We use mathematical models to answer questions about the transmission and control of infectious diseases. Our work primarily focuses on dengue, Zika, chikungunya, malaria, and other vector-borne diseases, but we take interest in other systems, too.

The guiding paradigm for our research is answering questions of biological significance with the aid of mechanistic mathematical models informed by biological knowledge and data. This approach is guided by the philosophy that appropriately constructed models represent the best understanding we have of a system. By articulating our biological understanding in a mathematical form, we then have the ability to challenge our understanding quantitatively, by confronting models with data, and qualitatively, by performing theoretical analyses. When things go wrong, we figure out why, we learn something, and we advance science.

Scientific questions that interest us include...

• What are the spatial scales at which models can be used to meaningfully infer and forecast transmission dynamics?
• How can we best utilize information about human movement and other drivers to understand the spread of diseases?​
  
• What are key sources of uncertainty in intervention trials and how can we better account for them?
• What can we learn epidemiologically from pathogen genetic data? And how should we use those data mathematically?
• Is it worthwhile to target interventions, and if so what is the best way of doing that?

Please get in touch if you have an interest in these or related questions. We are highly collaborative and are looking to grow.