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Sensitivities and Specificities of Diagnostic Tests and Infection Prevalence of Schistosoma haematobium Estimated from Data on Adults in Villages Northwest of Accra, Ghana

Substantial uncertainties surround the sensitivities and specificities of diagnostic techniques for urinary schistosomiasis. We used latent class (LC) modeling to address this problem. In this study, 220 adults in three villages northwest of Accra, Ghana were examined using five Schistosoma haematobium diagnostic measures: microscopic examination of urine for detection of S. haematobium eggs, dipsticks for detection of hematuria, tests for circulating antigens, antibody tests, and ultrasound scans of the urinary system. Testing of the LC model indicated non-invariance of the performance of the diagnostic tests across different age groups, and measurement invariance held for males and females and for the three villages. We therefore recommend the use of LC models for comparison between and the identification of the most accurate schistosomiasis diagnostic tests. Furthermore, microscopy and hematuria dipsticks were indicated through these models as the most appropriate techniques for detection of S. haematobium infection.

Received June 18, 2008. Accepted for publication October 22, 2008.

Acknowledgments: We thank the adults for participating in the study and the numerous members of the field research team for their hard work.

Financial support: This study was supported by funds from the Schistosomiasis Control Initiative to Artemis Koukounari and Joanne P. Webster, Medical Research Council to Christl A. Donnelly and grant no. 1RO3CA103497-01 from the National Cancer Institute to Clive Shiff. Bethany Bray was supported by Award Number P50-DA-010075 from the National Institute on Drug Abuse. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health.

^* Address correspondence to Artemis Koukounari, Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, St. Mary’s Campus, Norfolk Place, London, W2 1PG, United Kingdom. E-mail: artemis.koukounari{at}imperial.ac.uk

Authors’ addresses: Artemis Koukounari and Joanne P. Webster, Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College, St. Mary’s Campus, Norfolk Place, London W2 1PG, United Kingdom, E-mails: artemis.koukounari{at}imperial.ac.uk and joanne.webster{at}imperial.ac.uk. Christl A. Donnelly, Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College, St. Mary’s Campus, Norfolk Place, London W2 1PG, United Kingdom, E-mail: c.donnelly{at}imperial.ac.uk. Bethany C. Bray, The Methodology Center, Pennsylvania State University, 204 E. Calder Way, Suite 400, State College, PA 16801, E-mail: bcbray{at}psu.edu. Jean Naples and Clive Shiff, Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21205, E-mails: jnaples{at}jhsph.edu and cshiff{at}jhsph.edu. Kwabena Bosompem, Department of Parasitology, Noguchi Memorial Institute for Medical Research, Legon, Accra, Ghana, E-mail: kbosompem{at}noguchi.mimcom.net.