Research ArticleHIV

Sources of HIV infection among men having sex with men and implications for prevention

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Science Translational Medicine  06 Jan 2016:
Vol. 8, Issue 320, pp. 320ra2
DOI: 10.1126/scitranslmed.aad1863
  • Fig. 1. Study design.

    Nationwide sources of transmission were identified of MSM with evidence of recent infection in the first year before diagnosis (recipient MSM). (A) Out of all patients in the ATHENA cohort, men whose course of infection overlapped with the infection window were considered as potential transmitters. (B) Only those pairs with sequences from both individuals were considered for further analysis. (C and D) With viral phylogenetic analyses, the vast majority of pairs could be ruled out. All remaining pairs were considered phylogenetically probable. (E) On the basis of detailed clinical records, probable transmission events were characterized by stage in the HIV infection and care continuum. Because transmitters progressed in stage over time, we considered time-resolved transmission intervals. (F) Independent viral phylogenetic data from epidemiologically confirmed pairs were used to determine the phylogenetic probability of direct transmission during each interval. Statistical analyses were adjusted for extensive sampling and censoring biases.

  • Fig. 2. Phylogenetically probable transmission intervals, linked to stages in the infection and care continuum.

    (A) Left: Each recipient could have been infected during his infection window from multiple probable transmitters. For each transmitter, the transmission window was split into 6-week-long probable transmission intervals. Infection/care stages were assigned to these intervals on the basis of clinical data to reflect progression of the transmitters through the infection/care continuum. Right: Relationship between the 14 infection/care stages as defined in Table 2. Transmitters progress unidirectionally, except for stages after first viral suppression, or when individuals reenter care (as indicated by arrows). (B) For each stage, the total number of observed transmission intervals to recipient MSM during their infection windows is shown by date of diagnosis of the recipients. Overall, the number of probable transmission intervals per recipient increases with time, reflecting the increasing number of infected men in care. Transmitters are increasingly less likely to have been diagnosed by 2013, resulting in a decreasing number of undiagnosed transmission intervals toward the present. (C) In addition to censoring, diagnosed transmitters may not have a sequence sampled. Comparing men with and without a sequence in the near-complete population cohort, we could adjust for these biases. The total number of expected missing transmission intervals to recipients is shown, along with 95% bootstrap confidence intervals. Observed and expected missing transmission intervals were associated with phylogenetic transmission probabilities, which sum to 1 per recipient.

  • Fig. 3. Proportion of transmissions by stage in the infection and care continuum versus proportion of these stages among infected men.

    (A) Relative frequency of infection/care stages in the population, among potential transmitters that overlap with the infection windows of recipient MSM and could have, in principle, transmitted to one of the recipient MSM (stage A in Fig. 1; color codes as in Fig. 2). (B) Proportion of the 617 transmission events attributable to each infection/care stage (bar: 95% bootstrap confidence interval).

  • Fig. 4. Impact of biomedical interventions among MSM in the Netherlands.

    Estimated proportion of transmissions that could have been averted in the period July 2008 to December 2010 if the corresponding additional prevention strategies had been implemented by July 2008 (line, median; box, bootstrap interquartile range; whiskers, 95% bootstrap confidence interval). Scenarios were varied by annual testing coverage of phylogenetically identified, probable transmitters. Current testing coverage was 17%, corresponding to the proportion of probable transmitters that had a negative test in the 12 months before diagnosis.

