The effect of interventions on the transmission and spread of HIV in South Africa: a phylodynamic analysis

Reconstructing the phylodynamic history and geographic spread of the CRF01_AE-predominant HIV-1 epidemic in the Philippines from PR/RT sequences sampled from 2008 to 2018

The Philippines has had a rapidly growing human immunodeficiency virus (HIV) epidemic with a shift in the prevalent subtype from B to CRF01_AE. However, the phylodynamic history of CRF01_AE in the Philippines has yet to be reconstructed. We conducted a descriptive retrospective study reconstructing the history of HIV-1 CRF01_AE transmissions in the Philippines through molecular epidemiology. Partial polymerase sequences (n = 1144) collected between 2008 and 2018 from three island groups were collated from the Research Institute for Tropical Medicine drug resistance genotyping database. Estimation of the time to the most recent common ancestor (tMRCA), effective reproductive number (Re), effective viral population size (Ne), relative migration rates, and geographic spread of CRF01_AE was performed with BEAST. Re and Ne were compared between CRF01_AE and B. Most CRF01_AE sequences formed a single clade with a tMRCA of June 1996 [95 per cent highest posterior density (HPD): December 1991, October 1999]. An increasing CRF01_AE Ne was observed from the tMRCA to 2013. The CRF01_AE Re reached peaks of 2.46 [95 per cent HPD: 1.76, 3.27] in 2007 and 2.52 [95 per cent HPD: 1.83, 3.34] in 2015. A decrease of CRF01_AE Re occurred in the intervening years of 2007 to 2011, reaching as low as 1.43 [95 per cent HPD: 1.06, 1.90] in 2011, followed by a rebound. The CRF01_AE epidemic most likely started in Luzon and then spread to the other island groups of the country. Both CRF01_AE and Subtype B exhibited similar patterns of Re fluctuation over time. These results characterize the subtype-specific phylodynamic history of the largest CRF01_AE cluster in the Philippines, which contextualizes and may inform past, present, and future public health measures toward controlling the HIV epidemic in the Philippines.

Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community

Background: South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. Methods: We separately analysed HIV-1 for gag, pol, and env genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Results: Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with gag were generally smaller than those estimated with pol and env. When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%-92%) for gag, 62% (CI = 40%-78%) for pol, and 77% (CI = 58%-90%) for env in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. Conclusions: We estimated consistent epidemic dynamic trends for gag, pol and env genes using phylodynamic models. There was a high probability that new infections were not attributable to endogenous transmission within Hlabisa, suggesting high inter-connectedness between communities in rural South Africa.

Race, place, and HIV: The legacies of apartheid and racist policy in South Africa

Black South Africans accounted for 6.2 out of 6.4 million people living with HIV in South Africa in 2012, highlighting extreme racial disparities in HIV infection. These racial disparities are the result of structural and historical factors, specifically, the racist policies which were facilitated by segregation before, during, and after Apartheid. First, we describe the theoretical context of how racist policies and segregation are linked to HIV prevalence. Next, using data from a 2012 national survey of South Africans (SABSSM IV) and Statistics South Africa (StatsSA), we describe the race-specific geospatial distribution of HIV in South Africa, provide empirical evidence for the impact of Apartheid on important risk factors for HIV infection, and describe the relationship between these risk factors and HIV within racial groups. Using multilevel logistic regression, we find that segregation increases the odds of HIV infection among Black South Africans, even after adjusting for many covariates which are sometimes blamed, in place of structural factors, for a higher HIV prevalence in Black South Africans. We found that the estimated odds of infection in the most segregated municipality was 1.95 (95% CI: 1.15, 3.32) times the odds of infection in the least segregated municipality for Black South Africans. In addition to segregation, we also find other covariates to be differentially associated with HIV infection depending on race, such as gender, age, and sexual behavior. We also find that the HIV infection odds ratio comparing Black and Coloured (i.e., multiple ethnic groups with mixed ancestries from Africa, Asia, and Europe) South Africans varies over space. These results continue to build evidence for the influence of structural and historical factors on the modern geospatial and demographic distribution of HIV.

Independent epidemic patterns of HIV-1 CRF01_AE lineages driven by mobile population in Shenzhen, an immigrant city of China

Shenzhen, a city with >12 million migrant population, may play a key role in the spread of human immunodeficiency virus (HIV)-1 in China. The transmission dynamics of CRF01_AE, a predominant subtype in Shenzhen, is a good model to characterize the impact of human mobility on HIV-1 epidemic locally and nationally. We used phylodynamic and phylogeographic methods to estimate the viral transmission dynamics and migration trajectory of variable lineages based on 1,423 CRF01_AE sequences in Shenzhen sampled between 2006 and 2015. Eleven lineages of CRF01_AE were detected in Shenzhen. Of those, four main lineages originated during the 1990s. Their basic viral reproduction number (R0) ranged 1.96–3.92. The effective viral reproduction number (Re) of two lineages prevalent among heterosexuals/people who inject drugs had reduced <1 at the end of sampling, and the main sources were the intra-provincial immigrants (72 per cent) for one and local residents of Shenzhen (91 per cent) for another. Within two lineages among men who have sex with men (MSM), Re had been above or close to 1 at the end of sampling, and the immigrants from Jiangxi/Shaanxi and Hubei as sources accounted for 93 per cent and 68 per cent of all viral migration events, respectively. Moreover, no obvious recipients were found throughout the viral migration history for any lineage. Our findings demonstrate that HIV epidemic is declining in Shenzhen, which coincided with the initiation of the interventions during the 2000s. However, the obvious differences of the epidemic patterns between lineages emphasize the importance of further targeting interventions and continued molecular tracing, focusing on high-risk transmission sources among MSM.

Optimizing viral genome subsampling by genetic diversity and temporal distribution (TARDiS) for phylogenetics

SUMMARY

TARDiS is a novel phylogenetic tool for optimal genetic subsampling. It optimizes both genetic diversity and temporal distribution through a genetic algorithm.

AVAILABILITY AND IMPLEMENTATION

TARDiS, along with example datasets and a user manual, is available at https://github.com/smarini/tardis-phylogenetics.

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.

Molecular network-based intervention brings us closer to ending the HIV pandemic

Precise identification of HIV transmission among populations is a key step in public health responses. However, the HIV transmission network is usually difficult to determine. HIV molecular networks can be determined by phylogenetic approach, genetic distance-based approach, and a combination of both approaches. These approaches are increasingly used to identify transmission networks among populations, reconstruct the history of HIV spread, monitor the dynamics of HIV transmission, guide targeted intervention on key subpopulations, and assess the effects of interventions. Simulation and retrospective studies have demonstrated that these molecular network-based interventions are more cost-effective than random or traditional interventions. However, we still need to address several challenges to improve the practice of molecular network-guided targeting interventions to finally end the HIV epidemic. The data remain limited or difficult to obtain, and more automatic real-time tools are required. In addition, molecular and social networks must be combined, and technical parameters and ethnic issues warrant further studies.

Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.