Jasmina Panovska-Griffiths

I lead the Mathematical Modelling for Public Health Policy Support group, spread across the Pandemic Sciences Institute at Oxford and the UK Health Security Agency (UKHSA). It comprises modellers and data-scientists at UKHSA and DPhil students at University of Oxford. My group utilises mathematical and statistical modelling to respond to current and emerging questions in infectious disease epidemiology, pandemic preparedness and public health.

My group develops and deploys advanced modelling frameworks, such as agent-based models and machine-learning algorithms, to support pandemic preparedness and real‑time operational response during infectious disease outbreaks. We also develop technical methods to improve the efficiency of calibration of ABMs, and complementing modular frameworks to make modelling more user friendly. 

I have proven record and vast experience providing strategic leadership for analysis across a number of major modelling programmes to quantify disease burden across infectious diseases. Since 2017, I have been providing strategic leadership across a number of large-value projects commissioned by the UK Department of Health and Social Care and its advisory bodies JCVI, NERVTAG and SPI-M.

I work closely with UKHSA colleagues to answer emerging public health questions. These include modelling mpox and Avian influenza transmission, identifying people at risk of blood-borne viruses and evaluating different immunisation strategies to reduce pneumococcal disease burden and explore different HPV screening strategies. Recently, under my leadership, my team evaluated different combination of pandemic-preparedness vaccines to support the UK pandemic preparedness planning. Our modelling work gave analytical insights into strategic policy advice. Additionally, we are currently evaluating different pneumococcal immunisation strategies for the elderly, and our recently published work informed the change of the pneumococcal vaccine from 2026. 

Over the COVID-19 pandemic, I led the ensemble modelling that was responsible for the generation of the short-term reproduction number R and growth rate r nowcasts and the medium-term projections (MTPs) of the COVID-19 trajectories, as a collaboration between the Scientific Pandemic Influenza Group for Modelling Operational (SPI-M-O) and the UKHSA. Additionally, I modelled the transmission of different SARS-CoV-2 variants using agent-based models (ABMs), advising policy decision bodies in the UK at different decision junctures over the pandemic. Notably, my modelling results on when and how to reopen schools after the national lockdowns, and my roadmap modelling projections in 2021 were used by the SPI-M-O, the Scientific Advisory Group for Emergencies (SAGE), NHS and UKHSA.

Pre COVID-19, my research was focused on developing models to evaluate different intervention strategies for infectious diseases, including seasonal and pandemic influenza, RSV and HIV. Over 2017-2021, my PhD student at UCL developed and applied a mathematical model to evaluate the optimal allocation of RSV vaccines in England. This work directly informed the JCVI advice to include RSV adult vaccination as part of the routine programme from 2024. 

I am also a Fellow of The Institute of Mathematics and its Applications, of The Royal Statistical Society and of The Royal Society for Public Health and I am on the Advisory Body for the Academy for Mathematical Sciences. I take a keen interest in promoting mathematics and statistics, regularly giving talks at schools across the UK.