  • Table 1. HIV incidence trends and care for infected MSM in the Netherlands and other countries.
    CountryUninfected
    MSM
    testing
    annually
    Diagnosed
    MSM
    receiving
    ART
    Treated
    MSM with
    suppressed
    viral load
    MSM
    retained
    in care
    HIV incidence
    among MSM
    Year%Year%Median
    CD4
    count at
    ART
    initiation
    (cells/ml)
    Year%Viral load
    threshold
    (cps/ml)
    Year%YearTrend
    The Netherlands2003??200379202200380<1002003922003Increasing*
    201338.4201390382201391<1002012952013Stable*
    Australia201361.1201375379§¶201388¶||<50201396§¶2013Stable to
    increasing**
    British
    Columbia
    200951††201485‡‡411‡‡201484‡‡<50201186¶§§2013Stable¶¶
    Switzerland201039.3201486|| ||402|| ||201296¶***<200201297¶†††2014Decreasing new
    diagnoses‡‡‡
    UK201036.4201386§§§420¶¶¶201391|| || ||<200201395|| || ||2013Stable****

    *From (47). †From The EMIS Network. EMIS 2010: The European Men-Who-Have-Sex-With-Men Internet Survey. Findings from 38 countries. Stockholm: European Centre for Disease Prevention and Control, 2013. ‡From Gay Community Periodic Surveys, https://kirby.unsw.edu.au/projects/gay-community-periodic-surveys, reported in HIV, hepatitis, and sexually transmissible infections in Australia Annual surveillance report 2014. §From Australian HIV Observational Database Annual Report 2014, reporting care indicators in a closed observational cohort. ¶Estimate not specific to MSM. ||From the Australian HIV Observational Database, reported in HIV, hepatitis, and sexually transmissible infections in Australia Annual surveillance report 2014. **From fact sheet HIV and AIDS in Australia, 20th International AIDS conference.

    ††From Mancount, prospective cross-sectional survey in Vancouver, www.mancount.ca/files/ManCount_Report2010.pdf. ‡‡From HIV monitoring quarterly report for British Columbia, fourth quarter 2014. §§From B. Nosyk, J. S. Montaner, G. Colley, V. D. Lima, K. Chan, K. Heath, B. Yip, H. Samji, M. Gilbert, R. Barrios, R. Gustafson, R. S. Hogg, The cascade of HIV care in British Columbia, Canada, 1996–2011: A population-based retrospective cohort study. Lancet Infect. Dis. 14, 40–49 (2014). ¶¶From www.phac-aspc.gc.ca/aids-sida/publication/epi/2010/index-eng.php. || ||2621 of 3081 MSM on ART and registered in the Swiss HIV Cohort Study, personal communication with the Datacenter of the Swiss HIV Cohort Study.

    ***From P. Kohler, A. J. Schmidt, B. Ledergerber, P. Vernazza, CROI2015, www.croiconference.org/sites/default/files/posters-2015/1008.pdf. †††From www.shcs.ch/155-shcs-key-data-figures, update June 2014. ‡‡‡From HIV- und STI-Fallzahlen 2014: Berichterstattung, Analysen und Trends, in comparison with numbers for 2008 in the 2012 report, www.bag.admin.ch/hiv_aids/12472/12480/12481/12484/index.html?lang=de. §§§From www.gov.uk/government/statistics/hiv-data-tables. ¶¶¶Within 9 months before ART initiation, personal communication PHE. || || ||From HIV in the UK: 2014 Report. ****From P. J. Birrell, O. N. Gill, V. C. Delpech, A. E. Brown, S. Desai, T. R. Chadborn, B. D. Rice, D. De Angelis, HIV incidence in men who have sex with men in England and Wales 2001–10: A nationwide population study. Lancet Infect. Dis. 13, 313–318 (2013).

