Quantifying and predicting ongoing Human Immunodeficiency Virus Type 1 (HIV-1) transmission dynamics in Switzerland using a distance-based clustering approach. The Journal of Infectious Diseases
Labarile et al. aimed to analyze cluster growth dynamics in the Swiss HIV epidemic in the context of the Swiss HIV Cohort Study (SHCS) as well as the predictive capabilities that can be achieved in this framework.
To reach this goal the authors adapted a distance-based clustering mechanism implemented in HIV-Transmission Cluster Engine (HIV-TRACE) using evolutionary distances between viral sequences from the SHCS and combined it with statistical learning approaches.
They found that only a minority of clusters and patients acquired links to new infections between 2007 and 2020. While the growth of clusters and the probability of individual patients acquiring new links in the transmission network was associated with epidemiological, behavioral, and virological predictors, the strength of these associations decreased substantially when adjusting for network characteristics. Thus, these network characteristics were able to capture major heterogeneities beyond classical epidemiological parameters. When modeling the probability of a newly diagnosed patient being linked with future infections, they found that the best predictive performance (median area under the curve receiver operating characteristic AUCROC=0.77) was achieved by models including characteristics of the network as predictors and that models excluding them performed substantially worse (median AUCROC=0.54).
In conclusion, the study shows that in the timespan from 2007 to 2020 only a minority of the HIV clusters in Switzerland were growing. Similarly, only a small fraction of patients enrolled up to the year 2007 have formed any new links, which would be an indication of onward transmission of HIV. The study presents new insights into the long-term dynamics of HIV cluster growth including the value of using cluster-based variables in predicting future growth both on the level of clusters and individual patients in the Swiss HIV epidemic.