A few fast-growing clusters now sustain Switzerland's HIV epidemic, cohort analysis finds

Switzerland has a stated goal of halting HIV transmission by 2030. A molecular epidemiology study published in The Lancet HIV on September 21 offers a map of what stands in the way — and it is not a diffuse, evenly spread epidemic but a small set of chains doing most of the work [s1].

The global backdrop is a disease still far from contained. WHO's HIV fact sheet records an estimated 41.0 million people living with HIV at the end of 2025, 64% of them in the WHO African Region, with an estimated 1.2 million people acquiring HIV and 570,000 dying of HIV-related causes in 2025 [s2].

Reading the epidemic in its genomes

The study drew on the Swiss HIV Cohort Study, one of the longest-running of its kind. Researchers analysed 32,294 HIV-1 pol sequences from 16,428 participants enrolled between August 14, 1984, and May 19, 2025 [s1]. Sequences were aligned and clustered using a 0.01 Tamura-Nei 93 genetic distance threshold, and networks were built at the level of individual participants to identify clusters and track how they grew over time [s1].

The logic is that viruses that are genetically close reflect people who are epidemiologically close. Watching which clusters expand, and when, turns a static registry into something closer to a live view of where transmission is still happening.

A fragmented epidemic with a few hot chains

Just under half the cohort sat inside a cluster: 7,387 participants (45.0%) belonged to 1,131 clusters [s1]. But the size distribution was highly skewed. Sixty-two percent of clusters contained only two individuals, while a handful of large clusters accounted for thousands of participants [s1].

The historical shape of the epidemic came through in the genomes. It fragmented from a single dominant cluster among people who inject drugs in the 1990s into numerous smaller clusters, predominantly among gay, bisexual, and other men who have sex with men [s1]. That is the arc of a successful harm-reduction era giving way to a different, more dispersed transmission pattern.

The operational finding is where recent growth concentrated. Since 2016, 32.6% of total cluster growth was concentrated in a set of 23 fast-growing clusters [s1]. These mostly comprised western European men who have sex with men with high rates of condomless sex, and cluster growth was strongly associated with viraemia among connected participants [s1].

Why viraemia is the thread

That last association is the pivot of the whole analysis. Growth clustered where connected people had detectable virus in their blood. Treatment that suppresses the virus to undetectable levels also makes it untransmittable — the principle behind treatment as prevention — so a cluster sustained by viraemia is, by definition, a cluster where suppression has not reached everyone in the chain.

That reframes the target. If a third of recent growth runs through 23 identifiable clusters, and if those clusters are held open by unsuppressed virus, then the intervention is not a blanket campaign but a focused effort to find and treat the specific people keeping each chain alive.

What molecular surveillance can and cannot do

The authors' conclusion is that the Swiss epidemic has evolved into fragmented, short transmission chains, with a small number of fast-growing clusters sustaining ongoing transmission, and that molecular surveillance can identify such clusters to enable tailored interventions that complement treatment as prevention [s1]. Achieving zero transmission, they write, will require integrating molecular epidemiology into routine prevention [s1].

The approach has real limits, and they are partly ethical rather than technical. A cluster is a statistical object built from viral sequences, not a list of named contacts, and turning cluster detection into action means deciding how far public health may act on genetic linkage between people — a question that carries obvious risks of stigma for the groups where clusters concentrate.

There is also a coverage caveat built into the data. The analysis rests on sequences from cohort participants, so transmission involving people who are undiagnosed, untested, or outside the cohort is invisible to it by construction. A map drawn from those who are already in care can only ever show part of the terrain, and the chains most likely to be missed are precisely those least connected to services.

The wider point

For a high-income country with strong treatment coverage, the study is a reminder that the last stretch toward elimination is not a smaller version of the epidemic's middle years. It is a different problem — a scatter of short chains punctuated by a few that grow — and it rewards precision over volume. The analysis was funded by the Swiss National Science Foundation [s1].

This article is informational and is not medical advice.