Phylogenetics and Networks of Generalised HIV epidemics in Africa
We develop statistical methods to analyse viral deep sequence data. We contribute to the development of phyloscanner. We estimate sources and sinks of HIV transmission. We collaborate with colleagues at the Big Data Institute in Oxford, John's Hopkins University, the Rakai Health Sciences Institute, and many others.
The phyloscanner program changes the capabilities of molecular epidemiological studies because the direction of transmission can be estimated from the structure in viral deep sequence phylogenies. Chris's paper explains our concepts and pipelines (Wymant et al., 2018). We have applied phyloscanner to large-scale data sets to reconstruct likely transmission networks (Ratmann et al., 2019), geographic source and sink populations of transmission flow (Ratmann et al., 2020), and developed methods for estimating transmission flows at a resolution of 1-year age bands (Xi et al., 2021).
I am on PANGEA-HIV's executive committee and we are grateful for the longstanding support of the Bill & Melinda Gates Foundation.
Global reference group on children affected by COVID-19
We develop methods to quantify the number of children who lost their parents or caregivers to COVID-19. We contribute to global estimates and in-country analyses. We collaborate with the researchers at the CDC, the University of Oxford, UCL, UNAIDS, the WHO, the World Bank, and NGO's.
Imperial College London COVID-19 Response Team
We develop flexible, semi-parametric mathematical models of disease spread that can be fitted in a fully Bayesian framework. We estimated the age groups that drive the spread of COVID-19 in resurgent epidemics across the US. We helped describe the emergence of variants of concern in the UK and Brazil. We contributed to risk benefit analyses of vaccination in adolescents. We identified the role of healthcare pressure on shocks in COVID-19 fatality rates in hospitals. We collaborate with mobile phone data intelligence companies across the US, and many other partners worldwide.
Some of these studies have appeared in leading journals, including a Science paper led by my PhD student Melodie (Flaxman et al, Nature 2020, Monod et al, Science 2021, Volz et al, Nature 2021; Faria et al, Science 2021).
Our semi-parametric Bayesian models are fitted with Stan, exploiting parallelisation with the reduce_sum functionality, and are available here.
Long-term impact of universal treatment and dolutegravir on population HIV virologic and incidence outcomes in Africa
We develop bespoke methods to characterise longitudinal trajectories of HIV viral load in African patients since diagnosis, and the factors driving them. We collaborate with partners at the Rakai Health Sciences Program and John's Hopkins University.
Kate is the PI on the LONGVIEW study, and I am the lead statistician. This study is funded by the NIH.
HIV transmission elimination initiative Amsterdam
We develop methods to reconstruct city-level spread of HIV. We collaborate with colleagues at Stichting HIV monitoring, the Amsterdam public health institute, Amsterdam hospitals, and NGOs.
We are especially grateful for the AIDSFonds to support our combined epidemiological and phylogenetic work on characterising city-level spread of HIV in Amsterdam.
Characterising the spread of HIV-1 in Seattle, USA, in near real time
Related to our work in Amsterdam, we are also involved characterising the spread of HIV in Seattle, USA. The particular focus is on better understanding the sources of new infections among adolescents and migrants, and how to stop them. Drawing parallels to the epidemic context in Amsterdam is a particularly exciting part of this work.