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

dc.contributor.authorGrebe, Eduarden_ZA
dc.contributor.authorWelte, Alexen_ZA
dc.contributor.authorJohnson, Leigh F.en_ZA
dc.contributor.authorVan Cutsem, Gillesen_ZA
dc.contributor.authorAdrian Puren, Adrianen_ZA
dc.contributor.authorEllman, Tomen_ZA
dc.contributor.authorEtard, Jean-Francoisen_ZA
dc.contributor.authorConsortium for the Evaluation and Performance of HIV Incidence Assaysen_ZA
dc.contributor.authorHuerga, Helenaen_ZA
dc.date.accessioned2019-10-07T11:54:03Z
dc.date.available2019-10-07T11:54:03Z
dc.date.issued2018-09-13
dc.identifier.citationGrebe, E. et al. 2018. Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa. PLoS ONE, 13(9):e0203638, doi:10.1371/journal.pone.0203638.
dc.identifier.issn1932-6203 (online)
dc.identifier.otherdoi:10.1371/journal.pone.0203638
dc.identifier.urihttp://hdl.handle.net/10019.1/106584
dc.descriptionCITATION: Grebe, E. et al. 2018. Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa. PLoS ONE, 13(9):e0203638, doi:10.1371/journal.pone.0203638.
dc.descriptionThe original publication is available at https://journals.plos.org/plosone
dc.description.abstractIntroduction: There is a notable absence of consensus on how to generate estimates of population-level incidence. Incidence is a considerably more sensitive indicator of epidemiological trends than prevalence, but is harder to estimate. 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.en_ZA
dc.description.urihttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0203638
dc.format.extent16 pages
dc.language.isoen_ZAen_ZA
dc.publisherPublic Library of Science
dc.subjectHIV infections -- Epidemiology -- Mathematical modelsen_ZA
dc.subjectHIV infections -- Recent infections -- Mathematical modelsen_ZA
dc.subjectHIV infections -- Age factors -- Mathematical modelsen_ZA
dc.subjectHIV infections -- Sex factors -- Mathematical modelsen_ZA
dc.subjectCohort analysisen_ZA
dc.subjectBiochemical markersen_ZA
dc.subjectHIV infections -- South Africa -- KwaZulu-Natalen_ZA
dc.titlePopulation-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africaen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthors retain copyright


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