Accidental Father-to-Son HIV-1 Transmission During the Seroconversion Period

Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Inferring viral transmission time from phylogenies for known transmission pairs

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously-described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time-calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Human immunodeficiency virus transmission from a 24-year-old woman to her 78-year-old grandmother: a case report

Introduction

Since its debut recognition in 1981, human immunodeficiency virus/acquired immunodeficiency syndrome has affected over 77 million people and has resulted in premature cessation of 35.4 million lives worldwide. Commonly, human immunodeficiency virus is transmitted by sexual contact across mucosal surfaces, by sharing of injecting equipment, through contaminated blood transfusions, and by maternal–infant exposure. Nevertheless, accidental transmission incidences involving family members are rare but possible.

Case presentation

A 78-year-old woman of African descent from Mtwara Region south of Tanzania was referred to us for further evaluation and treatment. She is 30 years postmenopausal and has a 35-year history of hypertension. Her last attendance to our institute was 11 months prior the index visit and she tested negative for human immunodeficiency virus. She came with complaints of weight loss, recurrent fevers, and cough. Her hematological tests revealed leukopenia with lymphocytosis, together with a normocytic normochromic anemia. Enzyme-linked immunosorbent assay for human immunodeficiency virus was positive, and she had a CD4 count of 177 cells/µL. We went back to history taking to identify the potential source of infection. We were informed that for the past 6 months, the 78-year-old lady has been living with her unwell 24-year-old granddaughter who has been divorced. The granddaughter had a history of recurrent fevers, significant weight loss, and a suppurative skin condition. As a way to show love and care, the old lady was puncturing the suppurative lesions with bare hands; then she would suck them to clear away the discharge. We requested to see the young lady, and she tested positive for human immunodeficiency virus. Both were started on tenofovir/lamivudine/dolutegravir combination plus cotrimoxazole 960 mg. The family was in total disarray following these findings. The patient was discharged through infectious diseases department and died of Pneumocystis jirovecii pneumonia 12 weeks later.

Conclusions

Certain sociocultural norms that are believed to express love, care, and togetherness in developing rural communities, particularly Sub-Saharan Africa, have a potential of spreading human immunodeficiency virus, thus warranting prompt transformation.

Phylogenetic evidence of HIV-1 transmission linkage between two men who have sex with men

Background

In China, an HIV-infected man (complainant; P2) alleged that another man (defendant; P1) had unlawfully infected him with HIV through unprotected homosexual contact in 2018.

Methods

We employed epidemiological, serological and phylogenetic analyses to investigate the transmission linkage between two men who have sex with men (MSM). Partial segments of three HIV-1 gene regions (gag, pol, and env) were amplified and sequenced by cloning. Maximum-likelihood (ML) and Bayesian methods were used to determine the direction and estimate the timing of transmission. Local control sequences and database control sequences were also used in the phylogenetic analysis.

Results

It indicated that P2 underwent HIV seroconversion after P1 was diagnosed as HIV positive. The time to the most recent common ancestor (tMRCA) estimates consistently showed that P1 most likely became HIV-1 infected at an earlier date than P2. P1 and P2 were infected with the same HIV-1 CRF01_AE subtype according to segments of all three gene regions (gag, pol, and env). All three genetic regions of P1 have been subject to more potential selective forces than those of P2, indicating a longer evolutionary history. Bayesian and ML trees showed similar paraphyletic-monophyletic topologies of gag and env, with the virus from P1 located at the root, which supported a P1-to-P2 transmission direction.

Conclusions

Phylogenetic investigations can elucidate HIV transmission linkage and might empower its use in the opposition of the intentional transmission of HIV-1 as a forensic tool.