Computational

Mathematical Models for Infectious Disease Dynamics

February 13th - 24th 2017

Wellcome Genome Campus, Hinxton, UK

Summary

Over the last two decades, mathematical models have seen a huge
development in all aspects of infectious diseases, from microbiology to
epidemiology and evolution. Professionals in these fields are now exposed
to a wide range of models, often without receiving appropriate training.

This intensive, two-week course combines lectures, discussions and
hands-on computational practicals and is aimed at any life scientist,
public health officer, or medical or veterinary professional with an
interest in quantitative approaches to infectious disease dynamics and
control in humans or animals.

The basic concepts of the course are applied largely to human infectious
disease systems, with reference to more general applications in wildlife,
livestock and plant systems. The course has a strong emphasis on building
practical skills using the programming software R and RStudio. The course
starts with an introduction to computer programming from first
principles, but participants who are not familiar with R are encouraged
to learn the language basics (data analysis, vector manipulation and
graphics) before attending. Please note: The course is
not aimed at scientists with extensive experience in modelling or with a
strongly theoretical background. Applicants whose research project
involves the use of models or interactions with modellers will be
selected in priority.

Feedback from the 2016 course:

  • “I want to thank all of those involved organizing this wonderful course and I encourage you to keep bringing this top level science to the developing world.”
  • “Special thanks to each of the instructors for being so attentive and making themselves approachable. Their commitment was obvious and appreciated.”
  • “The experience taken from this course it is going to be of major relevance to my research but also to my personal career. It was great to have contact with such an amazing group of lectures and see their passion of their research and availability to teach, very inspirational. Just have to say thank you all!!”
  • “This course was undoubtedly of high quality and lecturers have a great teaching skill. Lectures were extremely well organised and were able to show us how an understanding on the detailed maths covered in this course is helpful to use disease models. Lectures on statistical inference also explained, in a very clear manner, topics that are important but not easy to approach by many epidemiologists. I would like to thank all the lectures and organisers once again!!”
  • “Fantastic course with brilliant instructors. Allowed me to crystalise my modeling plans and introduced me to a large number of learning materials to utilise in the future.”

Programme

The programme will cover introductory and advanced concepts in
mathematical modelling of infectious diseases, including:

  • Mathematical review (calculus, probability…)
  • Population dynamics
  • Deterministic and stochastic models
  • Modelling structured populations: Age-structured, Spatial and Network models
  • Applied programming with R
  • Statistical estimation of models
  • Computer-based simulations

Learning outcomes
After attending this course, participants will be able to:

  • design, implement and estimate simple epidemic models
  • better appreciate the value and limits of mathematical models in their own field
  • more fully understand and apply knowledge from scientific articles that include mathematical models
  • explore the behaviour of simple models
  • engage more effectively in collaborations with mathematical modellers

Instructors and speakers

Course instructors
Andrew
Conlan
University
of Cambridge, Department of Veterinary Medicine, UK
Cerian
Webb
University
of Cambridge, Department of Plant Sciences, UK
TJ
McKinley
College of
Engineering, Mathematics and Physical Sciences, University of Exeter,
UK
Nik
Cunniffe
University of Cambridge, Department of Plant
Sciences, UK
Matt
Castle
University of Cambridge, Department of Plant
Sciences, UK
Ellen
Brooks Pollock

School of Social and Community Medicine, University of Bristol, UK
Leon
Danon
School of Social and Community Medicine, University of
Bristol, UK

Guest speakers
John
Edmunds
London
School of Hygiene and Tropical Medicine, UK
Azra Ghani
Imperial College London, UK
Daniel
Streicker

University of Glasgow, UK
Caroline
Trotter
University
of Cambridge, UK

How to apply

Prerequisites
The course is aimed at life scientists, public health officers and
medical or veterinary professionals with an interest in quantitative
approaches to infectious disease dynamics and control in humans or
animals.
Applicants are typically educated to a minimum of A or AS level in
mathematics and should include details of their maths education, as well
as any previous experience using R or other scientific software, in the
application.

Cost
The
course is subsidised by the Wellcome Genome Campus Advanced Courses
and Scientific Conferences Programme. This is a residential
course and
there is a fee of £1065 towards board and lodging for
non-commercial applicants. Please contact us for the commercial fee.

Additional limited bursaries are available (up to 50%
of the course fee)
and are awarded on merit. Please see the “Bursaries”
tab for details.

Applications
Applications for this course can be completed online. If you have any
problems with the online application process, please contact us.

Please note: Applications
must be supported by a
recommendation from a scientific or clinical sponsor (e.g. supervisor or
head of department). A request for a supporting
statement will be sent
to your nominated sponsor automatically during
the application process.
Applicants must ensure that their sponsor
provides this supporting
statement by the application deadline. Applications without a supporting
statement cannot be considered.

Deadlines
Deadline for Applications: Closed

Travel visas
Please contact the
event organiser if you require a letter to support a
travel visa
application. Note that letters will be provided to confirmed
attendees.

Non-European Economic Area or Swiss nationals may be required to have a
visa to enter the UK.
Early application is strongly advised, as this process can take 6-8 weeks
or longer.

Please visit the following websites for further information:
UK Border Agency website and information for general visitors and business
visitors.

Cost and bursaries

Cost
The
course is subsidised by the Wellcome Genome Campus Advanced Courses
and
Scientific Conferences Programme. This is a residential
course and
there is a fee of £1065 towards board and lodging for
non-commercial applicants. Please contact us for the commercial fee.

Bursaries
Advanced Courses are subsidised for non-commercial
applicants from anywhere in the world. Additional, limited bursaries are
available (up to 50% of the course fee) and are awarded on merit. If you
would like to apply for a
bursary, please complete the bursary section
of the online application
form.

Please note that both the applicant
and sponsor are required to provide
a justification for the
bursary as part of the application.

Bursary terms and conditions

UK Courses (held at the Wellcome Genome Campus, Hinxton,
Cambridge)
A
limited number of bursaries are available for each course. These are
awarded by the selection committee according to merit. The bursary
covers a maximum of 50% of the course fee, though in exceptional
circumstances an application for the total course fee may be considered.
Where there are many bursary applications, the selection committee may
issue smaller amounts. We cannot assist with travel costs to attend UK
courses.

Overseas Courses (held outside of the UK)
A
limited number of bursaries are available for each course. These are
awarded on merit to cover travel, accommodation and sustenance. The
maximum award for travel (economy class) will be £750.

Bursaries can be applied for as part of the course application form.
Applicants
will be notified of a bursary award along with their place on
the
course, usually within one month of the application deadline. The
decision of the selection committee is
final.

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