Use this URL to cite or link to this record in EThOS:
Title: Mathematical modelling of epidemics with account for population awareness
Author: Agaba, Grace Omeche
ISNI:       0000 0004 5992 4689
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
In this thesis I developed and analysed several mathematical models that describe the dynamics of infectious diseases spreading in a population simultaneously with people becoming aware of the presence of the disease and thus modifying their behaviour. This is achieved using compartmental models, with further extensions to models with time delays and the administration of vaccines. Resulting mathematical models were analysed using the techniques of dynamical systems and bifurcations theory, complemented by direct numerical simulations. Design of optimal strategies maximising the reduction of infection rates subject to logistical constraints were studied within the new modelling framework and with a view to be used in realistic contexts. Of particular interest is the design and analysis of the impact of local and global awareness campaigns, as well as the administration of vaccines to minimise the spread of infections.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: RA0648.5 Epidemics. Epidemiology. Quarantine. Disinfection