    • Table 2. Stages in the HIV infection and care continuum.
      Infection/care stage of transmitterDefinition
      UndiagnosedTransmission intervals whose midpoint is before diagnosis:
        Confirmed to have recent infection at diagnosisAll transmission intervals of transmitters that were
      confirmed to have recent infection at time of diagnosis.
        Estimated to have recent infectionConsidering transmitters that had no evidence of recent infection
      at time of diagnosis, all transmission intervals whose midpoint is less
      than 12 months after the estimated infection date.
        Estimated to have chronic infectionConsidering transmitters that had no evidence of recent infection
      at time of diagnosis, all transmission intervals whose midpoint is
      more than 12 months after the estimated infection date.
      DiagnosedTransmission intervals whose midpoint is after diagnosis and before
      ART start (only of transmitters that are in contact with care services):
        Diagnosed <3 months, confirmed recent
      infection at diagnosis
      Considering transmitters who had confirmed recent infection at time
      of diagnosis, all transmission intervals whose midpoint is within the
      first 3 months after diagnosis.
        No CD4 measuredNo available CD4 count since diagnosis up to the midpoint of the interval.
        CD4 >500CD4 counts remained above 500 cells/ml between the first
      CD4 count and the midpoint of the interval.
        CD4 350–500CD4 counts decreased to 350–500 cells/ml between the first
      CD4 count and the midpoint of the interval.
        CD4 <350CD4 counts decreased to below 350 cells/ml between the first
      CD4 count and the midpoint of the interval.
      ART initiatedTransmission intervals whose midpoint is after ART start (only of
      transmitters that are in contact with care services):
        Before first viral suppressionNo first viral load measurement below 100 copies/ml in any
      transmission interval of the transmitter after ART start
        After first viral suppression*
          No viral load measured*No viral load measurement in any transmission interval
      of the transmitter after ART start
          No viral suppression*At least one viral load measurement at or above 100 copies/ml in
      any transmission interval of the transmitter after ART start
          Viral suppression, one observation*One viral load measurement in any transmission interval of the
      transmitter after ART start, which is below 100 copies/ml.
          Viral suppression, ≥2 observations*Several viral load measurements in any transmission interval of the
      transmitter after ART start, all of which are below 100 copies/ml.
      Not in contactNo patient record (last contact, clinic visit, CD4 measurement,
      viral load measurement) in the past and future 9 months from
      the midpoint of the transmission interval.

      *Although flow through the stages is typically unidirectional, men could move freely between these stages.

      • Table 3. Characteristics of the recipient MSM with identified sources of transmission.

        IQR, interquartile range.

        CharacteristicRecipient MSM with a phylogenetically
        probable transmitter (n = 617)
        Recipient MSM with or
        without a sequence (n = 1794)
        Diagnosed
        MSM (n = 7978)
        Evidence for infection in the past year
          Previous negative test in the past year (%)777617
          Laboratory diagnosis (%)872
          Clinical diagnosis of acute infection (%)15174
        Age at diagnosis (years; mean and IQR)36.8
        (29.5–42.9)
        37.2
        (29.9–43.5)
        38.7
        (31.3–45.1)
        First CD4 count within 12 months of diagnosis
        and before ART start (cells/ml; mean
        and IQR)
        505
        (350–630)
        534
        (360–670)
        402
        (200–560)
        Viral load count within 12 months of diagnosis
        (log10 RNA; mean and IQR)
        4.9
        (4.4–5.5)
        4.8
        (4.3–5.4)
        4.7
        (4.3–5.3)
        In care in the Amsterdam metropolitan area (%)45.143.543.6
        Last negative test within 12 months before
        diagnosis (%)
        77.076.117.1
        Self-reported in country infection* (%)96.991.988.5

        *Of those self-reporting a country of origin.

