ANR SMITID Project
Viruses can cause epidemics of high impact in developing and developed countries alike. For such pathogens, inferring transmission links within a host population or between host populations (e.g. for zoonoses) is crucial to build epidemiological predictions and control strategies. In this aim, for fast-evolving pathogens, one can take advantage of the statistical analysis of pathogen sequence data because they inform which hosts contain pathogen variants that are most closely related to each other. However, so far existing models have mostly exploited a limited amount of information from sequencing data, such as consensus Sanger sequences, although deep Sanger sequencing (DSS; based on amplicon cloning) and high-throughput sequencing (HTS) techniques can reveal the polymorphic nature of within-host populations of pathogens. In this project, we propose an avant-gardist modelling and statistical approach that will exploit DSS and HTS data to infer disease transmission links for fast-evolving pathogens, such as viruses, and to infer relationships between transmissions and environment.
Alamil M, Hughes J., Berthier K., Desbiez C., Thébaud G., Soubeyrand S. (2019). Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases. Philosophical Transactions of the Royal Society B: Biological Sciences 374: 20180258. doi:10.1098/rstb.2018.0258
Picard C., Dallot S., Brunker K., Berthier K., Roumagnac P., Soubeyrand S., Jacquot E., Thébaud G. (2017). Exploiting Genetic Information to Trace Plant Virus Dispersal in Landscapes. Annual Review of Phytopathology 55. doi:10.1146/annurev-phyto-080516-035616
Alamil, M. (2017). Modélisation de la cinétique et de l'évolution virale intra-hôte. Master 2 Internship Report, BioSP, INRA. Under the supervision of S. Soubeyrand.
Gawinowski, M. (2017). A simulation model for the kinetics, evolution and transmission of viral populations. Master 1 Internship Report, BioSP, INRA. Under the supervision of S. Soubeyrand.
Boge, J. (2019). Développement d’un composant de visualisation spatio-temporelle d’une épidémie. Matser 2 Internship Report, BioSP, INRA. Under the supervision of J.-F. Rey.
2019/05/06: Our manuscript corresponding to the methodological core of the SMITID project is published in Philosophical Transactions B - Alamil et al. (2019)
2019/02/01: Julien Boge joined us to work on the SMITID software WP during his Master internship supervised by Jean-François
2018/09/11: R scripts for estimating epidemiological links available in the ZENODO citeable archive, as well as Ebola, Swine influenza and potyvirus data used in our analyses
2018/06/25: First external PhD monitoring meeting for Maryam Alamil
2018/01/08: Karine Berthier will visit BioSP one day per weekly, in particular to work on the SMITID project
2017/10/01: Maryam Alamil begins her PhD funded by SMITID
2017/06/29: Meije Gawinowski starts her summer internship funded by SMITID
2017/06/07: Our review for characterizing plant virus spread using molecular epidemiology is online in Annual Review of Phytopathology
2017/05/02: Maryam Alamil starts her master internship funded by SMITID
2017/02/28: SMITID was presented at INRA’s conference for the 2017 Paris International Agricultural Show (SIA) - Symposium on People, Animals and the Environment: One Health
2017/02/09-10: Discussion about the links between the research carried out in SMITID and the topics of interest in the STrATEGE network (STATistics in Ecology and GEnomic data)
2016/11/25: Kick-off meeting at the ANR headquarter (Paris) to launch the 2016 projects of the "Emerging pathogens-OneHealth" comity (CES 35)
2016/11/04: Kick-off meeting at Avignon gathering the project members and a few other colleagues
2016/11/01: Starting date of the project