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Modeling HIV-HCV coinfection epidemiology in the direct-acting antiviral era: the road to elimination

Overview of attention for article published in BMC Medicine, December 2017
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Title
Modeling HIV-HCV coinfection epidemiology in the direct-acting antiviral era: the road to elimination
Published in
BMC Medicine, December 2017
DOI 10.1186/s12916-017-0979-1
Pubmed ID
Authors

Victor Virlogeux, Fabien Zoulim, Pascal Pugliese, Isabelle Poizot-Martin, Marc-Antoine Valantin, Lise Cuzin, Jacques Reynes, Eric Billaud, Thomas Huleux, Firouze Bani-Sadr, David Rey, Anne Frésard, Christine Jacomet, Claudine Duvivier, Antoine Cheret, Laurent Hustache-Mathieu, Bruno Hoen, André Cabié, Laurent Cotte, the Dat’AIDS Study Group

Abstract

HCV treatment uptake has drastically increased in HIV-HCV coinfected patients in France since direct-acting antiviral (DAA) treatment approval, resulting in HCV cure in 63% of all HIV-HCV patients by the end of 2015. We investigated the impact of scaling-up DAA on HCV prevalence in the whole HIV population and in various risk groups over the next 10 years in France using a transmission dynamic compartmental model. The model was based on epidemiological data from the French Dat'AIDS cohort. Eight risk groups were considered, including high-risk (HR) and low-risk (LR) men who have sex with men (MSM) and male/female heterosexuals, intra-venous drug users, or patients from other risk groups. The model was calibrated on prevalence and incidence data observed in the cohort between 2012 and 2015. On January 1, 2016, 156,811 patients were registered as infected with HIV in France (24,900 undiagnosed patients) of whom 7938 (5.1%) had detectable HCV-RNA (722 undiagnosed patients). Assuming a treatment coverage (TC) rate of 30%/year (i.e., the observed rate in 2015), model projections showed that HCV prevalence among HIV patients is expected to drop to 0.81% in 2026. Sub-analyses showed a similar decrease of HIV-HCV prevalence in most risk groups, including LR MSM. Due to higher infection and reinfection rates, predicted prevalence in HR MSM remained stable from 6.96% in 2016 to 6.34% in 2026. Increasing annual TC rate in HR MSM to 50/70% would decrease HCV prevalence in this group to 2.35/1.25% in 2026. With a 30% TC rate, undiagnosed patients would account for 34% of HCV infections in 2026. Our model suggests that DAA could nearly eliminate coinfection in France within 10 years for most risk groups, including LR MSM. Elimination in HR MSM will require increased TC.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 17%
Student > Ph. D. Student 9 12%
Other 7 9%
Student > Bachelor 7 9%
Student > Doctoral Student 6 8%
Other 14 18%
Unknown 22 28%
Readers by discipline Count As %
Medicine and Dentistry 22 28%
Nursing and Health Professions 6 8%
Engineering 3 4%
Immunology and Microbiology 3 4%
Mathematics 3 4%
Other 13 17%
Unknown 28 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 January 2018.
All research outputs
#14,832,856
of 23,012,811 outputs
Outputs from BMC Medicine
#3,007
of 3,455 outputs
Outputs of similar age
#250,750
of 439,953 outputs
Outputs of similar age from BMC Medicine
#42
of 47 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,455 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 439,953 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.