Title: Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers

Abstract

Most HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about (i) the time between infection and diagnosis (TI) for the general population, and (ii) the time between immigration and diagnosis for foreign-born persons. We developed a new statistical method for estimating the incidence of HIV-1 and the number of undiagnosed people living with HIV (PLHIV), based on dynamic modelling of heterogeneous HIV-1 surveillance data. The methods consist of a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI of HIV-1-positive individuals, and a novel incidence estimator which distinguishes between endogenous and exogenous infections by modelling explicitly the probability that a foreign-born person was infected either before or after immigration. The incidence estimator allows for direct calculation of the number of undiagnosed persons. The new methodology is illustrated combining heterogeneous surveillance data from Sweden between 2003 and 2015. A leave-one-out cross-validation study showed that the multiple-biomarker model was more accurate than single biomarkers (mean absolute error 1.01 vs ≥1.95). We estimate that 816 [95% credible interval (CI) 775-865] PLHIV were undiagnosed in 2015, representing a proportion of 10.8% (95% CImore » 10.3-11.4%) of all PLHIV. Here, the proposed methodology will enhance the utility of standard surveillance data streams and will be useful to monitor progress towards and compliance with the 90–90-90 UNAIDS target.« less

Authors:

Giardina, Federica  ^[1];

• Search DOE PAGES for author "Giardina, Federica"
• Search DOE PAGES for ORCID "0000-0002-3710-0940"

Romero-Severson, Ethan O.  ^[2];

• Search DOE PAGES for author "Romero-Severson, Ethan O."
• Search DOE PAGES for ORCID "0000-0002-8082-1225"

Axelsson, Maria ^[3]; Svedhem, Veronica ^[4]; Leitner, Thomas Kenneth  ^[2];

• Search DOE PAGES for author "Leitner, Thomas Kenneth"
• Search DOE PAGES for ORCID "0000-0001-8160-2588"

Britton, Tom ^[5]; Albert, Jan ^[4]

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+ Show Author Affiliations

1. Stockholm Univ., Stockholm (Sweden); Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. Medical Center Rotterdam, Rotterdam (The Netherlands)
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
3. Public Health Agency of Sweden, Solna (Sweden)
4. Karolinska Institute, Stockholm (Sweden); Karolinska Univ. Hospital, Stockholm (Sweden)
5. Stockholm Univ., Stockholm (Sweden)

Publication Date:

Fri May 10 00:00:00 EDT 2019

Research Org.:

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

USDOE Laboratory Directed Research and Development (LDRD) Program; Swedish Research Council (VR); National Institutes of Health (NIH); USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:

1532732

Report Number(s):

LA-UR-19-25855; LA-UR-19-30213
Journal ID: ISSN 0300-5771

Grant/Contract Number:  

89233218CNA000001; 340–2013-5003; K2014-57X-09935; R01AI087520

Resource Type:

Accepted Manuscript

Journal Name:

International Journal of Epidemiology

Additional Journal Information:

Journal Volume: 48; Journal Issue: 6; Journal ID: ISSN 0300-5771

Country of Publication:

United States

Language:

English

Subject:

60 APPLIED LIFE SCIENCES; Biological Science; HIV-1; incidence estimation; undiagnosed HIV-1 infections; BED assay; pol sequences