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Integration of a recent infection testing algorithm into HIV surveillance in Ireland: improving HIV knowledge to target prevention

Published online by Cambridge University Press:  04 March 2019

E. Robinson*
Affiliation:
Health Service Executive (HSE) Health Protection Surveillance Centre, Dublin, Ireland
J. Moran
Affiliation:
Health Service Executive (HSE) Health Protection Surveillance Centre, Dublin, IrelandNational Virus Reference Laboratory, University College Dublin, Dublin, Ireland
K. O'Donnell
Affiliation:
Health Service Executive (HSE) Health Protection Surveillance Centre, Dublin, Ireland
J. Hassan
Affiliation:
National Virus Reference Laboratory, University College Dublin, Dublin, Ireland
H. Tuite
Affiliation:
Infectious Diseases Society of Ireland, Dublin, Ireland
O. Ennis
Affiliation:
Department of Public Health Medicine, HSE East, Dublin, IrelandHIV Ireland, Dublin, Ireland
F. Cooney
Affiliation:
Department of Public Health Medicine, HSE East, Dublin, Ireland
E. Nugent
Affiliation:
HIV Ireland, Dublin, Ireland
L. Preston
Affiliation:
Positive Now, Dublin, Ireland
S. O'Dea
Affiliation:
HSE Gay Men's Health Service, Dublin, Ireland
S. Doyle
Affiliation:
Department of Public Health Medicine, HSE South East, Kilkenny, Ireland
S. Keating
Affiliation:
Society for the Study of Sexually Transmitted Diseases in Ireland, Dublin, Ireland
J. Connell
Affiliation:
National Virus Reference Laboratory, University College Dublin, Dublin, Ireland
C. De Gascun
Affiliation:
National Virus Reference Laboratory, University College Dublin, Dublin, Ireland
D. Igoe
Affiliation:
Health Service Executive (HSE) Health Protection Surveillance Centre, Dublin, Ireland
*
Author for correspondence: E. Robinson, E-mail: eveprobinson@gmail.com
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Abstract

Recent infection testing algorithms (RITA) for HIV combine serological assays with epidemiological data to determine likely recent infections, indicators of ongoing transmission. In 2016, we integrated RITA into national HIV surveillance in Ireland to better inform HIV prevention interventions. We determined the avidity index (AI) of new HIV diagnoses and linked the results with data captured in the national infectious disease reporting system. RITA classified a diagnosis as recent based on an AI < 1.5, unless epidemiological criteria (CD4 count <200 cells/mm3; viral load <400 copies/ml; the presence of AIDS-defining illness; prior antiretroviral therapy use) indicated a potential false-recent result. Of 508 diagnoses in 2016, we linked 448 (88.1%) to an avidity test result. RITA classified 12.5% of diagnoses as recent, with the highest proportion (26.3%) amongst people who inject drugs. On multivariable logistic regression recent infection was more likely with a concurrent sexually transmitted infection (aOR 2.59; 95% CI 1.04–6.45). Data were incomplete for at least one RITA criterion in 48% of cases. The study demonstrated the feasibility of integrating RITA into routine surveillance and showed some ongoing HIV transmission. To improve the interpretation of RITA, further efforts are required to improve completeness of the required epidemiological data.

Information

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s) 2019
Figure 0

Fig. 1.Application of RITA to new HIV diagnoses in Ireland during 2016. (a) Using Lag avidity assay; (b) using Lag avidity assay and p24 antigen.

Figure 1

Table 1.Characteristics associated with recent infections amongst new diagnoses of HIV in Ireland in 2016

Figure 2

Table 2.Characteristics associated with recent infection amongst new diagnoses of HIV MSM in Ireland in 2016