        • Table 4. Proportion of transmissions by stage in the HIV infection and care continuum.
          Infection/care stage of transmitter% of transmissions by time of diagnosis of recipient MSM (95% confidence interval)
          Overall
          (n = 617)
          Jul. 1996 to
          Apr. 2006
          (n = 165)
          May 2006 to
          Dec. 2007
          (n = 145)
          Jan. 2008 to
          Jun. 2009
          (n = 151)
          Jul. 2009 to
          Dec. 2010
          (n = 156)
          Undiagnosed (total)70.9 (65.8–72.5)67.6 (59.3–72.7)72.3 (64.2–76.9)71.8 (63.4–76.3)72.2 (63.3–76.3)
            Confirmed recent infection at diagnosis15.5 (11.9–17.4)15 (7.6–19.4)21.7 (15–26.5)16.4 (11–20.8)9.4 (5.6–14.1)
            Estimated to have recent infection25.1 (19.4–28.1)17.3 (11.7–22.7)23 (15.1–30.1)25.9 (15.4–33.6)34.6 (19.4–43.4)
            Estimated to have chronic infection30.3 (28–34)35.2 (30.2–42)27.6 (22.4–34)29.5 (24.2–36.1)28.2 (23–35.7)
          Diagnosed (total)22.4 (20.7–26.2)23.6 (18.5–29.7)22.9 (18.6–29.1)22.8 (18.3–29.4)20.7 (17.4–27.3)
            Diagnosed <3 months, recent infection at diagnosis2.9 (2.2–4.1)2.5 (1–4.9)3.2 (1.7–5.5)3 (1.9–5.4)2.8 (1.8–4.4)
            No CD4 measured1.6 (1.2–2.4)2.9 (1.6–4.8)0.8 (0.4–1.8)1.5 (0.6–3)1 (0.6–2.1)
            CD4 >5008.3 (7–10.3)10.2 (6.7–14.2)7 (4.5–10.8)8.7 (5.9–12.5)7.1 (5.4–10.1)
            CD4 in 350–5006.4 (5.4–7.9)4.8 (2.6–7.8)7.3 (5.1–10.5)5.9 (4.2–8.3)7.7 (5.7–11)
            CD4 <3503.4 (2.5–4.3)3.2 (1.2–5.5)4.6 (2.6–6.6)3.7 (2.2–5.6)2.1 (1.3–3.3)
          ART initiated (total)5.7 (5.2–7.8)7 (4.8–11.7)3.7 (2.2–6.5)4.9 (3.7–8.1)6.7 (5.4–10.2)
            Before first viral suppression1.8 (1.6–2.7)2.2 (1.2–4.4)0.7 (0.4–1.5)1.3 (0.9–2.6)2.8 (2.1–4.6)
            After first viral suppression
              No viral load measured0.5 (0.3–1)0.9 (0.1–2.4)0.1 (0–0.3)0.3 (0.1–0.9)0.8 (0.4–1.8)
              No viral suppression1.4 (0.9–2.1)2.8 (1.2–5.2)1.2 (0.4–2.6)0.9 (0.4–1.9)0.5 (0.1–1)
              Viral suppression, one observation0.4 (0.3–0.8)0.1 (0–0.5)0.2 (0–0.8)0.5 (0.2–1.7)0.6 (0.3–1.5)
          Viral suppression, ≥2 observations1.6 (1.1–2.5)1 (0.1–2.6)1.5 (0.6–3.1)1.9 (0.9–3.6)2 (1.1–3.6)
          Not in contact1 (0.7–1.6)1.8 (0.8–3.4)1.1 (0.4–2.3)0.5 (0.2–1.4)0.4 (0.2–0.8)
          Recent infection (total)43.5 (36.6–46)34.9 (25.4–40.6)47.9 (36.9–54.8)45.3 (33.3–54.1)47.7 (32.8–53.8)

        Supplementary Materials

        • www.sciencetranslationalmedicine.org/cgi/content/full/8/320/320ra2/DC1

          Extended acknowledgments

          Materials and Methods

          Fig. S1. Number of identified recipient MSM by 3-month intervals.

          Fig. S2. Duration of infection windows of recipient MSM.

          Fig. S3. Snapshot of the reconstructed viral phylogeny.

          Fig. S4. Uncertainty in the estimated genetic distance between sequences from the transmitter and recipient of potential transmission pairs.

          Fig. S5. Genetic distance between sequence pairs from previously published, epidemiologically confirmed transmitter-recipient pairs, and sequence pairs from the phylogenetically probable transmission pairs in this study.

          Fig. S6. Right censoring at past, hypothetical database closure times.

          Fig. S7. Sequence sampling probabilities by stage in the infection and care continuum.

