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., 2017, Modelling historical changes in the force-of-infection of Chagas disease to inform control and elimination programmes: application in Colombia, Bmj Global Health, Vol:2, Pages:e000345-e000345
et al., 2017, Key data for outbreak evaluation: building on the Ebola experience, Philosophical Transactions of the Royal Society B-biological Sciences, Vol:372, ISSN:0962-8436
et al., 2017, Heterogeneities in the case fatality ratio in the West African Ebola outbreak 2013-2016, Philosophical Transactions of the Royal Society B-biological Sciences, Vol:372, ISSN:0962-8436
et al., 2017, A simple approach to measure transmissibility and forecast incidence., Epidemics
et al., 2017, How universal is coverage and access to diagnosis and treatment for Chagas disease in Colombia? A health systems analysis, Social Science & Medicine, Vol:175, ISSN:0277-9536, Pages:187-198