Monday, 23^rd May, 2016
16.00 - 17.00 : Room BG10, Ground Floor
Oakfield House

Gabriela Gomes
Liverpool School of Tropical Medicine, UK
and
Research Centre in Biodiversity and Genetic Resources
University of Porto, Portugal

"A double-edged sword in the treatment of high-risk groups"

  

Having started a research career in non-linear dynamics, symmetries and patterns, I was easily intrigued by the complexity of risk factors and processes that determine the patterns of disease in populations. After some initial years studying fluids and chemical reactions, my attention drifted to the dynamics of microbes in interaction with their hosts, and resulting infectious diseases.

Confident that infectious disease epidemiology would be all about specific population processes, differing essentially from non-communicable diseases, I spent over a decade developing mathematical models of infectious disease transmission. These models may come in the simplest forms that compartmentalise the population into a minimal set of groups - such as susceptible (S) and infected (I) - or in more detailed implementations, going all the way to representing hosts at the level of individuals, connected by a network of contacts, exposed to a diversity of evolving pathogens, in a dynamic environment.

Now, I realise that when it actually comes to quantify and interpret measurements of disease, whether observationally or experimentally, most valuable insights result from processes that are common to both infectious and non-communicable diseases. Most remarkably, any heterogeneous population under pressure by any disease, undergoes a process of cohort selection whereby high-risk individuals are affected preferentially. This can easily overrule the complexities of transmission dynamics and feedbacks in the particular case of infectious diseases, and turn interventions into double-edged swords. Applying this general population process, we can answer outstanding questions, such as: 

1. Why do vaccines appear less efficacious in higher-incidence settings?

2. Why do transmission models over-predict the impact of interventions to control infectious diseases?

3. What does cohort selection have to say about “irreproducible research”?

 

ALL WELCOME