          Fig. S8. Individual-level variation in phylogenetically derived transmission probabilities by infection/care stages.

          Fig. S9. Frequency of infection/care stages among phylogenetically probable transmitters.

          Fig. S10. Phylogenetically derived transmission probabilities of observed transmission intervals.

          Fig. S11. Transmission risk ratio from men after ART start compared to diagnosed untreated men with CD4 >500 cells/ml.

          Fig. S12. Sensitivity analysis on the impact of PrEP with lower efficacy.

          Fig. S13. Sensitivity analysis on the impact of lower or higher PrEP coverage.

          Fig. S14. Impact of sampling and censoring adjustments on the estimated proportion of transmissions from stages in the infection and care continuum.

          Fig. S15. Impact of phylogenetic transmission probabilities on the estimated proportion of transmissions from stages in the infection and care continuum.

          Fig. S16. Impact of infection time estimates on the estimated proportion of transmissions from stages in the infection and care continuum.

          Fig. S17. Impact of phylogenetic clustering criteria on the estimated proportion of transmissions from stages in the infection and care continuum.

          Fig. S18. Impact of additional genetic distance criteria on the estimated proportion of transmissions from stages in the infection and care continuum.

          Fig. S19. Impact of sequence sampling and censoring adjustments on the estimated proportion of averted infections.

          Fig. S20. Impact of phylogenetic transmission probabilities on the estimated proportion of averted infections.

          Fig. S21. Impact of infection time estimates and phylogenetic exclusion criteria on the estimated proportion of averted infections.

          Fig. S22. Impact of additional genetic distance criteria on the estimated proportion of averted infections per biomedical intervention.

          Fig. S23. Differences in transmission networks with and without a recipient MSM.

          Fig. S24. Exploratory local polynomial regression fits to the time to diagnosis of MSM with a last negative test in the ATHENA cohort.

          Fig. S25. Multivariable gamma regression model fitted to the time between the midpoint of the seroconversion interval and diagnosis of MSM with a last negative test in the ATHENA cohort.

          Fig. S26. Estimated probability that the time between the midpoint of the seroconversion interval and diagnosis among MSM with a last negative test is larger than t years.

          Fig. S27. Time to diagnosis estimates.

          Fig. S28. Genetic distance among sequence pairs from transmitter-recipient pairs in the Belgium and Swedish transmission chains.

          Fig. S29. Approximate type I error of the phylogenetic clustering criterion as a function of the clade frequency threshold.

          Fig. S30. Type I error and power of the coalescence compatibility test.

          Fig. S31. Estimated fraction of noncensored potential transmission intervals.

          Fig. S32. Time between last negative test and diagnosis among MSM diagnosed in July 2009 to December 2010 and probable transmitters of recipients diagnosed in July 2009 to December 2010.

          Table S1. Clinical and viral sequence data used in this study.

          Table S2. Potential transmitters and potential transmission pairs to the recipient MSM.

          Table S3. Identified phylogenetically probable transmitters and phylogenetically probable transmission pairs to the recipient MSM.

          Table S4. Demographic and clinic characteristics of the 3025 MSM with a last negative test, which were used to fit the multivariable regression model.

          References (4852)

        • Supplementary Material for:

          Sources of HIV infection among men having sex with men and implications for prevention

          Oliver Ratmann,* Ard van Sighem, Daniela Bezemer, Alexandra Gavryushkina, Suzanne Jurriaans, Annemarie Wensing, Frank de Wolf, Peter Reiss, Christophe Fraser, ATHENA observational cohort

          *Corresponding author. E-mail: oliver.ratmann{at}imperial.ac.uk

          Published 6 January 2016, Sci. Transl. Med. 8, 320ra2 (2016)
          DOI: 10.1126/scitranslmed.aad1863

          This PDF file includes:

