Grippe | EPFL Graph Search

La grippe (ou influenza) est une maladie infectieuse fréquente et contagieuse causée par certains virus à ARN de la famille des orthomyxoviridés : le virus de la grippe A, le virus de la grippe B, le virus de la grippe C et le virus de la grippe D. Elle touche les oiseaux et certains mammifères dont le porc, le phoque et l'être humain. Favorisée par la promiscuité et le confinement à l'intérieur des bâtiments, la grippe humaine sévit ainsi sur un mode épidémique, saisonnier automno-hivernal (saison froide) dans les pays tempérés et avec un pic lors de la saison des pluies (saison chaude) dans les pays tropicaux. Des recherches montrent également qu'il existe une relation entre les pandémies grippales et les conditions d'El Niño à La Niña dans l'océan Pacifique. Les années où la Niña sévit, l'épidémie de grippe est plus virulente, elle touche plus de personnes et fait davantage de morts. À l'inverse, les années où El Niño est dans l'océan Pacifique, la propagation de la grippe est plu

Virucidal nanomaterials against influenza

Özgün Kocabiyik

Influenza affects millions of people in all parts of the world. The fact that influenza virus can spread through air increases the chance of influenza outbreaks. There are 3 to 5 million severe cases of influenza resulting in 290,000 to 650,000 deaths every year. Not as common as outbreaks, but in the 20th century four influenza pandemics appeared: Spanish influenza (1918, 50 million deaths), Asian influenza (1957, 2 million deaths), Hong Kong influenza (1968, 1 million deaths) and swine influenza pandemic (2009, 150,000 to 500,000 deaths). World health organization (WHO) emphasizes that influenza is the only pathogen that has a reasonable chance of causing a new pandemic in the near future. It is unlikely that current influenza vaccines and therapeutics will be sufficient to prevent a coming pandemic. Presented within this thesis is a novel approach to irreversibly inhibit influenza virus with non-toxic and highly effective nanomaterials. These nanomaterials are designed so to bear glycan end-groups that bind to the influenza virus with high-affinity. Their design is such that binding determines a chain of events that leads to the irreversible loss of viral infectivity (i.e. virucidal mechanism). There are two key elements in the design of these materials. The first is the correct glycan sequence, terminating with sialic acid, needed to bind with high affinity to the influenza virus attachment ligand that is hemagglutinin. The second is a certain hydrophobic content in the drug, needed to impart the irreversibility in the antiviral effect. We show that when both elements are present, a virucidal non-toxic drug can be achieved either with gold nanoparticles or with cyclodextrins. With these materials several human influenza strains of type A and B were inhibited with virucidal mechanism. Furthermore, ex-vivo and in-vivo antiviral activity of the nanomaterials with cyclodextrin core was investigated against a very aggressive influenza A strain. Ex-vivo studies clearly demonstrated that the mechanism of inhibition is virucidal. In the in-vivo studies, nanomaterials prevented the mice to loose weight and body temperature; significantly reduced the virus concentration in the lungs and in the nose. These materials can be further developed to target animal strains of the influenza virus. This is particularly important since influenza pandemics usually appear when humans are infected with a new animal strain such as avian and swine influenza.

EPFL2019

Contact networks across ages: computational analysis of epidemiological dynamics

Gianrocco Lazzari

For decades mathematical modeling in epidemiology has helped understanding the dynamics of infectious diseases, as well as describe possible intervention scenarios to prevent and control them. However, such models were relying on several assumptions, such as the ones on the structure of the underlying contact networks. The robustness of their predictions was therefore limited by this lack of knowledge. About a decade ago, with the advent of digital epidemiology, scientist have finally started to try to corroborate those assumptions, for instance with the use of wearable sensors to measure indeed contact networks. In this thesis, together with collaborators, I try to combine the digital collection of public health data with computational tools, in order to have a more realistic understanding of the phenomena under consideration. In two projects it was possible to finalise such marriage, thanks also to fruitful collaborations with other researchers who provided the data. This is for instance the case for the two chapters respectively on the modeling of influenza and plague outbreaks. Although they involve different technologies for the data collection, historical epochs and data types, the traditional epidemiological modeling allowed us to derive interpretable conclusions, capable for instance to inform public health interventions. In other projects, either the relevant data collection is still ongoing in the lab (like for the FoodRepo project), or the data collection has not started yet (like for the project on measles), although our work provides insights on the importance of such data collection for future studies. In the first chapter, we explore different mechanistic interpretation compatible with our data on the 1630 plague outbreak in Venice, collected through the digitisation of parish books from the historical State Archives of Venice. The data shows a non trivial temporal structure, which led us to propose few different epidemiological explanations. Further data collection will be needed to better constrain such interpretations. In the second chapter, we use previously recorded contact data in a high-school to assess the relative effect of ventilation on the influenza spread, with respect to vaccination strategies. Our result suggest the usefulness of non pharmacological interventions such as indeed improved ventilation, which become even more meaningful in the context of vaccination hesitancy and low vaccine efficacy, due for instance to the high mutation rate of viruses like influenza virus. In the third chapter, we propose a simple network generation model to try to explain differences in the incidence of highly infectious diseases (such as measles), across countries with similar vaccination coverages. Such differences are indeed one of the main open questions in public health, which are not yet fully understood even considering social phenomena such as recent anti-vax movements. In the last chapter, we present our open database of barcoded food products, FoodRepo. This database represents on the one hand, the first piece of a large study ongoing in our lab, in the field of nutritional epidemiology, that aims to assess the variability of glycemic response in an healthy cohort. On the other hand, important features such as its openness and programmatic accessibility make it an important digital tool at the service of any private or public actors in the field of nutrition.

EPFL2020

Assessing the Dynamics and Control of Droplet- and Aerosol-Transmitted Influenza Using an Indoor Positioning System

Gianrocco Lazzari, Marcel Salathé

There is increasing evidence that aerosol transmission is a major contributor to the spread of influenza. Despite this, virtually all studies assessing the dynamics and control of influenza assume that it is transmitted solely through direct contact and large droplets, requiring close physical proximity. Here, we use wireless sensors to measure simultaneously both the location and close proximity contacts in the population of a US high school. This dataset, highly resolved in space and time, allows us to model both droplet and aerosol transmission either in isolation or in combination. In particular, it allows us to computationally quantify the potential effectiveness of overlooked mitigation strategies such as improved ventilation that are available in the case of aerosol transmission. Our model suggests that recommendation-abiding ventilation could be as effective in mitigating outbreaks as vaccinating approximately half of the population. In simulations using empirical transmission levels observed in households, we find that bringing ventilation to recommended levels had the same mitigating effect as a vaccination coverage of 50% to 60%. Ventilation is an easy-to-implement strategy that has the potential to support vaccination efforts for effective control of influenza spread.

2019