1. Epidemiology and Global Health
  2. Evolutionary Biology

Transmission Histories: Traversing missing links in the spread of HIV

Combining clinical and genetic data can improve the effectiveness of virus tracking with the aim of reducing the number of HIV cases by 2030.
https://doi.org/10.7554/eLife.82610
Share this article
Cite this article
  1. Erin Brintnell
  2. Art Poon
(2022)
Transmission Histories: Traversing missing links in the spread of HIV
eLife 11:e82610.
https://doi.org/10.7554/eLife.82610
  2. Download BibTeX
  3. Download .RIS
  1. Erin Brintnell
  2. Art Poon  Is a corresponding author
  1. Department of Pathology and Laboratory Medicine, Western University, Canada
  2. Department of Computer Science, Western University, Canada

The human immunodeficiency virus type 1 (HIV-1), which can lead to acquired immune deficiency syndrome (AIDS), remains a leading cause of death and a health threat worldwide, with over 38.4 million people currently living with the virus. Global health sector strategies strive to end HIV-1 epidemics by 2030 (Duncombe et al., 2019). This requires significant investment in resources to treat and prevent the disease, such as reducing the number of people who do not know they are carrying the virus and improving the availability and affordability of effective treatments.

In cities that have scaled up HIV-1 treatment and prevention, it will be crucial to establish whether new HIV-1 infections are due to ongoing local transmission or to infections acquired abroad. This means reconstructing the spread of HIV-1 between individuals through contact tracing: interviewing people recently diagnosed with HIV, and locating and notifying their intimate partners. However, contact tracing is both time-consuming and intrusive (El-Sadr et al., 2022).

A cost-effective alternative to contact tracing is to compare the genomic sequences of HIV-1 samples from different patients, which are often collected to screen for mutations that confer drug resistance. Infections that are genetically similar are more likely to be related through recent transmissions. This is especially true for HIV-1, a rapidly evolving virus that becomes genetically unique within months of an infection (Williamson, 2003).

These genetic sequences can be used to build a tree that represents the shared evolutionary history of the infections and approximates the history of recent transmissions (De Maio et al., 2018; Romero-Severson et al., 2014). Furthermore, the spread of infections from one place to another can be extrapolated by reconstructing locations of ‘ancestral’ infections at deeper nodes of the tree from the known locations at the tips (Faria et al., 2011). The accuracy of these estimates, however, is impeded by the unknown number of people with undiagnosed infections, or with diagnosed infections that have not been sequenced (Didelot et al., 2017). In addition, reconstructing transmission patterns from HIV-1 sequences comes with its own ethical challenges because HIV-1 transmission is criminalized in many countries (Dawson et al., 2020).

Now, in eLife, Oliver Ratmann at the HIV Transmission Elimination Amsterdam Consortium and colleagues – including Alexandra Blenkinsop as first author – report an innovative approach to overcome the disadvantages of sequence analysis (Blenkinsop et al., 2022). Blenkinsop et al. combined different data sources to reconstruct the transmission histories of HIV-1 in Amsterdam, which has the highest concentration of HIV-1 cases in the Netherlands. Amsterdam is also part of the Fast-Track city network, which provides funds to expand effective HIV prevention, testing and treatment services.

Blenkinsop et al. extended the standard approach of reconstructing transmission histories from HIV-1 sequences by incorporating additional information from clinical biomarkers (biological indicators of disease progression or response to treatment) and other patient data (Figure 1). A statistical model was fitted to two biomarkers: the number of HIV-1 particles circulating in the blood (the viral load) and the number of white blood cells targeted by HIV-1. Based on how these biomarkers changed over time, it was possible to estimate the length of time between a person’s HIV-1 infection and diagnosis. These estimates were then used to infer how many cases were transmitted from people with unsequenced infections, adjusting for factors like route of transmission (e.g., injection drug use), age group, and place of birth.

Figure 1
Download asset Open asset
Estimating the number of unsampled HIV-1 infections.

