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 Clement Twumasi

Clement Twumasi

Research student, School of Mathematics

Email:
twumasic@cardiff.ac.uk
Telephone:
07411484454
Location:
M/2.04, 21-23 Senghennydd Road, Cathays, Cardiff, CF24 4AG

The overarching main of my PhD research is to develop novel mathematical models to help better understand the spread of  Gyrodactylus infection dynamics across three different population of fish and three different parasite strains. It was required development of novel Simulation models, novel Approximate Bayesian Computation for complex model calibration, adoptation of recently developing methodolgy known as the Functional Data Analysis for advanced data exploration and visualization, Compartmental models and Socia Network models. This field/research requires advanved knowledge of  both theoritical mathematics and statistics as well as modelling and programming skills.

Research interests

Background

The management of infectious disease is a major concern for conservation of wild fish stocks and is a primary constraint on the viability and sustainability of farmed fish. One pathogen alone, infectious salmon anaemia, is estimated to have cost the Scottish farming industry £20 million in the 1998/1999 outbreak, and still costs the Norwegian and Canadian industries around US$11 and $14 million, respectively, per annum. Emerging infectious diseases also pose a serious economic risk to freshwater fisheries, with a number of newly detected pathogens causing large scale disease outbreaks in England, and, some trout fisheries in South Wales and South West England have had to close due these pathogens. Investigating the dynamics of infectious diseases among fishes is of high importance since farmed fish are the major source of human protein and aquaculture contributes significantly to the world economy.

Aims

This research will focus on the dynamics of Gyrodactylus parasitic infections among fish. Quite a bit is known about the dynamics of Gyrodactylus infections on a single fish, and there exist (agent based) simulation models that reproduce these dynamics. The overarching aim of this research is to produce a simulation model for Gyrodactylus infections across a whole population of fish, realistic enough that it can be used to inform management decisions for the control of Gyrodactylus infections. Aprroximate Bayesian Computation would be used for model calibration.  Several other complex models would be developed for subsequent objectives.

Research Area:

  • Compartmental models (Dynamical Systems)
  • Continuous-time Markov chains
  • Predator-prey models and host-parasite models
  • Biology of Gyrodactylus parasites
  • Social Network Models

Teaching

  • Postgraduate Tutor/ Teaching Assistance, Cardiff School of Mathematics.

  • Graduate Teaching Assistant

September 2017-September 2018    Department of Statistics   University of Ghana- Legon

 

Duties

Teach graduate courses including Stochastic Processes, Advanced Engineering Mathematics as well as Estimation and Statistical Inference.

Assist other lecturers in courses at other departments involving statistics in the university.

 

  • National Service (Research Assistant and Teaching Assistant)

September 2015- Oct. 2016      School of Public Health/Department of Statistic  and Mathematics                              

                                                           University of Ghana                         Accra-Legon

Duties: Taught Multivariate Methods, Stochastic Processes, Actuarial Statistics and Numeracy Skills at the Department of Statistics as a teaching assistant.

Taught Financial Mathematics at the Department of Mathematics. 

Assisted in Projects or academic research works and taught Biostatics at the School of Public Health as TA.

Thesis

In Silico Modelling Of Parasite Dynamics

Background


The management of infectious disease is a major concern for conservation of wild fish stocks and is a primary constraint on the viability and sustainability of farmed fish. One pathogen alone, infectious salmon anaemia, is estimated to have cost the Scottish farming industry £20 million in the 1998/1999 outbreak, and still costs the Norwegian and Canadian industries around US$11 and $14 million, respectively, per annum. Emerging infectious diseases also pose a serious economic risk to freshwater fisheries, with a number of newly detected pathogens causing large scale disease outbreaks in England, and, some trout fisheries in South Wales and South West England have had to close due these pathogens. Investigating the dynamics of infectious diseases among fishes is of high importance since farmed fish are the major source of human protein and aquaculture contributes significantly to the world economy.


Aims


This research will focus on the dynamics of Gyrodactylus parasitic infections among fish. Quite a bit is known about the dynamics of Gyrodactylus infections on a single fish, and there exist (agent based) simulation models that reproduce these dynamics. The overarching aim of this research is to produce a simulation model for Gyrodactylus infections across a whole population of fish, realistic enough that it can be used to inform management decisions for the control of Gyrodactylus infections. Aprroximate Bayesian Computation would be used for model calibration.  Several other complex models would be developed for subsequent objectives.


Research Area:



  • Compartmental models (Dynamical Systems)

  • Continuous-time Markov chains

  • Predator-prey models and host-parasite models

  • Biology of Gyrodactylus parasites

  • Social Network Models


Funding source

Vice Chancellor's International Scholarship for Research Excellence

Professor Owen Jones photograph

Professor Owen Jones

Chair in Operational Research

Professor Joanne Cable

Professor Jo Cable

Professor, Masters Lead