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.
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 […]
Identifying the role of immunity in driving viral diversity – dengue case study
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 […]
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 […]
2019Differential mobility and local variation in infection attack rate, PLoS Comput. Biol. 2019 01;15(1):e1006600.
2018Viridot: An automated virus plaque (immunofocus) counter for the measurement of serological neutralizing responses with application to dengue virus, PLoS Negl Trop Dis 2018 10;12(10):e0006862.
2018Dengue serosurvey after a 2-month long outbreak in Nîmes, France, 2015: was there more than met the eye?, Euro Surveill. 2018 Jun;23(23).
2018Reconstruction of antibody dynamics and infection histories to evaluate dengue risk, Nature 2018 May;557(7707):719-723.
2018Using serological studies to reconstruct the history of bluetongue epidemic in French cattle under successive vaccination campaigns, Epidemics 2018 12;25:54-60.
2018Micro-hotspots of Risk in Urban Cholera Epidemics, J. Infect. Dis. 2018 May;.
2018Understanding dengue virus evolution to support epidemic surveillance and counter-measure development, Infect. Genet. Evol. 2018 Apr;62:279-295.
2018Characterization of the Spatial and Temporal Distribution of Nipah Virus Spillover Events in Bangladesh, 2007-2013, J. Infect. Dis. 2018 Apr;217(9):1390-1394.
2017Real-Time Assessment of Health-Care Requirements During the Zika Virus Epidemic in Martinique, Am. J. Epidemiol. 2017 Nov;186(10):1194-1203.
2017Genomic history of the seventh pandemic of cholera in Africa, Science 2017 11;358(6364):785-789.
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