Mathematical models are increasingly important to understand new and existing diseases and for planning how we tackle these diseases. Models with enough detail of how a disease interacts with the body, how drugs and other interventions affect the disease, and how health systems respond can help us evaluate the best approaches for addressing diseases.
In this project, we will examine the impact of pathogen resistance to disease interventions. We address two important pathogens: malaria and SARS-Cov-2. As we get closer to eliminating malaria and other diseases, preventing diseases from evolving resistance to response measures becomes ever more critical. Since the characteristics of resistance differ depending on the level of disease, public health strategies are likely to change as we near elimination. In the current global SARS-CoV-2 pandemic, we are at a crucial moment to define strategies for deploying vaccines. Since the virus that causes COVID-19 is likely to mutate further, new vaccine-resistant variants may emerge.
We will examine how resistance to vaccines and other treatment measures comes about, and will define intervention roll-out strategies to best avoid resistance for different pathogens. Our work will bring together mathematical models and what we know about how diseases evolve, to come up with the best possible health policies and vaccine roll-out plans over the coming years. We will build and calibrate detailed parasite models, mosquito-to-human transmission models and adapt individual-level models for malaria. We will also adapt models of SARS-CoV-2 to examine the emergence of vaccine-resistant COVID variants.
These new models will help identify key disease characteristics that drive the evolution of resistance and the spread of resistant pathogens. We will examine resistance to vaccines, drugs and immune response therapies; in the case of malaria, we will also examine the spread of mosquitoes resistant to insecticides.
Our work will provide evidence to support the selection of disease control and elimination strategies and inform decision-making, especially surrounding resistance. Of immediate relevance to malaria and COVID-19, it will also inform efforts to control other diseases.