# Geospatial and phylogenetic clustering of acute and recent HIV infections in Lilongwe, Malawi

**Authors:** Griffin J. Bell, Kimberly A. Powers, Oliver Ratmann, Ann M. Dennis, Pearson Mmodzi, Mitch Matoga, Edward Jere, Jane S. Chen, Courtney N. Maierhofer, Sarah E. Rutstein, Kathryn E. Lancaster, Maganizo B. Chagomerana, Naomi Bonongwe, Esther Mathiya, Beatrice Ndalama, David Bonsall, Sharon S. Weir, Mina C. Hosseinipour, Michael Emch, Myron S. Cohen, Irving F. Hoffman, William C. Miller, Sanghyuk S Shin, Sanghyuk S Shin

PMC · DOI: 10.1371/journal.pgph.0005420 · PLOS Global Public Health · 2025-11-05

## TL;DR

This study examines how HIV spreads in Lilongwe, Malawi, by analyzing where and how new infections cluster geographically and genetically.

## Contribution

The study introduces a combined geospatial and phylogenetic approach to identify clusters of acute and recent HIV infections.

## Key findings

- Four geospatial clusters accounted for 30% of acute HIV cases in a small area.
- Fourteen phylogenetic clusters were identified, including male-female and same-sex pairs.
- No phylogenetic linkages were found within geospatial clusters, suggesting separate transmission patterns.

## Abstract

HIV transmission during early HIV infection impedes efforts to end HIV as a public health threat, as diagnosis typically occurs after this period of elevated transmission risk. To guide diagnosis and prevention strategies, we evaluated the geospatial and phylogenetic clustering of acute and recent HIV infection in Lilongwe, Malawi. We identified people with acute (pre-seroconversion) HIV infection (AHI) and a random sample of people with post-acute HIV infection who presented to a sexually transmitted infections (STI) clinic in Lilongwe, Malawi between 2015 and 2019. We evaluated infection recency in people with post-acute HIV using a LAg-Avidity assay. We mapped the household locations of people with AHI and identified geospatial clusters using a flexible scan statistic. We constructed consensus sequences from deep sequencing reads to identify phylogenetic clusters through genetic distance thresholds and maximum likelihood trees. We identified 141 people with AHI, 30 people with recent HIV, and 652 people with chronic (non-recent) HIV. We identified four geospatial clusters that contained the residences of 30% of clinic attendees with AHI, despite comprising just 0.8% of the populated land area and 3.5% of the population. We also identified fourteen distinct two-person phylogenetic clusters. Ten of the fourteen were male-female pairs, nine of which were clinic referral pairs. The remaining four were same-sex pairs who had not referred each other to the clinic and may have been missing network intermediaries. Three of the fourteen phylogenetic pairs consisted of only acute/recent members, and zero phylogenetic linkages were located within geospatial clusters. AHI detection programs anchored in STI clinic populations and their neighborhoods could facilitate identification of early HIV infection, enabling treatment initiation and transmission prevention efforts during this most infectious period. Future studies of intervention packages and deployment approaches can help inform the optimal design and implementation of AHI-focused strategies for reducing HIV incidence.

## Linked entities

- **Diseases:** sexually transmitted infections (MONDO:0021681)

## Full-text entities

- **Diseases:** (pre-seroconversion) (MESH:D006679), STI (MESH:D012749), infectious (MESH:D003141), infection (MESH:D007239), HIV (MESH:D015658)
- **Species:** Human immunodeficiency virus 1 (no rank) [taxon 11676]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12588460/full.md

## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12588460/full.md

## References

54 references — full list in the complete paper: https://tomesphere.com/paper/PMC12588460/full.md

---
Source: https://tomesphere.com/paper/PMC12588460