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., 2019, Case fatality ratio estimates for the 2013 – 2016 West African Ebola epidemic: application of Boosted Regression Trees for imputation, Clinical Infectious Diseases, ISSN:1058-4838
et al., 2019, Outbreak analytics: a developing data science for informing the response to emerging pathogens, Philosophical Transactions B: Biological Sciences, Vol:374, ISSN:0962-8436
Waxman D, Nouvellet P, 2019, Sub- or supercritical transmissibilities in a finite disease outbreak: Symmetry in outbreak properties of a disease conditioned on extinction, Journal of Theoretical Biology, Vol:467, ISSN:0022-5193, Pages:80-86
et al., 2019, Genetic and spatial characterization of the red fox (Vulpes vulpes) population in the area stretching between the Eastern and Dinaric Alps and its relationship with rabies and canine distemper dynamics, Plos One, Vol:14, ISSN:1932-6203
et al., 2019, Big brother is watching - using digital disease surveillance tools for near real-time forecasting, ELSEVIER SCI LTD, Pages:27-27, ISSN:1201-9712