Simon Cauchemez joined Institut Pasteur in 2013 to head Mathematical Modelling of Infectious Diseases Unit. The main research objective of his unit is to develop state-of-the-art statistical and mathematical methods to address these challenges, with the aim to increase the understanding of how pathogens spread in human populations as well as the impact of interventions, to support policy making and optimize control strategies. His approach is highly multidisciplinary, looking at infectious diseases through multiple perspectives (statistics, modelling, epidemiology, surveillance, Public Health, policy making, microbiology), multiple scales and multiple data streams. Before joining Institut Pasteur, Simon Cauchemez was working in the Department of Infectious Disease Epidemiology at Imperial College London.
INCEPTION – Institut Convergence for the study of Emergence of Pathology Through Individuals and Populations
IINCEPTION Goal The Inception’s goal is to develop a core structure to mobilize data resources, numerical sciences, and fundamental experimental biology in a range of health issues (Official website here : https://www.inception-program.fr/en). Inception program […]
300 to 400 million cases of dengue fever occur each year worldwide. Spreading rapidly, more than 40% of the world’s population is now at risk of contracting dengue This transversal program brings together talents […]
LabEx IBEID – Integrative Biology of Emerging Infectious Diseases
Presentation The aim of the Integrative Biology of Emerging Infectious Diseases (IBEID) project, coordinated by Professors Philippe Sansonetti and Pascale Cossart, is to develop a structure to anticipate and tackle emerging infectious diseases (EIDs). […]
Pasteur International Center for Research on Emerging Infectious Diseases
We established an Emerging Infectious Disease Research Center in Southeast Asia and West/Central Africa with an inter-continental one-health approach designed to improve the capacity to respond rapidly and effectively to outbreaks. We built on […]
Assessing the threat posed by zoonotic viruses like MERS-CoV, Nipah, Yellow Fever or plague
Zoonotic viruses are viruses that have an animal reservoir but may also infect humans. The 2009 A(H1N1)pdm09 influenza pandemic, the SARS epidemic in 2003, the recent emergence of a novel coronavirus in the Middle […]
Analysis and modelling to support decision making during epidemics
The Mathematical Modelling of Infectious Diseases Unit works closely with public health agencies in France and abroad to provide modelling support during epidemics so that our assessments can contribute to evidence-based decision making and […]
Statistical and mathematical methods to characterize disease transmission from incomplete epidemiological data
To design effective ways to mitigate the spread of a pathogen in a population, it is important to first have a good understanding of the transmission characteristics of the pathogen as well as the […]
Developing a One Health perspective: the case of Nipah virus
Nipah virus (NiV) is a bat-borne paramyxovirus found throughout South and South East Asia. With a case fatality ratio of >70% and no available treatment or vaccines, NiV has been identified by the […]
Optimizing the interpretation of serological data
When individuals get infected by a pathogens, they will develop antibodies against that pathogen that will continue to circulate in their blood. By using assays that can detect these antibodies, we can develop an […]
Use of sequences to identify drivers of pathogen spread
In order to understand the spread of infectious diseases, we are often interested in the transmission relationship between pairs of cases. The use of pathogen sequences has revolutionized our ability to characterize the relationship […]
Improved understanding of patterns of pathogen infection risk
There have been a number of recent efforts to build global maps of infection risk for different pathogens. These maps typically use the results of regressions in well-characterized settings to quantify the association between […]
2023Impact and mitigation of sampling bias to determine viral spread: Evaluating discrete phylogeography through CTMC modeling and structured coalescent model approximations., Virus Evol 2023 ; 9(1): vead010.
2023Modelling the end of a Zero-COVID strategy using nirmatrelvir/ritonavir, vaccination and NPIs in Wallis and Futuna., Lancet Reg Health West Pac 2023 Jan; 30(): 100634.
2022Transmission dynamics of Q fever in French Guiana: A population-based cross-sectional study., Lancet Reg Health Am 2022 Dec; 16(): 100385.
2022Analytical framework to evaluate and optimize the use of imperfect diagnostics to inform outbreak response: Application to the 2017 plague epidemic in Madagascar., PLoS Biol 2022 Aug; 20(8): e3001736.
2022Selection for infectivity profiles in slow and fast epidemics, and the rise of SARS-CoV-2 variants., Elife 2022 May; 11(): .
2022An ensemble model based on early predictors to forecast COVID-19 health care demand in France., Proc Natl Acad Sci U S A 2022 May; 119(18): e2103302119.
2022Global spatial dynamics and vaccine-induced fitness changes of Bordetella pertussis., Sci Transl Med 2022 Apr; 14(642): eabn3253.
2022Reconstructing antibody dynamics to estimate the risk of influenza virus infection., Nat Commun 2022 Mar; 13(1): 1557.
2022Impact of SARS-CoV-2 Delta variant on incubation, transmission settings and vaccine effectiveness: Results from a nationwide case-control study in France., Lancet Reg Health Eur 2022 Feb; 13(): 100278.
2022Early chains of transmission of COVID-19 in France, January to March 2020., Euro Surveill 2022 02; 27(6): .
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