PhD Position (Fully Funded): Optimising Zoonotic Virus Surveillance in Bats with Mechanistic Models Background and objectives Bats are well known reservoirs for several zoonotic viruses of public health importance, including coronoviruses, Ebola and Nipah. Numerous epidemics over the last twenty years, including the recent COVID-19 pandemic, have highlighted a critical need for improving our understanding of viral diversity within sylvatic reservoirs such as bats. However, isolating viruses from wild bat populations is highly labour intensive and entails large overheads and investments of time. It is therefore pertinent to ask how field sampling can be optimised so we can maximize our knowledge of bat-borne viruses given the finite resources available. This is where predictive modelling, and this thesis, can help. Our working hypotheses are that fundamental bat ecology provides major drivers on the dynamics of bat-borne viruses, and that mechanistic models of these effects can help optimise field sampling. The thesis will explore a range of ecological phenomenon that potentially influence viral dynamics in bats. The thesis will initially study how viral dynamics are affected by seasonality in bat reproduction, and then address the effects of other ecological factors such as land use, climatic change or spatial aggregation. The thesis will also answer the practical question of what data is required by modellers in order to predict the dynamics of bat borne zoonoses and to optimise surveillance. The PhD student is expected to calibrate SIR models to existing field data using Bayesian approaches (e.g. Markov chain Monte Carlo in NIMBLE, https://r-nimble.org), test the predictive performance of the models, and quantify the effects of the timing and duration of reproductive periods on seasonality in pathogen circulation and detectability via sensitivity analyses. All data required to complete the PhD are already available. Thus, the COVID-19 situation will not interfere with the completion of the PhD. However, complementary data sets will be collected in the framework of the forthcoming Horizon Europe project BCOMING. Field work undertaken within BCOMING will give the PhD student the opportunity to participate in bat capture and sampling activities and become familiar with the ecological systems being studied in Cambodia and Guinea. During the PhD, three scientific publications in peer-reviewed journals should be written and compiled for the PhD thesis. One accepted publication is mandatory to defend the PhD. Candidate requirements The candidate is required to possess a masters degree in fields such as ecology, epidemiology, biostatistics or applied mathematics. The candidate is required to be, or become, comfortable with : theoretical ecology, epidemiological modelling, temporally forced SIR models, non-linear dynamics, chaos, biostatistics, Bayesian inference and Markov chain Monte Carlo. A demonstrable history of working with the following (or similar) would also be highly appreciated: R, git, Rmarkdown, latex and NIMBLE. Proficiency in English (both spoken and written) is required, as well as good communication skills (oral and in writing). 1 Conditions of employment Start date: October 2022 Duration of contract: 3 years Monthly gross salary: 1975 € + health insurance Hosting institutions: CIRAD, INRAE and Montpellier University (currently ranked 3rd globally in ecology). Working location: Campus International de Baillarguet, UMR ASTRE, Montpellier, France Contact information For further information, please contact David Pleydell (david.pleydell@inrae.fr) and Julien Capelle (julien. cappelle@cirad.fr) Application procedure Applications can be made via email. Please include a CV, a letter of motivation and contact details for two or three referees. Applications must be received no later than 15 August 2022. Recent publications from the supervisors Muñoz, F., Pleydell, D.R.J. & Jori, F. (2022) A combination of probabilistic and mechanistic approaches for predicting the spread of African swine fever on Merry Island. Revised manuscript under review at Epidemics. Pleydell, D. R.J. & Bouyer, J. (2019) Biopesticides improve efficiency of the sterile insect technique for controlling mosquito-driven dengue epidemics. Communications Biology. DOI:10.1038/s42003-019-0451-1 Peccoud, J., Pleydell, D.R.J. & Sauvion, N. (2018) A framework for estimating the effects of sequential reproductive barriers: implementation using Bayesian models with field data from cryptic species. Evolution. DOI:10.1111/evo.13595 Pleydell, D.R.J., et al (2018) Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape. PLOS Computational Biology. DOI:10.1371/journal.pcbi.1006085 Cappelle, J. et al (2020) Nipah virus circulation at human-bat interfaces, Cambodia. Bull. World Health Organ. 98, 539–547. DOI:10.2471/BLT.20.254227 Cappelle, J. et al (2021) Longitudinal monitoring in Cambodia suggests higher circulation of alpha and betacoronaviruses in juvenile and immature bats of three species. Scientific Reports. 11.1. DOI:10.1038/ s41598-021-03169-z