I am a post-doctoral researcher in infectious disease epidemiology and modelling at Institut Pasteur and Centre de recherche en épidémiologie et santé des populations (CESP) at INSERM. I work closely with Lulla Opatowski, Didier Guillemot and Laura Temime (CNAM).
My focus is on the epidemiology of virus transmission and how this is affected by the host behaviour and interactions between viruses.
Seasonality and interactions between viral respiratory infections
Viral respiratory infections present a substantial and seasonal risk of hospitalisation. The seasonal patterns of Influenza and RSV are well described, but many other viruses contribute to the burden of disease. Within-host interactions between these viruses may also play a role in the shape of epidemics and the clinical consequences.
I am currently working in collaboration with researchers at FISABIO in Valencia, who have collected more than 10 years of samples patients hospitalised with respiratory illness. These have been analysed using a multiplex assay to test for presence of 9 viruses (Influenza, RSV, Rhino/enteroviruses, Adenovirus, Bocavirus, Metapneumovirus, Parainfluenza virus, SARS-CoV-2 and non-SARS Coronaviruses). I use waveform analysis to describe seasonal patterns, and two-virus compartmental models to estimate the extent of interaction between pairs of viruses.
Contact structure and epidemic risk in healthcare
A detailed understanding of the risk of healthcare outbreaks requires knowledge of contact patterns between different hospital users (staff, patients and visitors).
In the nodscov2 study (pre-print here, in press in Scientific Reports), data on close proximity contact between hospital users was collected using wearable sensors. I analysed this data to estimate overall contact patterns, and converted these into predictions of epidemic risk. We explored how this risk could be reduced by identifying staff and patients with the highest contact hours and targeting them for preventive interventions.
In a follow-up to this work, I used this contact data to explore fundamental questions about whether contact rates increase or stay relatively constant under increasing population density.
Estimating the basic reproduction number (R0) of SARS-CoV-2 in healthcare
During the first waves of the COVID-19 pandemic, I worked in close collaboration with clinical staff at AP-HP to estimate the epidemic potential of SARS-CoV-2 in a long-term care facility. Using a stochastic model to account for the small population size, and a specific observation process to account for irregular sampling due to shortages of tests, we estimated the R0 across the whole facility and in each ward.
We also estimated the size of the reduction in R0 (~85%) thought to result from the introduction of universal masking and other contact precautions.
I have also contributed to other modelling (pandemic-related sick-leave, COVID-19 and antibiotic resistance) and review studies on disease transmission in healthcare.
Previous work
- Modelling, field work and assessment of surveillance tools at the Clinton Health Access Initiative and the Swiss Tropical and Public Health Institute as part of malaria elimination efforts in Southern Africa.
- Field epidemiology with Médecins Sans Frontières in South Kivu, DRC: assessing surveillance tools and providing epidemiological support for a vaccination campaign.
- Evaluating the efficacy of vaccines against poliovirus using clinical and environmental surveillance data, at Imperial College, working with the World Health Organisation, the Global Polio Eradication Initiative and national governments of Nigeria and Pakistan.
- Measuring the fitness cost of HIV-1 drug resistance mutations using phylodynamic analysis at ETH Zürich.
- Exploring the evolution of virulence in HIV-1 using modelling and phylodynamic analysis at Imperial College and ETH Zürich.