Martin Hoenigl1,2,3, Joshua Graff-Zivin4, Susan J Little1. 1. Division of Infectious Diseases, University of California-San Diego. 2. Division of Pulmonology. 3. Section of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Medical University of Graz, Austria. 4. School of International Relations and Pacific Studies and Department of Economics, University of California-San Diego.
Abstract
BACKGROUND: In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking. METHODS: To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%. RESULTS: Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%. CONCLUSIONS: Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%.
BACKGROUND: In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking. METHODS: To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%. RESULTS: Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%. CONCLUSIONS: Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%.
Authors: Eric M Ramos; Socorro Harb; Joan Dragavon; Paul Swenson; Joanne D Stekler; Robert W Coombs Journal: J Clin Virol Date: 2013-08-26 Impact factor: 3.168
Authors: Martin Hoenigl; Nadir Weibel; Sanjay R Mehta; Christy M Anderson; Jeffrey Jenks; Nella Green; Sara Gianella; Davey M Smith; Susan J Little Journal: Clin Infect Dis Date: 2015-04-22 Impact factor: 9.079
Authors: Yen T Duong; Yvonne Mavengere; Hetal Patel; Carole Moore; Julius Manjengwa; Dumile Sibandze; Christopher Rasberry; Charmaine Mlambo; Zhi Li; Lynda Emel; Naomi Bock; Jan Moore; Rejoice Nkambule; Jessica Justman; Jason Reed; George Bicego; Dennis L Ellenberger; John N Nkengasong; Bharat S Parekh Journal: J Clin Microbiol Date: 2014-08-13 Impact factor: 5.948
Authors: Christopher D Pilcher; Brian Louie; Shelley Facente; Sheila Keating; John Hackett; Ana Vallari; Chris Hall; Teri Dowling; Michael P Busch; Jeffrey D Klausner; Frederick M Hecht; Sally Liska; Mark W Pandori Journal: PLoS One Date: 2013-12-12 Impact factor: 3.240
Authors: Martin Hoenigl; Carlee B Moser; Nicholas Funderburg; Ronald Bosch; Amy Kantor; Yonglong Zhang; Jesper Eugen-Olsen; Malcolm Finkelman; Jochen Reiser; Alan Landay; Daniela Moisi; Michael M Lederman; Sara Gianella Journal: Clin Infect Dis Date: 2019-08-01 Impact factor: 9.079
Authors: Martin Hoenigl; Erin Morgan; Donald Franklin; Peter L Anderson; Elizabeth Pasipanodya; Matthew Dawson; Marvin Hanashiro; Eric E Ellorin; Jill Blumenthal; Robert Heaton; David J Moore; Sheldon R Morris Journal: J Neurovirol Date: 2019-01-07 Impact factor: 2.643
Authors: Nella Green; Martin Hoenigl; Antoine Chaillon; Christy M Anderson; Sergei L Kosakovsky Pond; Davey M Smith; Susan J Little Journal: AIDS Date: 2017-01-14 Impact factor: 4.177
Authors: Martin Hoenigl; Dominique L Braun; Roger Kouyos; Huldrych F Günthard; Susan J Little Journal: J Acquir Immune Defic Syndr Date: 2017-04-01 Impact factor: 3.731
Authors: Lorraine T Dean; Madeline C Montgomery; Julia Raifman; Amy Nunn; Thomas Bertrand; Alexi Almonte; Philip A Chan Journal: Am J Prev Med Date: 2018-02-01 Impact factor: 5.043
Authors: Martin Hoenigl; Antoine Chaillon; Sanjay R Mehta; Davey M Smith; Joshua Graff-Zivin; Susan J Little Journal: J Infect Date: 2016-08-11 Impact factor: 6.072
Authors: Timothy C Lin; Maartje Dijkstra; Godelieve J De Bree; Maarten F Schim van der Loeff; Martin Hoenigl Journal: J Acquir Immune Defic Syndr Date: 2018-10-01 Impact factor: 3.731