Exclusive Interview: Diepreye Ayabina discusses her work on IMPACT-TB

Posted on: April 11, 2019

 

Diepreye Ayabina is a research assistant at LSTM working with Gabriela Gomes on modelling heterogeneity in TB transmission as part of the IMPACT TB . We sat down with her to discuss the work she has done so far and upcoming plans for the final year of the programme. You can follow her on Twitter @preyeayabina

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Q: You are working at LSTM as a research assistant on modelling heterogeneity for the IMPACT-TB project, can you explain the methods you are using in this project?

I work with mathematical models that incorporate individual-level heterogeneity in risk to tuberculosis. I apply methods from economic theory to estimate distributions of risk from incidence data, then I parameterize the models with this distribution to make predictions about the impact of interventions such as active case finding.

Q: Why are using these methods in particular?

There are several epidemiologically important sources of variation in risk and often, most measured risk factors do not adequately capture the entire risk in a population. So instead of using traditional approaches that compartmentalize the population according to known risk factors such as age, sex, incarceration etc., I follow the premise that a distribution of unobserved heterogeneity can be inferred from incidence trends in a holistic manner.

Q: Why is modelling so important for a health research project like IMPACT-TB?

Mathematical modelling plays an important role in programs that focus on controlling infectious diseases, such as IMPACT-TB, because they allow for rapid assessment of the impact of projects on disease burden and can make predictions about the scale up of programs towards meeting global targets.

Q: You have recently produced a publication called ‘Introducing risk inequality metrics in tuberculosis policy development’. Why did you decide to focus on this topic? 

This paper introduces concrete metrics of risk inequality, demonstrating their utility in mathematical models and emphasizes the importance of incorporating heterogeneity in mathematical models of infectious diseases.  The availability of comparable inequality metrics in economics and health can pave the way to pertinent studies between income inequality and health.

Q: The next IMPACT-TB consortium meeting will take place in Kathmandu, Nepal in July. What are you hoping to present on?

I’m currently working on some theoretical approaches to fine tuning our methods paper on risk inequality metrics and I hope to present some of this. Also, I would be presenting work that applies the methods in the risk metric paper to Nepal and Vietnam at the implementation district level.

Q: You are also attending the EEID conference in the USA in June. Can you tell us a little more about that?

The Ecology and Evolution of infection disease (EEID) conference is an annual conference organised by IDEAS (Infectious Disease Evolution Across Scales; a group of researchers with diverse and common interests in evolution of infectious diseases). This year’s edition, the 17th since inception, will be held at Princeton University. EEID attracts global leading researchers of infectious disease and presents an opportunity to present our work on risk equality metrics, be informed of recent advances in my research area as well as establish links with potential collaborators. I’m particularly excited about this year’s edition as one of core themes is the behavioural and environmental drivers of infectious diseases which play a key role in the control of tuberculosis.