Ethan Obie Romero-Severson1, Cody Lee Petrie2, Edward Ionides3, Jan Albert4, Thomas Leitner2. 1. Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM, USA eoromero@lanl.gov. 2. Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM, USA. 3. Department of Statistics, University of Michigan, Ann Arbor, MI, USA and. 4. Departments of Microbiology, Karolinska Institute and Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
Abstract
BACKGROUND: HIV-1 is a lifelong disease, often without serious symptoms for years after infection, and thus many infected persons go undetected for a long time. This makes it difficult to track incidence, and thus epidemics may go through dramatic changes largely unnoticed, only to be detected years later. Because direct measurement of incidence is expensive and difficult, several biomarker-based tests and algorithms have been developed to distinguish between recent and long-term infections. However, current methods have been criticized and demands for novel methods have been raised. METHODS: We developed and applied a biomarker-based incidence model, joining a time-continuous model of immunoglobulin G (IgG) growth (measured by the IgG-capture BED-enzyme immunoassay) with statistical corrections for both sample size and unobserved diagnoses. Our method uses measurements of IgG concentration in newly diagnosed people to calculate the posterior distribution of infection times. Time from infection to diagnosis is modelled for all individuals in a given period and is used to calculate a sample weight to correct for undiagnosed individuals. We then used a bootstrapping method to reconstruct point estimates and credible intervals of the incidence of HIV-1 in Sweden based on a sample of newly diagnosed people. RESULTS: We found evidence for: (i) a slowly but steadily increasing trend in both the incidence and incidence rate in Sweden; and (ii) an increasing but well-controlled epidemic in gay men in Stockholm. Sensitivity analyses showed that our method was robust to realistic levels (up to 15%) of BED misclassification of non-recently infected persons as early infections. CONCLUSIONS: We developed a novel incidence estimator based on previously published theoretical work that has the potential to provide rapid, up-to-date estimates of HIV-1 incidence in populations where BED test data are available. Published by Oxford University Press on behalf of the International Epidemiological Association 2015. This work is written by US Government employees and is in the public domain in the US.
BACKGROUND:HIV-1 is a lifelong disease, often without serious symptoms for years after infection, and thus many infected persons go undetected for a long time. This makes it difficult to track incidence, and thus epidemics may go through dramatic changes largely unnoticed, only to be detected years later. Because direct measurement of incidence is expensive and difficult, several biomarker-based tests and algorithms have been developed to distinguish between recent and long-term infections. However, current methods have been criticized and demands for novel methods have been raised. METHODS: We developed and applied a biomarker-based incidence model, joining a time-continuous model of immunoglobulin G (IgG) growth (measured by the IgG-capture BED-enzyme immunoassay) with statistical corrections for both sample size and unobserved diagnoses. Our method uses measurements of IgG concentration in newly diagnosed people to calculate the posterior distribution of infection times. Time from infection to diagnosis is modelled for all individuals in a given period and is used to calculate a sample weight to correct for undiagnosed individuals. We then used a bootstrapping method to reconstruct point estimates and credible intervals of the incidence of HIV-1 in Sweden based on a sample of newly diagnosed people. RESULTS: We found evidence for: (i) a slowly but steadily increasing trend in both the incidence and incidence rate in Sweden; and (ii) an increasing but well-controlled epidemic in gay men in Stockholm. Sensitivity analyses showed that our method was robust to realistic levels (up to 15%) of BED misclassification of non-recently infected persons as early infections. CONCLUSIONS: We developed a novel incidence estimator based on previously published theoretical work that has the potential to provide rapid, up-to-date estimates of HIV-1 incidence in populations where BED test data are available. Published by Oxford University Press on behalf of the International Epidemiological Association 2015. This work is written by US Government employees and is in the public domain in the US.
Authors: John W Hargrove; Jean H Humphrey; Kuda Mutasa; Bharat S Parekh; J Steve McDougal; Robert Ntozini; Henry Chidawanyika; Lawrence H Moulton; Brian Ward; Kusum Nathoo; Peter J Iliff; Ekkehard Kopp Journal: AIDS Date: 2008-02-19 Impact factor: 4.177
Authors: H Irene Hall; Ruiguang Song; Philip Rhodes; Joseph Prejean; Qian An; Lisa M Lee; John Karon; Ron Brookmeyer; Edward H Kaplan; Matthew T McKenna; Robert S Janssen Journal: JAMA Date: 2008-08-06 Impact factor: 56.272
Authors: Charlotte Sakarovitch; Francois Rouet; Gary Murphy; Albert K Minga; Ahmadou Alioum; Francois Dabis; Dominique Costagliola; Roger Salamon; John V Parry; Francis Barin Journal: J Acquir Immune Defic Syndr Date: 2007-05-01 Impact factor: 3.731
Authors: Etienne Karita; Matt Price; Eric Hunter; Elwyn Chomba; Susan Allen; Lin Fei; Anatoli Kamali; Eduard J Sanders; Omu Anzala; Michael Katende; Nzeera Ketter Journal: AIDS Date: 2007-02-19 Impact factor: 4.177
Authors: Federica Giardina; Ethan O Romero-Severson; Maria Axelsson; Veronica Svedhem; Thomas Leitner; Tom Britton; Jan Albert Journal: Int J Epidemiol Date: 2019-12-01 Impact factor: 7.196