AI Article Synopsis
- Public health officials need effective strategies to allocate limited resources to transmission clusters, and this study tests a new method based on lineage-level diversification rates.
- The research used data from 9,822 HIV sequences to compare the effectiveness of diversification rate measures against traditional growth-based measures for prioritizing transmission clusters.
- Results show that diversification rate approaches not only match but often exceed the predictive power of growth-based methods, especially for long-term growth and identifying high-transmission potential groups.
Article Abstract
Background And Objectives: Public health officials faced with a large number of transmission clusters require a rapid, scalable and unbiased way to prioritize distribution of limited resources to maximize benefits. We hypothesize that transmission cluster prioritization based on phylogenetically derived lineage-level diversification rates will perform as well as or better than commonly used growth-based prioritization measures, without need for historical data or subjective interpretation.
Methodology: 9822 HIV pol sequences collected during routine drug resistance genotyping were used alongside simulated sequence data to infer sets of phylogenetic transmission clusters via patristic distance threshold. Prioritized clusters inferred from empirical data were compared to those prioritized by the current public health protocols. Prioritization of simulated clusters was evaluated based on correlation of a given prioritization measure with future cluster growth, as well as the number of direct downstream transmissions from cluster members.
Results: Empirical data suggest diversification rate-based measures perform comparably to growth-based measures in recreating public heath prioritization choices. However, unbiased simulated data reveals phylogenetic diversification rate-based measures perform better in predicting future cluster growth relative to growth-based measures, particularly long-term growth. Diversification rate-based measures also display advantages over growth-based measures in highlighting groups with greater future transmission events compared to random groups of the same size. Furthermore, diversification rate measures were notably more robust to effects of decreased sampling proportion.
Conclusions And Implications: Our findings indicate diversification rate-based measures frequently outperform growth-based measures in predicting future cluster growth and offer several additional advantages beneficial to optimizing the public health prioritization process.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311310 | PMC |
| http://dx.doi.org/10.1093/emph/eoac026 | DOI Listing |
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- Public health officials need effective strategies to allocate limited resources to transmission clusters, and this study tests a new method based on lineage-level diversification rates.
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- Results show that diversification rate approaches not only match but often exceed the predictive power of growth-based methods, especially for long-term growth and identifying high-transmission potential groups.
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