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  • program_project
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  • whocc
  • project
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  • tool
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  • Associate Professor
  • Clinical Research Assistant
  • Full Professor
  • Graduate Student
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  • PhD Student
  • Physician
  • Post-doc
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
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  • Honorary President of the Departement
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Scientific Fields
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About

Henrik Salje is a Group Leader in the Mathematical Modelling of Infectious Diseases Unit at Institut Pasteur. His group focuses on applied public health research, especially with regards to the spread of arboviruses. His research combines the development of analytical approaches with empirical research to better understand the transmission dynamics of different infectious diseases. In particular this involves working with genetic, antigenic and epidemiological data. He has a Bachelors and Masters degree in Biochemistry from Oxford University, a Masters degree in Biostatistics from Johns Hopkins Bloomberg School of Public Health and a PhD in Epidemiology, also from Johns Hopkins. Prior to starting his PhD, he worked in financial modeling in the investment banking sector in London. He is also an Adjunct Assistant Professor at Johns Hopkins Bloomberg School of Public Health.

Projects

Project
Ongoing
7 Members

Assessing the threat posed by zoonotic viruses like MERS-CoV, Nipah, Yellow Fever or plague

Simon Cauchemez (PI)

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 […]
Project
Ongoing
6 Members

Analysis and modelling to support decision making during epidemics

Simon Cauchemez (PI)

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 […]
Project
Ongoing
10 Members

Statistical and mathematical methods to characterize disease transmission from incomplete epidemiological data

Simon Cauchemez (PI)

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 […]
Project
Ongoing
3 Members

Developing a One Health perspective: the case of Nipah virus

Birgit Nikolay (PI)

  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 […]
Project
Ongoing
3 Members

Optimizing the interpretation of serological data

Henrik Salje (PI)

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 […]
Project
Ongoing
3 Members

Use of sequences to identify drivers of pathogen spread

Henrik Salje (PI)

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 […]
Project
Ongoing
2 Members

Identifying the role of immunity in driving viral diversity – dengue case study

Henrik Salje (PI)

Dengue causes significant morbidity and mortality worldwide, with millions of symptomatic cases occurring throughout the central band of the world each year. Large increases in cases are often associated with a shift in predominant […]
Project
Ongoing
5 Members

Improved understanding of patterns of pathogen infection risk

Henrik Salje (PI)

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 […]

Publications

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