patterns of transmission of STDs including HIV. Empirical data on sexual partnerships and sexual partner networks collected through sampling individuals are a non‐random sample of partnerships and network structures even if individuals are sampled randomly. This has the potential to bias estimates of measures describing the sexual partner network. In addition, biases may be introduced through non‐response and missing data. Using Monte Carlo simulation, we investigate the biases that are introduced in estimated measures of the sexual partner network through three common sampling methods. The results indicate that substantial systematic biases are introduced. The direction and magnitude of these biases suggest that, by ignoring them, the risk for the establishment and persistence of infection in a population may be underestimated. © 1998 John Wiley & Sons, Ltd.