Mathematical Modelling Of Infectious Diseases

The last few years have been marked by the emergence and spread of a number of infectious diseases across the globe. For example, outbreaks of Zika and chikungunya in the Americas, Ebola Virus Disease in West Africa and MERS coronavirus in the Middle East and South Korea each resulted in substantial public health burden and received widespread international attention. These emergences have highlighted the many challenges faced by the public health community to anticipate, assess, manage and control these epidemics. In addition, established infectious diseases such as seasonal influenza, dengue or malaria keep on affecting hundreds of millions of persons each year. Policy-making to control these epidemics should ideally be informed by sound epidemiological assessments as well as projections of what may happen under a number of scenarios describing the different control strategies available. However, performing such analyses proves particularly challenging. First, epidemiological data are often frail, incomplete and hard to interpret, especially when captured in emergency and uncontrolled situations. Second, infectious diseases dynamics are complex and non-linear so that dedicated modelling techniques are required both to interpret trends and predict what will happen next.   The main research objective of our 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 populations, assess the impact of interventions, support policy making and optimize control strategies. Our approach is highly multidisciplinary, looking at infectious diseases through multiple perspectives (epidemiology, statistics, modelling, surveillance, public health, policy making, microbiology), multiple scales (intra-host, person-to-person transmission, spread at the local/national/international level) and multiple data streams (epidemiological, demographic, climatic, genomic, social media). We work closely with public health agencies in France and abroad to ensure our assessments can inform the public health response to epidemics.   Since the start of the COVID-19 pandemic, the team has been developping mathematical and statistical models to better characterize, understand and anticipate the threat posed by COVID-19 and evaluate the impact of control measures. Our research activities on COVID-19 are presented in a dedicated webpage: https://modelisation-covid19.pasteur.fr/.