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Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa

View ORCID ProfileEduard Grebe, Alex Welte, Leigh F. Johnson, Gilles van Cutsem, Adrian Puren, Tom Ellman, Jean-François Etard, the Consortium for the Evaluation and Performance of HIV Incidence Assays (CEPHIA), Helena Huerga
doi: https://doi.org/10.1101/306464
Eduard Grebe
1DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
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  • ORCID record for Eduard Grebe
Alex Welte
1DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
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Leigh F. Johnson
2Centre for Infectious Diseases Epidemiology and Research (CIDER), University of Cape Town, Cape Town, South Africa
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Gilles van Cutsem
2Centre for Infectious Diseases Epidemiology and Research (CIDER), University of Cape Town, Cape Town, South Africa
3Médecins Sans Frontières, Cape Town, South Africa
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Adrian Puren
4National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg, South Africa
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Tom Ellman
3Médecins Sans Frontières, Cape Town, South Africa
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Jean-François Etard
5TransVIHMI, Institut de Recherche pour le Développement (IRD), Institut National de la Santé et de la Recherche Médicale (INSERM), Montpellier University, Montpellier, France
6Epicentre, Paris, France
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Helena Huerga
6Epicentre, Paris, France
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Abstract

Introduction There is a notable absence of consensus on how to generate estimates ofpopulation-level incidence. Incidence is a considerably more sensitive and harder to estimate indicator of epidemiological trends than prevalence. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa.

Methods Our novel method uses an ‘optimal weighting’ of estimates based on an implementation of a particular ‘synthetic cohort’ approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of ‘recent infection’ (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013.

Results Using the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI:0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY(2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY(0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY(0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27).

Discussion HIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small.

Conclusion Application of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies.

Footnotes

  • ↵¶ Membership list can be found in the Acknowledgments section.

  • ↵* eduardgrebe{at}sun.ac.za

  • 1 In the CEPHIA Evaluation Panel, all treated subjects were virally suppressed, resulting in an estimate of PR|tx = 0 in all cases where a supplemental viral load threshold is applied. In real-world populations, it is likely that a certain (unknown) proportion of treated subjects would be virally unsuppressed and that the FRR in treated subjects would therefore be non-zero.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 26, 2018.
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Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa
Eduard Grebe, Alex Welte, Leigh F. Johnson, Gilles van Cutsem, Adrian Puren, Tom Ellman, Jean-François Etard, the Consortium for the Evaluation and Performance of HIV Incidence Assays (CEPHIA), Helena Huerga
bioRxiv 306464; doi: https://doi.org/10.1101/306464
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Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa
Eduard Grebe, Alex Welte, Leigh F. Johnson, Gilles van Cutsem, Adrian Puren, Tom Ellman, Jean-François Etard, the Consortium for the Evaluation and Performance of HIV Incidence Assays (CEPHIA), Helena Huerga
bioRxiv 306464; doi: https://doi.org/10.1101/306464

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