My current research focuses on developing statistical methods to estimate relevant parameters within complex ecological setting by integrating various sources of information in order to better understand the dynamics of diseases’ transmission and mitigate their public health risk.
The focus of my current work concentrates on 3 themes:
- Vector-borne and zoonotic diseases, with a strong focus on rabies and Chagas disease.
- Emerging diseases, with a strong focus on MERS-CoV, Ebola, Zika and antibiotic resistance.
- Rapid response to outbreaks and real-time analysis, with a strong focus on developing tools and capacity ahead of future outbreaks.
In each of those 3 themes, my interests broadly sit at the interface between ecology and epidemiology where the potential for endemic and (re-)emerging zoonotic diseases lies.
Broadly speaking, I would define myself as a quantitative biologist and epidemiologist, as I seek to resolve concrete ecological and epidemiological problems using mathematical formalisation. Importantly, I see myself as belonging to the data-driven branch of modelling, and I strongly believe that models not only need to be fed with data, but also that in turn the analysis of data is greatly enhanced by modelling.
et al., 2023, Gaps in mobility data and implications for modelling epidemic spread: a scoping review and simulation study, Epidemics: the Journal of Infectious Disease Dynamics, Vol:42, ISSN:1755-4365, Pages:1-11
Nash RK, Cori A, Nouvellet P, 2022, Estimating the epidemic reproduction number from temporally aggregated incidence data: a statistical modelling approach and software tool
et al., 2022, Understanding the incidence and timing of rabies cases in domestic animals and wildlife in south-east Tanzania in the presence of widespread domestic dog vaccination campaigns, Veterinary Research, Vol:53, ISSN:0928-4249
et al., 2022, Estimating Zika virus attack rates and risk of Zika virus-associated neurological complications in Colombian capital cities with a Bayesian model, Royal Society Open Science, Vol:9, ISSN:2054-5703
et al., 2022, National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021., Commun Med (lond), Vol:2