Impact of environment and control strategies on the dynamics of Rift Valley fever

Start date
1 July 2021
Duration
36 months
Application deadline
Funding information

Funding will cover University fees at the UK/EU rate for three years and a stipend for three years at RCUK levels (about £15,000 per year). In addition, funding includes bench fees to a value of about £10,000 over the three years to cover conference attendance and training. For further information visit the Veterinary Medicine and Science PhD programme page.The PhD studentship is expected to commence no later than October 2021.

Funding source
This PhD studentship has been generously funded by the Longhurst Legacy
Supervised by

About

Mosquitoes are considered the deadliest animal in the world because of the devastating diseases that they carry. These include Rift Valley fever, whose outbreaks can lead to large economic losses to farmers, and sometimes hundreds of deaths in humans.

Many strategies to tackle mosquito-borne diseases have been proposed, for instance vaccination, change in water-body dynamics (due to, e.g. irrigation) and reduction of the mosquito population (via insecticides or releasing genetically modified, non-biting, male mosquitoes incapable of producing viable offspring). Mathematical models are powerful tools to safely assess these control strategies before applying them in the real world. These models need to capture the effects of weather/climate as mosquitoes thrive in warm and wet regions, to determine under which environmental conditions the mosquito population and/or the infection can fade out or establish.

You will develop and use models to assess the efficacy of classical and novel (e.g. release of genetically modified mosquitoes) strategies and some of their combinations. The modelling work will be relevant/applicable to other widespread vector-borne diseases.

Dr Lo Iacono will supervise the overall project, providing mathematical expertise and general guidance. Dr Betson will provide expertise in public health, vector-borne diseases and research experience in vector biology. Dr Bett (ILRI, Kenya) is a veterinarian with expertise in infectious disease modelling, participatory epidemiology and disease surveillance. Dr Boëte (ISEM, France) is an evolutionary biologist with a background in medical entomology. He will provide expertise on ecology and control of mosquito vectors.  Dr Betson, Bett and Boëte will act as co-supervisors.

Related links
Environmental limits of Rift Valley fever revealed using ecoepidemiological mec… Deadly Rift Valley fever: new insight, and hope for the future

The ideal starting time is July, but the option to start in October 2021 is also considered.  If you want to start in October, please discuss this with Dr Lo Iacono.

Eligibility criteria

This is an interdisciplinary project requiring computational and mathematical skills as well as a good understanding of biological processes. Applicants are required to hold an undergraduate degree in Mathematics or a related subject (e.g. Physics, Engineering). Undergraduates with a degree in Biological Sciences or related subjects are also welcomed as long as they have a strong interest in mathematical modelling. A Masters degree in a public health or epidemiological-related subject is desirable. Experience in mathematical modelling, biostatistics is desirable but not essential.

Available to UK and eligible EU students (i.e. who hold a settled status).

IELTS requirements: 6.5 or above (or equivalent) with 6 in each individual category.

How to apply

Please apply for this PhD through the School of Veterinary Medicine PhD applications portal. Applicants are invited to contact Dr Lo Iacono to discuss the project informally prior to making an application.


Application deadline

Contact details

Gianni Lo Iacono
- VSM 02
Telephone: +44 (0)1483 688893
E-mail: g.loiacono@surrey.ac.uk

Veterinary Epidemiology and Public Health

The student will be based at the Veterinary school at the University of Surrey. This is an ideal location which promotes informal interactions among the member of the team (e.g. through the research carried at the Neglected Tropical Diseases hub and at the Centre for Mathematical and Computational Biology) and constant exposure to innovative approaches, problems and settings beyond pure academia (e.g. vHive, https://vhive.buzz/). The PhD student will work in close connection with world leading scholars on a hugely relevant disease (RVFV is classified as one of the 10 deadliest virus by the WHO) and innovative control strategies in a truly international (UK, Kenya, France) environment. The student will learn state of the art modelling techniques that can be used in broader context and they will interact with experts from different background (mathematical model, parasitologist, veterinary, entomology) and institutes other than pure academia such as ILRI, with strong opportunities to engage in policy making. The team has a strong academic and non-academic network which will be beneficial to the student’s career.

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