The top panel illustrates how a chain of HIV-1 infections may be partially sampled over time. The top dashed line shows an infection (represented by the virus particle symbol) that is transmitted (red arrow) before it is sequenced (DNA symbol), with the time between the infection occurring and sequencing taking place indicated by the two-headed arrow. The dashed line in the centre shows an infection resulting from transmission from the first infection, which is transmitted (red arrow) but never sequenced. The dashed line on the bottom represents a third infection resulting from the second infection, that is sequenced (DNA symbol) more quickly than the original infection. The bottom panel depicts two phylogenetic trees. The first tree (green) is inferred from the available sequences (in this case, the two infections sequenced in the top panel). By fitting a statistical model to HIV-1 cases with estimated dates of infection and clinical data, the number of unsampled infections (‘missing links’) in the new tree (red) can be extrapolated for different populations.

Despite extensive measures to curb the transmission of HIV in Amsterdam, results from Blenkinsop et al. suggest that many HIV-1 infections have remained undiagnosed for a long time, especially among heterosexual residents and recent arrivals from sub-Saharan Africa. Further, they provide evidence of ongoing HIV-1 transmission within the city over the duration of the five-year study. These results suggest that, while Amsterdam has made significant progress in reducing the spread of HIV-1, closing the final gap to end the local epidemic by 2030 remains a challenge.

The study also highlights the importance of linking HIV-1 sequences to both clinical and demographic information to determine which groups have been neglected by the generalized scale-up of public health testing and treatment. This may also be a critical step for other cities in the FastTrack initiative. Furthermore, the work of Blenkinsop et al. mirrors ongoing challenges in tracking and controlling other infectious diseases like COVID-19, which is characterised by an abundance of viral genome sequences but a lack of linked contextual information, including clinical outcomes, travel histories and sampling strategies (Chiara et al., 2021; Chen et al., 2022).

References

Article and author information

Author details

  1. Erin Brintnell

    Erin Brintnell is in the Department of Pathology and Laboratory Medicine, Western University, London, Canada
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5042-7799

  2. Art Poon

    Art Poon in the Department of Pathology and Laboratory Medicine, the Department of Microbiology and Immunology, and the Department of Computer Science, Western University, London, Canada
    For correspondence
    apoon42@uwo.ca
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3779-154X

Publication history

  1. Version of Record published: September 30, 2022 (version 1)

Copyright

© 2022, Brintnell and Poon

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 216
    Page views
  • 38
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Erin Brintnell
  2. Art Poon
(2022)
Transmission Histories: Traversing missing links in the spread of HIV
eLife 11:e82610.
https://doi.org/10.7554/eLife.82610

Categories and tags

Research organism

    1. Related to

    Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam

    Alexandra Blenkinsop, Mélodie Monod ... Oliver Ratmann
  2. Further reading

Further reading

    1. Epidemiology and Global Health
    2. Evolutionary Biology

    Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam

    Alexandra Blenkinsop, Mélodie Monod ... Oliver Ratmann
    Research Article Updated

    Background:

    More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion of Amsterdam HIV infections that originated within the city, from Amsterdam residents. We also aimed to estimate the proportion of recent HIV infections during the 5-year period 2014–2018 in Amsterdam that remained undiagnosed.

    Methods:

    We located diagnosed HIV infections in Amsterdam using postcode data (PC4) at time of registration in the ATHENA observational HIV cohort, and used HIV sequence data to reconstruct phylogeographically distinct, partially observed Amsterdam transmission chains. Individual-level infection times were estimated from biomarker data, and used to date the phylogenetically observed transmission chains as well as to estimate undiagnosed proportions among recent infections. A Bayesian Negative Binomial branching process model was used to estimate the number, size, and growth of the unobserved Amsterdam transmission chains from the partially observed phylogenetic data.

