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. 2025 Mar 7;17(3):384.
doi: 10.3390/v17030384.

A Spatiotemporal Analysis of a High-Resolution Molecular Network Reveals Shifts of HIV-1 Transmission Hotspots in Guangzhou, China

Huanchang Yan  1   2 , Yifan Lu  1 , Shunming Li  3 , Hao Wu  3 , Jingyang Hu  4 , Yefei Luo  3 , Qingmei Li  3 , Lingxuan Lai  1 , Weiping Huang  5 , Jing Gu  2 , Lijun Ma  1 , Yuantao Hao  6 , Zhigang Han  3   7 , Xin-Lin Chen  8 , Yu Liu  1   9
Affiliations

A Spatiotemporal Analysis of a High-Resolution Molecular Network Reveals Shifts of HIV-1 Transmission Hotspots in Guangzhou, China

Huanchang Yan et al. Viruses. .

Abstract

Background: High-resolution and longitudinal HIV molecular surveillance can inform the evolving hotspots to tailor regionally focused control strategies.

Methods: HIV-1 pol sequences of three predominant genotypes (CRF01_AE, CRF07_BC, and CRF55_01B) were collected for molecular network reconstruction from people living with HIV (PLWH) in Guangzhou (2018-2020). They were categorized by geographical residences into central, suburban, and outer suburban areas. Clustering rates, assortativity coefficients, and intensity matrices were employed to assess transmission dynamics, geographic mixing patterns, and intra- and inter-area transmission, respectively.

Results: Of the 2469 PLWH, 55.5% resided in the central area. Clustering rates showed no significant differences across areas (44.5%, 40.6% vs. 45.7%; p = 0.184). However, the transmission hotspots for CRF01_AE and CRF55_01B shifted to the outer suburban area. PLWH tended to form links within their local area (assortativity coefficient = 0.227, p < 0.001), particularly for CRF01_AE (0.512, p < 0.001; intra-area intensity = 69.2%). The central area exhibited the highest but decreasing intra-area transmission (74.5% to 30.2%), while intra- and inter-area transmission involving the outer suburban area increased (23.1% to 38.2%).

Conclusions: Despite most PLWH residing in the central area, the outer suburban area emerged as the hotspot, requiring interventions towards both intra- and inter-area transmission.

Keywords: human immunodeficiency virus; molecular transmission network; spatiotemporal analysis.

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Conflict of interest statement

No conflicts of interest were declared by the authors.

Figures

Figure 1
Figure 1
Characteristics of people living with HIV (PLWH) diagnosed with the three main genotypes in Guangzhou, China (2018–2020). (A) Distribution of PLWH across three areas: central, suburban, and outer suburban. (B) Demographic and social characteristics of PLWH in each area.
Figure 2
Figure 2
Molecular networks of CRF01_AE, CRF07_BC, and CRF55_01B in Guangzhou, China. Molecular networks were constructed using a pairwise genetic distance threshold of 0.012 substitutions per site. Rows represent the genotypes (CRF01_AE, CRF07_BC, and CRF55_01B) and columns display data for each year (2018, 2019, and 2020). Colors represent different areas of Guangzhou, while shapes indicate infection routes. HET, heterosexual transmission; IDU, injecting drug users; MSM, men who have sex with men.
Figure 3
Figure 3
Spatiotemporal distribution of people living with HIV (A) and clustering rates (B) in Guangzhou from 2018 to 2020. Maps of PLWH are colored by the proportions of PLWH in a given year, while those of clustering rates are colored by absolute values. Higher values are represented by red hues, whereas lower values are represented in green.
Figure 4
Figure 4
Spatiotemporal distribution of HIV-1 transmission intensities across different areas of Guangzhou from 2018 to 2020. Colors indicate the proportions of transmission intensity in a given year, with red hues representing higher proportions and green hues representing lower proportions. The color of each grid cell at the intersection of two areas indicates the number of links between the people living with HIV in two areas.
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