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.
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et al., 2020, State-level tracking of COVID-19 in the United States, Nature Communications, ISSN:2041-1723
et al., 2020, Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study, Lancet Infectious Diseases, Vol:20, ISSN:1473-3099, Pages:1381-1389
et al., 2020, SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China, Journal of Travel Medicine, Vol:27, ISSN:1195-1982, Pages:1-3
et al., 2020, A database for the epidemic trends and control measures during the first wave of COVID-19 in mainland China, International Journal of Infectious Diseases, ISSN:1201-9712