    Results:

    Between 1 January 2014 and 1 May 2019, there were 846 HIV diagnoses in Amsterdam residents, of whom 516 (61%) were estimated to have been infected in 2014–2018. The rate of new Amsterdam diagnoses since 2014 (104 per 100,000) remained higher than the national rates excluding Amsterdam (24 per 100,000), and in this sense Amsterdam remained a HIV hotspot in the Netherlands. An estimated 14% [12–16%] of infections in Amsterdan MSM in 2014–2018 remained undiagnosed by 1 May 2019, and 41% [35–48%] in Amsterdam heterosexuals, with variation by region of birth. An estimated 67% [60–74%] of Amsterdam MSM infections in 2014–2018 had an Amsterdam resident as source, and 56% [41–70%] in Amsterdam heterosexuals, with heterogeneity by region of birth. Of the locally acquired infections, an estimated 43% [37–49%] were in foreign-born MSM, 41% [35–47%] in Dutch-born MSM, 10% [6–18%] in foreign-born heterosexuals, and 5% [2–9%] in Dutch-born heterosexuals. We estimate the majority of Amsterdam MSM infections in 2014–2018 originated in transmission chains that pre-existed by 2014.

    Conclusions:

    This combined phylogenetic, epidemiologic, and modelling analysis in the UNAIDS Fast-Track City Amsterdam indicates that there remains considerable potential to prevent HIV infections among Amsterdam residents through city-level interventions. The burden of locally acquired infection remains concentrated in MSM, and both Dutch-born and foreign-born MSM would likely benefit most from intensified city-level interventions.

    Funding:

    This study received funding as part of the H-TEAM initiative from Aidsfonds (project number P29701). The H-TEAM initiative is being supported by Aidsfonds (grant number: 2013169, P29701, P60803), Stichting Amsterdam Dinner Foundation, Bristol-Myers Squibb International Corp. (study number: AI424-541), Gilead Sciences Europe Ltd (grant number: PA-HIV-PREP-16-0024), Gilead Sciences (protocol numbers: CO-NL-276-4222, CO-US-276-1712, CO-NL-985-6195), and M.A.C AIDS Fund.

    1. Epidemiology and Global Health

    Reducing societal impacts of SARS-CoV-2 interventions through subnational implementation

    Mark M Dekker, Luc E Coffeng ... Sake J de Vlas
    Research Article Updated

    To curb the initial spread of SARS-CoV-2, many countries relied on nation-wide implementation of non-pharmaceutical intervention measures, resulting in substantial socio-economic impacts. Potentially, subnational implementations might have had less of a societal impact, but comparable epidemiological impact. Here, using the first COVID-19 wave in the Netherlands as a case in point, we address this issue by developing a high-resolution analysis framework that uses a demographically stratified population and a spatially explicit, dynamic, individual contact-pattern based epidemiology, calibrated to hospital admissions data and mobility trends extracted from mobile phone signals and Google. We demonstrate how a subnational approach could achieve similar level of epidemiological control in terms of hospital admissions, while some parts of the country could stay open for a longer period. Our framework is exportable to other countries and settings, and may be used to develop policies on subnational approach as a better strategic choice for controlling future epidemics.

    1. Epidemiology and Global Health
    2. Immunology and Inflammation

    Evaluation of antibody kinetics and durability in health individuals vaccinated with inactivated COVID-19 vaccine (CoronaVac): a cross-sectional and cohort study in Zhejiang, China

    Hangjie Zhang, Qianhui Hua ... Huakun Lv
    Research Article

    Background: Although inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed.

    Methods: We enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests.

    Results: Our results revealed that binding antibody IgM peaked 14-28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The neutralized fraction subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89) to 17.8% (16/90).

    Conclusions: Two doses of CoronaVac vaccine resulted in limited protection over a short duration. The inactivated vaccine booster can reverse the decrease of antibody levels to prime strain, but it does not elicit potent neutralization against Omicron; therefore, the optimization of booster procedures is vital.

    Funding: Key Research and Development Program of Zhejiang Province; Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission; Major Program of Zhejiang Municipal Natural Science Foundation; Explorer Program of Zhejiang Municipal Natural Science Foundation.