          • Extended acknowledgments
          • Materials and Methods
          • Fig. S1. Number of identified recipient MSM by 3-month intervals.
          • Fig. S2. Duration of infection windows of recipient MSM.
          • Fig. S3. Snapshot of the reconstructed viral phylogeny.
          • Fig. S4. Uncertainty in the estimated genetic distance between sequences from the transmitter and recipient of potential transmission pairs.
          • Fig. S5. Genetic distance between sequence pairs from previously published, epidemiologically confirmed transmitter-recipient pairs, and sequence pairs from the phylogenetically probable transmission pairs in this study.
          • Fig. S6. Right censoring at past, hypothetical database closure times.
          • Fig. S7. Sequence sampling probabilities by stage in the infection and care continuum.
          • Fig. S8. Individual-level variation in phylogenetically derived transmission probabilities by infection/care stages.
          • Fig. S9. Frequency of infection/care stages among phylogenetically probable transmitters.
          • Fig. S10. Phylogenetically derived transmission probabilities of observed transmission intervals.
          • Fig. S11. Transmission risk ratio from men after ART start compared to diagnosed untreated men with CD4 >500 cells/ml.
          • Fig. S12. Sensitivity analysis on the impact of PrEP with lower efficacy.
          • Fig. S13. Sensitivity analysis on the impact of lower or higher PrEP coverage.
          • Fig. S14. Impact of sampling and censoring adjustments on the estimated proportion of transmissions from stages in the infection and care continuum.
          • Fig. S15. Impact of phylogenetic transmission probabilities on the estimated proportion of transmissions from stages in the infection and care continuum.
          • Fig. S16. Impact of infection time estimates on the estimated proportion of transmissions from stages in the infection and care continuum.
          • Fig. S17. Impact of phylogenetic clustering criteria on the estimated proportion of transmissions from stages in the infection and care continuum.
          • Fig. S18. Impact of additional genetic distance criteria on the estimated proportion of transmissions from stages in the infection and care continuum.
          • Fig. S19. Impact of sequence sampling and censoring adjustments on the estimated proportion of averted infections.
          • Fig. S20. Impact of phylogenetic transmission probabilities on the estimated proportion of averted infections.
          • Fig. S21. Impact of infection time estimates and phylogenetic exclusion criteria on the estimated proportion of averted infections.
          • Fig. S22. Impact of additional genetic distance criteria on the estimated proportion of averted infections per biomedical intervention.
          • Fig. S23. Differences in transmission networks with and without a recipient MSM.
          • Fig. S24. Exploratory local polynomial regression fits to the time to diagnosis of MSM with a last negative test in the ATHENA cohort.
          • Fig. S25. Multivariable gamma regression model fitted to the time between the midpoint of the seroconversion interval and diagnosis of MSM with a last negative test in the ATHENA cohort.
          • Fig. S26. Estimated probability that the time between the midpoint of the seroconversion interval and diagnosis among MSM with a last negative test is larger than t years.
          • Fig. S27. Time to diagnosis estimates.
          • Fig. S28. Genetic distance among sequence pairs from transmitter-recipient pairs in the Belgium and Swedish transmission chains.
          • Fig. S29. Approximate type I error of the phylogenetic clustering criterion as a function of the clade frequency threshold.
          • Fig. S30. Type I error and power of the coalescence compatibility test.
          • Fig. S31. Estimated fraction of noncensored potential transmission intervals.
          • Fig. S32. Time between last negative test and diagnosis among MSM diagnosed in July 2009 to December 2010 and probable transmitters of recipients diagnosed in July 2009 to December 2010.
          • Table S1. Clinical and viral sequence data used in this study.
          • Table S2. Potential transmitters and potential transmission pairs to the recipient MSM.
          • Table S3. Identified phylogenetically probable transmitters and phylogenetically probable transmission pairs to the recipient MSM.
          • Table S4. Demographic and clinic characteristics of the 3025 MSM with a last negative test, which were used to fit the multivariable regression model.
          • References (4852)

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