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external supervisor

Andrew Tatem, University of Southampton


The HIV pandemic remains a major global public health problem, with 39 million people living with HIV in 2022. Global HIV genetic diversity forms a major challenge to the development of an HIV vaccine as well as diagnostic, drug resistance, and viral load assays, which are essential for antiretroviral therapy programmes. HIV diversity also impacts HIV transmission and pathogenicity. 

We previously collected data on nearly 400,000 subtyped HIV samples from 116 countries for the period 1990-2015. This showed that the global distribution of HIV-1 subtypes and recombinants is extremely complex and dynamic. sub-Saharan Africa accounts for two-thirds of all people living with HIV worldwide and has the greatest genetic diversity of HIV. The number and proportion of HIV recombinants is increasing, and country-level HIV diversity is increasing globally. Global HIV-1 genetic diversity surveillance therefore remains crucial in tackling the pandemic. 

Key references:

Hemelaar et al, Lancet Infectious Diseases,19(2):143-155(2019).

Hemelaar et al, Lancet HIV,7(11):e772-e781(2020).

Hemelaar et al, J Virology,95(2):e01580-20(2021).

Elangovan et al, Hemelaar, Front Microbiol, 12:690647(2021).

Nkazi et al, et al, Hemelaar, Front Public Health, 11:1153638 (2023)


Multiple factors likely contribute to the diversification of the HIV pandemic, including transportation networks, migration, founder effects, urbanisation, transmission networks, and population growth, but their relative contributions remain unclear. The project aims to apply a novel approach to conduct temporal phylogeographic analyses at a global scale, using a database with more than one million subtyped samples collected during 1990-2030.

A library of global multi-temporal geospatial datasets representing candidate factors driving global HIV diversification will be constructed. This will include population distributions, infrastructure, migration patterns over land, sea and air, land use and cover changes, global connectivity measures, and coverage of HIV treatment and prevention measures. A geostatistical modelling framework will be designed to examine the contributions of the different candidate factors in explaining the patterns seen within the global HIV diversity data, and how these vary sub-nationally and over time. These analyses on the contribution of populations, infrastructure, human migration and disparities in HIV treatment and prevention to the global spread of HIV variants aim to inform interventions to reduce the spread of HIV variants and help forecast future HIV subtype distributions.


It is anticipated that the work will be conducted in Oxford and all necessary facilities, equipment and training, including database, analytic and statistical training, will be provided in Oxford. Some training will be provided in Southampton.


A student with a background in medicine, infectious diseases, statistics or global/public health would be best suited to this project. The ideal candidate will have a Master's degree in a relevant area (e.g. statistics/epidemiology/public health), with experience in geospatial modelling. The project has a broad scope and candidates are encouraged to contact Dr Joris Hemelaar to work out a specific project proposal.