BACKGROUND: Measuring incidence is important for monitoring and maintaining the safety of the blood supply. Blood collected from repeat-donors has provided the opportunity to follow blood donors over time and has been used to estimate the incidence of viral infections. These incidence estimates have been extrapolated to first-time donors using the ratio of NAT yield cases in first-time versus repeat-donors. We describe a model to estimate incidence in first-time donors using the limiting antigen (LAg) avidity assay and compare its results with those from established models. METHODS: HIV-positive first-time donations were tested for recency using the LAg assay. Three models were compared; incidence estimated for (1) first-time donors using LAg avidity, (2) first-time and repeat-donors separately using the NAT yield window period (WP) model and (3) repeat-donors using the incidence/WP model. RESULTS: HIV incidence in first-time donors was estimated at 3·32 (CI 3·11, 3·55) and 3·81 (CI 3·07, 4·73) per 1000 PY using the LAg assay and NAT yield WP models, respectively. Incidence in repeat-donors was between 2·0- and 2·5-fold lower than in first-time donors estimated at 1·56 (CI 1·37, 1·77) and 1·94 (CI 1·86-2·01) per 1000 PY using the NAT yield/WP and incidence/WP models, respectively. CONCLUSION: Testing HIV-positive donations using the LAg assay provides a reliable method to estimate incidence in first-time donors for countries that collect the majority of blood from first-time donors and do not screen with NAT.
BACKGROUND: Measuring incidence is important for monitoring and maintaining the safety of the blood supply. Blood collected from repeat-donors has provided the opportunity to follow blood donors over time and has been used to estimate the incidence of viral infections. These incidence estimates have been extrapolated to first-time donors using the ratio of NAT yield cases in first-time versus repeat-donors. We describe a model to estimate incidence in first-time donors using the limiting antigen (LAg) avidity assay and compare its results with those from established models. METHODS: HIV-positive first-time donations were tested for recency using the LAg assay. Three models were compared; incidence estimated for (1) first-time donors using LAg avidity, (2) first-time and repeat-donors separately using the NAT yield window period (WP) model and (3) repeat-donors using the incidence/WP model. RESULTS: HIV incidence in first-time donors was estimated at 3·32 (CI 3·11, 3·55) and 3·81 (CI 3·07, 4·73) per 1000 PY using the LAg assay and NAT yield WP models, respectively. Incidence in repeat-donors was between 2·0- and 2·5-fold lower than in first-time donors estimated at 1·56 (CI 1·37, 1·77) and 1·94 (CI 1·86-2·01) per 1000 PY using the NAT yield/WP and incidence/WP models, respectively. CONCLUSION: Testing HIV-positive donations using the LAg assay provides a reliable method to estimate incidence in first-time donors for countries that collect the majority of blood from first-time donors and do not screen with NAT.
Authors: Michael P Busch; Christopher D Pilcher; Timothy D Mastro; John Kaldor; Gaby Vercauteren; William Rodriguez; Christine Rousseau; Thomas M Rehle; Alex Welte; Megan D Averill; Jesus M Garcia Calleja Journal: AIDS Date: 2010-11-27 Impact factor: 4.177
Authors: Marion Vermeulen; Nico Lelie; Charl Coleman; Wendy Sykes; Genevieve Jacobs; Ronel Swanevelder; Michael Busch; Gert van Zyl; Eduard Grebe; Alex Welte; Ravi Reddy Journal: Transfusion Date: 2018-09-28 Impact factor: 3.157
Authors: Michael P Busch; Simone A Glynn; Susan L Stramer; D Michael Strong; Sally Caglioti; David J Wright; Brandee Pappalardo; Steven H Kleinman Journal: Transfusion Date: 2005-02 Impact factor: 3.157
Authors: Marinus van Hulst; Gijs A A Hubben; Kwamena W C Sagoe; Charupon Promwong; Parichart Permpikul; Ladda Fongsatitkul; Diarmuid M Glynn; Cees T Smit Sibinga; Maarten J Postma Journal: Transfusion Date: 2009-08-25 Impact factor: 3.157
Authors: Eberhard W Fiebig; David J Wright; Bhupat D Rawal; Patricia E Garrett; Richard T Schumacher; Lorraine Peddada; Charles Heldebrant; Richard Smith; Andrew Conrad; Steven H Kleinman; Michael P Busch Journal: AIDS Date: 2003-09-05 Impact factor: 4.177
Authors: Reshma Kassanjee; Alex Welte; Thomas A McWalter; Sheila M Keating; Marion Vermeulen; Susan L Stramer; Michael P Busch Journal: PLoS One Date: 2011-06-09 Impact factor: 3.240
Authors: Reshma Kassanjee; Christopher D Pilcher; Sheila M Keating; Shelley N Facente; Elaine McKinney; Matthew A Price; Jeffrey N Martin; Susan Little; Frederick M Hecht; Esper G Kallas; Alex Welte; Michael P Busch; Gary Murphy Journal: AIDS Date: 2014-10-23 Impact factor: 4.177
Authors: Cassandra D Josephson; Simone Glynn; Sunitha Mathew; Rebecca Birch; Sonia Bakkour; Lisa Baumann Kreuziger; Michael P Busch; Kathleen Chapman; Carla Dinardo; Jeanne Hendrickson; Eldad A Hod; Shannon Kelly; Naomi Luban; Alan Mast; Philip Norris; Brian Custer; Ester Sabino; Bruce Sachais; Bryan R Spencer; Mars Stone; Steve Kleinman Journal: Transfusion Date: 2022-04-19 Impact factor: 3.337
Authors: Shelley N Facente; Eduard Grebe; Andrew D Maher; Douglas Fox; Susan Scheer; Mary Mahy; Shona Dalal; David Lowrance; Kimberly Marsh Journal: JMIR Public Health Surveill Date: 2022-03-11