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. 2016 Jul 12;11(7):e0159021.
doi: 10.1371/journal.pone.0159021. eCollection 2016.

Estimation of the Undiagnosed Intervals of HIV-Infected Individuals by a Modified Back-Calculation Method for Reconstructing the Epidemic Curves

Ngai Sze Wong  1   2   3 , Ka Hing Wong  4 , Man Po Lee  5 , Owen T Y Tsang  6 , Denise P C Chan  1 , Shui Shan Lee  1
Affiliations

Estimation of the Undiagnosed Intervals of HIV-Infected Individuals by a Modified Back-Calculation Method for Reconstructing the Epidemic Curves

Ngai Sze Wong et al. PLoS One. .

Abstract

Background: Undiagnosed infections accounted for the hidden proportion of HIV cases that have escaped from public health surveillance. To assess the population risk of HIV transmission, we estimated the undiagnosed interval of each known infection for constructing the HIV incidence curves.

Methods: We used modified back-calculation methods to estimate the seroconversion year for each diagnosed patient attending any one of the 3 HIV specialist clinics in Hong Kong. Three approaches were used, depending on the adequacy of CD4 data: (A) estimating one's pre-treatment CD4 depletion rate in multilevel model;(B) projecting one's seroconversion year by referencing seroconverters' CD4 depletion rate; or (C) projecting from the distribution of estimated undiagnosed intervals in (B). Factors associated with long undiagnosed interval (>2 years) were examined in univariate analyses. Epidemic curves constructed from estimated seroconversion data were evaluated by modes of transmission.

Results: Between 1991 and 2010, a total of 3695 adult HIV patients were diagnosed. The undiagnosed intervals were derived from method (A) (28%), (B) (61%) and (C) (11%) respectively. The intervals ranged from 0 to 10 years, and were shortened from 2001. Heterosexual infection, female, Chinese and age >64 at diagnosis were associated with long undiagnosed interval. Overall, the peaks of the new incidence curves were reached 4-6 years ahead of reported diagnoses, while their contours varied by mode of transmission. Characteristically, the epidemic growth of heterosexual male and female declined after 1998 with slight rebound in 2004-2006, but that of MSM continued to rise after 1998.

Conclusions: By determining the time of seroconversion, HIV epidemic curves could be reconstructed from clinical data to better illustrate the trends of new infections. With the increasing coverage of antiretroviral therapy, the undiagnosed interval can add to the measures for assessing HIV transmission risk in the population.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Annual number of reported new diagnoses and prevalent cases (number of diagnosed HIV-infected cases who were alive), estimated new infections and undiagnosed infections (total number of infections remaining undiagnosed) with uncertainty intervals smoothed by Seasonal-Trend Decomposition Procedure based on Loess for (a) heterosexual male, (b) MSM, (c) heterosexual female and (d) IDU.
Fig 2
Fig 2. Sensitivity analysis of new infection curves constructed by computing the first quartile, third quartile and median of the simulation results in Group A and B, and the median of undiagnosed interval in reference group (Group A, Group B, Group A and B) for Group C, by mode of transmission.
Fig 3
Fig 3
A) Temporal variation of the proportion of undiagnosed intervals (years) and the seroconversion estimation methods applied. B) Yearly variation of undiagnosed intervals (years) by mode of transmission.
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