arXiv subjects

Alexandra Blenkinsop

Publications and source records attributed to Alexandra Blenkinsop.

5 recordsLinked to original sources

arXiv2024

Bayesian mixture models for phylogenetic source attribution from consensus sequences and time since infection estimates

In stopping the spread of infectious diseases, pathogen genomic data can be used to reconstruct transmission events and characterize population-level sources of infection. Most approaches for identifying transmission pairs do not account for the time passing since divergence of pathogen variants in individuals, which is problematic in viruses with high within-host evolutionary rates. This prompted us to consider possible transmission pairs in terms of phylogenetic data and additional estimates of time since infection derived from clinical biomarkers. We develop Bayesian mixture models with an evolutionary clock as signal component and additional mixed effects or covariate random functions describing the mixing weights to classify potential pairs into likely and unlikely transmission pairs. We demonstrate that although sources cannot be identified at the individual level with certainty, even with the additional data on time elapsed, inferences into the population-level sources of transmission are possible, and more accurate than using only phylogenetic data without time since infection estimates. We apply the approach to estimate age-specific sources of HIV infection in Amsterdam MSM transmission networks between 2010-2021. This study demonstrates that infection time estimates provide informative data to characterize transmission sources, and shows how phylogenetic source attribution can then be done with multi-dimensional mixture models.

q-bio.PE↗

arXiv2024

Sources of HIV infections among MSM with a migration background: a viral phylogenetic case study in Amsterdam, the Netherlands

Background: Men and women with a migration background comprise an increasing proportion of incident HIV cases across Western Europe. Several studies indicate a substantial proportion acquire HIV post-migration. Methods: We used partial HIV consensus sequences with linked demographic and clinical data from the opt-out ATHENA cohort of people with HIV in the Netherlands to quantify population-level sources of transmission to Dutch-born and foreign-born Amsterdam men who have sex with men (MSM) between 2010-2021. We identified phylogenetically and epidemiologically possible transmission pairs in local transmission chains and interpreted these in the context of estimated infection dates, quantifying transmission dynamics between sub-populations by world region of birth. Results: We estimate the majority of Amsterdam MSM who acquired their infection locally had a Dutch-born Amsterdam MSM source (56% [53-58%]). Dutch-born MSM were the predominant source population of infections among almost all foreign-born Amsterdam MSM sub-populations. Stratifying by two-year intervals indicated shifts in transmission dynamics, with a majority of infections originating from foreign-born MSM since 2018, although uncertainty ranges remained wide. Conclusions: In the context of declining HIV incidence among Amsterdam MSM, our data suggest whilst native-born MSM have predominantly driven transmissions in 2010-2021, the contribution from foreign-born MSM living in Amsterdam is increasing.

q-bio.PE↗

arXiv2022

Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam

Amsterdam and other UNAIDS Fast-Track cities aim for zero new HIV infections. Utilising molecular and clinical data of the ATHENA observational HIV cohort, our primary aims are to estimate the proportion of undiagnosed HIV infections and the proportion of locally acquired infections in Amsterdam in 2014-2018, both in MSM and heterosexuals and Dutch-born and foreign-born individuals. We located diagnosed HIV infections in Amsterdam using postcode data at time of registration to the cohort, and estimated their date of infection using clinical HIV data. We then inferred the proportion undiagnosed from the estimated times to diagnosis. To determine sources of Amsterdam infections, we used HIV sequences of people living with HIV (PLHIV) within a background of other Dutch and international sequences to phylogenetically reconstruct transmission chains. Frequent late diagnoses indicate that more recent phylogenetically observed chains are increasingly incomplete, and we use a Bayesian model to estimate the actual growth of Amsterdam transmission chains, and the proportion of locally acquired infections. We estimate that 20% [95% CrI 18-22%] of infections acquired among MSM between 2014-2018 were undiagnosed by the start of 2019, and 44% [37-50%] among heterosexuals, with variation by place of birth. The estimated proportion of MSM infections in 2014-2018 that were locally acquired was 68% [61-74%], with no substantial differences by region of birth. In heterosexuals, this was 57% [41-71%] overall, with heterogeneity by place of birth. The data indicate substantial potential to further curb local transmission, in both MSM and heterosexual Amsterdam residents. In 2014-2018 the largest proportion of local transmissions in Amsterdam are estimated to have occurred in foreign-born MSM, who would likely benefit most from intensified interventions.

q-bio.PE↗

arXiv2021

COVID-19-Associated Orphanhood and Caregiver Death in the United States

Background: Most COVID-19 deaths occur among adults, not children, and attention has focused on mitigating COVID-19 burden among adults. However, a tragic consequence of adult deaths is that high numbers of children might lose their parents and caregivers to COVID-19-associated deaths. Methods: We quantified COVID-19-associated caregiver loss and orphanhood in the US and for each state using fertility and excess and COVID-19 mortality data. We assessed burden and rates of COVID-19-associated orphanhood and deaths of custodial and co-residing grandparents, overall and by race/ethnicity. We further examined variations in COVID-19-associated orphanhood by race/ethnicity for each state. Results: We found that from April 1, 2020 through June 30, 2021, over 140,000 children in the US experienced the death of a parent or grandparent caregiver. The risk of such loss was 1.1 to 4.5 times higher among children of racial and ethnic minorities, compared to Non-Hispanic White children. The highest burden of COVID-19-associated death of parents and caregivers occurred in Southern border states for Hispanic children, Southeastern states for Black children, and in states with tribal areas for American Indian/Alaska Native populations. Conclusions: We found substantial disparities in distributions of COVID-19-associated death of parents and caregivers across racial and ethnic groups. Children losing caregivers to COVID-19 need care and safe, stable, and nurturing families with economic support, quality childcare and evidence-based parenting support programs. There is an urgent need to mount an evidence-based comprehensive response focused on those children at greatest risk, in the states most affected.

stat.AP↗

arXiv2021

Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out

The COVID-19 pandemic has caused severe public health consequences in the United States. In this study, we use a hierarchical Bayesian model to estimate the age-specific COVID-19 attributable deaths over time in the United States. The model is specified by a novel non-parametric spatial approach, a low-rank Gaussian Process (GP) projected by regularised B-splines. We show that this projection defines a new GP with attractive smoothness and computational efficiency properties, derive its kernel function, and discuss the penalty terms induced by the projected GP. Simulation analyses and benchmark results show that the spatial approach performs better than standard B-splines and Bayesian P-splines and equivalently well as a standard GP, for considerably lower runtimes. The B-splines projected GP priors that we develop are likely an appealing addition to the arsenal of Bayesian regularising priors. We apply the model to weekly, age-stratified COVID-19 attributable deaths reported by the US Centers for Disease Control, which are subject to censoring and reporting biases. Using the B-splines projected GP, we can estimate longitudinal trends in COVID-19 associated deaths across the US by 1-year age bands. These estimates are instrumental to calculate age-specific mortality rates, describe variation in age-specific deaths across the US, and for fitting epidemic models. Here, we couple the model with age-specific vaccination rates to show that lower vaccination rates in younger adults aged 18-64 are associated with significantly stronger resurgences in COVID-19 deaths, especially in Florida and Texas. These results underscore the critical importance of medically able individuals of all ages to be vaccinated against COVID-19 in order to limit fatal outcomes.

stat.AP↗