Disease outbreaks pose significant global challenges, impacting public health, ecosystems, and economies. Globalisation, population growth, urbanisation, and climate change have heightened the frequency and impact of diseases, necessitating effective management strategies to control outbreaks. There is a growing need for mathematical models, particularly epi-economic and bio-economic models, to help understand disease dynamics and evaluate interventions. By integrating economics and epidemiology, these models offer a comprehensive understanding of disease spread, considering individual behaviour and ecological factors.
This doctoral thesis explores the use of epidemiological models in understanding disease dynamics, assessing impact, and identifying effective mitigation strategies for different systems. Four paper drafts contribute to this objective. Paper 1 presents a bioeconomic model investigating pests and pathogens’ effect on forest harvesting regimes, offering insights for forest managers in designing effective control strategies. Paper 2 develops a compartmental metapopulation model to analyse COVID-19 transmission in care homes, identifying mitigation strategies for vulnerable communities. Paper 3 explores COVID-19 related sickness absence rates among NHS England staff, guiding resource planning and interventions. Paper 4 introduces a mechanistic compartmental model to estimate COVID-19 sickness absence, evaluating cost-effective interventions and informing workforce management decisions.
Several methodological approaches are employed, including; differential equations (compartmental modelling), autoregressive time series models, multivariate regression, and the net present value analysis.
| Date of Award | 24 Apr 2024 |
|---|
| Original language | English |
|---|
| Awarding Institution | - University Of Strathclyde
|
|---|
| Sponsors | University of Strathclyde |
|---|
| Supervisor | Adam Kleczkowski (Supervisor) & Itamar Megiddo (Supervisor) |
|---|