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Coalescent estimates of HIV-1 generation time in vivo.

ABSTRACT: The generation time of HIV Type 1 (HIV-1) in vivo has previously been estimated using a mathematical model of viral dynamics and was found to be on the order of one to two days per generation. Here, we describe a new method based on coalescence theory that allows the estimate of generation times to be derived by using nucleotide sequence data and a reconstructed genealogy of sequences obtained over time. The method is applied to sequences obtained from a long-term nonprogressing individual at five sampling occasions. The estimate of viral generation time using the coalescent method is 1.2 days per generation and is close to that obtained by mathematical modeling (1.8 days per generation), thus strengthening confidence in estimates of a short viral generation time. Apart from the estimation of relevant parameters relating to viral dynamics, coalescent modeling also allows us to simulate the evolutionary behavior of samples of sequences obtained over time.

SUBMITTER: Rodrigo AG

PROVIDER: S-EPMC26758 | biostudies-literature | 1999 Mar

REPOSITORIES: biostudies-literature

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Coalescent estimates of HIV-1 generation time in vivo.

Rodrigo A G AG Shpaer E G EG Delwart E L EL Iversen A K AK Gallo M V MV Brojatsch J J Hirsch M S MS Walker B D BD Mullins J I JI

Proceedings of the National Academy of Sciences of the United States of America 19990301 5

The generation time of HIV Type 1 (HIV-1) in vivo has previously been estimated using a mathematical model of viral dynamics and was found to be on the order of one to two days per generation. Here, we describe a new method based on coalescence theory that allows the estimate of generation times to be derived by using nucleotide sequence data and a reconstructed genealogy of sequences obtained over time. The method is applied to sequences obtained from a long-term nonprogressing individual at fi ...[more]

PMID: 10051616

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Project description:BACKGROUND:It is frequently of epidemiological and/or clinical interest to estimate the date of HIV infection or time-since-infection of individuals. Yet, for over 15?years, the only widely-referenced infection dating algorithm that utilises diagnostic testing data to estimate time-since-infection has been the 'Fiebig staging' system. This defines a number of stages of early HIV infection through various standard combinations of contemporaneous discordant diagnostic results using tests of different sensitivity. To develop a new, more nuanced infection dating algorithm, we generalised the Fiebig approach to accommodate positive and negative diagnostic results generated on the same or different dates, and arbitrary current or future tests - as long as the test sensitivity is known. For this purpose, test sensitivity is the probability of a positive result as a function of time since infection. METHODS:The present work outlines the analytical framework for infection date estimation using subject-level diagnostic testing histories, and data on test sensitivity. We introduce a publicly-available online HIV infection dating tool that implements this estimation method, bringing together 1) curatorship of HIV test performance data, and 2) infection date estimation functionality, to calculate plausible intervals within which infection likely became detectable for each individual. The midpoints of these intervals are interpreted as infection time 'point estimates' and referred to as Estimated Dates of Detectable Infection (EDDIs). The tool is designed for easy bulk processing of information (as may be appropriate for research studies) but can also be used for individual patients (such as in clinical practice). RESULTS:In many settings, including most research studies, detailed diagnostic testing data are routinely recorded, and can provide reasonably precise estimates of the timing of HIV infection. We present a simple logic to the interpretation of diagnostic testing histories into infection time estimates, either as a point estimate (EDDI) or an interval (earliest plausible to latest plausible dates of detectable infection), along with a publicly-accessible online tool that supports wide application of this logic. CONCLUSIONS:This tool, available at https://tools.incidence-estimation.org/idt/ , is readily updatable as test technology evolves, given the simple architecture of the system and its nature as an open source project.

Project description:IntroductionTo close gaps in HIV prevention and care, knowledge about locations and populations most affected by HIV is essential. Here, we provide subnational and sub-population estimates of three key HIV epidemiological indicators, which have been unavailable for most settings.MethodsWe used surveillance data on newly diagnosed HIV cases from 2004 to 2014 and back-calculation modelling to estimate in France, at national and subnational levels, by exposure group and country of birth: the numbers of new HIV infections, the times to diagnosis, the numbers of undiagnosed HIV infections. The denominators used for rate calculations at national and subnational levels were based on population size (aged 18 to 64) estimates produced by the French National Institute of Statistics and Economic Studies and the latest national surveys on sexual behaviour and drug use.ResultsWe estimated that, in 2014, national HIV incidence was 0.17‰ (95% confidence intervals (CI): 0.16 to 0.18) or 6607 (95% CI: 6057 to 7196) adults, undiagnosed HIV prevalence was 0.64‰ (95% CI: 0.57 to 0.70) or 24,197 (95% CI: 22,296 to 25,944) adults and median time to diagnosis over the 2011 to 2014 period was 3.3 years (interquartile range: 1.2 to 5.7). Three mainland regions, including the Paris region, out of the 27 French regions accounted for 56% of the total number of new and undiagnosed infections. Incidence and undiagnosed prevalence rates were 2- to 10-fold higher than the national rates in three overseas regions and in the Paris region (p-values < 0.001). Rates of incidence and undiagnosed prevalence were higher than the national rates for the following populations (p-values < 0.001): born-abroad men who have sex with men (MSM) (respectively, 108- and 78-fold), French-born MSM (62- and 44-fold), born-abroad persons who inject drugs (14- and 18-fold), sub-Saharan African-born heterosexuals (women 15- and 15-fold, men 11- and 13-fold). Importantly, affected populations varied from one region to another, and in regions apparently less impacted by HIV, some populations could be as impacted as those living in most impacted regions.ConclusionsIn France, some regions and populations have been most impacted by HIV. Subnational and sub-population estimates of key indicators are not only essential to adapt, design implement and evaluate tailored HIV interventions in France, but also elsewhere where similar heterogeneity is likely to exist.

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Coalescent estimates of HIV-1 generation time in vivo.

Publications

Coalescent estimates of HIV-1 generation time in vivo.

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