MATHEMATICAL ECOLOGY AND EPIDEMIOLOGY - 2020/1
Module code: MAT3040
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
An introduction to the applications of ordinary, delay and partial differential equations to ecology and epidemiology.
LLOYD David (Maths)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
JACs code: G120
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 117
Lecture Hours: 33
Prerequisites / Co-requisites
MAT2007 Ordinary Differential Equations
Indicative content includes:
- Review of simple ODE models in ecology such as the logistic and Lotka-Volterra models. Extensions of such models such as the use of the Holling functional responses. Phase plane analysis of such models.
- ODE models in epidemiology. The Kermack McKendrick model. Higher dimensional models that include, for example, an exposed compartment, or which incorporate treatment, vaccination or quarantining. Analytical techniques useful in the linearised analysis of high dimensional systems, such as the Routh Hurwitz conditions. The calculation of the basic reproduction number and its importance in epidemiological modelling.
- Age structured models and their reformulation into delay differential equations or renewal integral equations. The study of the characteristic equations resulting from the linear stability analysis of such models. Use of such equations in ecology and epidemiology, to include the Ross Macdonald model of malaria transmission. The basic reproduction number for models with delay.
- Reaction-diffusion equations. Travelling wave solutions; applications to ecology and epidemiology.
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||IN-SEMESTER TEST (50 MINS)||20|
The assessment strategy is designed to provide students with the opportunity to demonstrate
· Understanding of how to model real life ecological and epidemiological scenarios, and an understanding of the meaning of the terms in a given model.
· Knowledge of appropriate mathematical techniques to analyse the models.
· Ability to make predictions.
Thus, the summative assessment for this module consists of:
· One two-hour examination (80%)
· One in-semester test at roughly the half way stage (20%).
Formative assessment and feedback
There will be 4 marked exercise sheets issued at roughly equal intervals. Written feedback is provided.
- introduce students to basic principles involved in mathematical modelling in ecology and epidemiology
- give students an appreciation of how ordinary differential equations, delay differential equations and partial differential equations can apply in various ecological and epidemiological scenarios
- teach appropriate analytical techniques for studying such models
- give students an appreciation of how to interpret the results and make predictions
|1||An understanding of how to model ecological and epidemiological problems using differential equations (ordinary, partial and delay)||KCT|
|2||An understanding of appropriate analytical techniques for the study of such problems||KC|
|3||An understanding of how to interpret the results of the analysis and how to make predictions||KCT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to provide:
- Skills in modelling ecological and epidemiological phenomena mathematically
- Knowledge of mathematical techniques appropriate to the study of those problems.
- An appreciation of how to interpret the results and make ecological or epidemiological predictions as appropriate.
The learning and teaching methods include:
3 one-hour lectures per week for 11 weeks, involving traditional lecturing and class discussion.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: MAT3040
Programmes this module appears in
|Mathematics MSc||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics with Music BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Economics and Mathematics BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics and Computer Science BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics MMath||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics with Statistics BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Financial Mathematics BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics and Physics BSc (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics and Physics MPhys||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics and Physics MMath||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.