What a start to the conference!
The theme of harnessing HIV and STI prevention opportunities rang throughout the hall during the plenary sessions - and continued to echo throughout the presentations.
Of particular note (for me) was the Causal Interactions Session - specifically the ‘Mega Model’ session presented initially by Marissa Becker and later by James Blanchard. At the base of these talks were the Mega Model diagram and a central concept of fluidity in program design approach. He asks us to specifically consider population transmission dynamics and individual risk, namely looking at biology, behaviour and networks when planning research and developing projects. Blanchard illustrated his ideas through asking the group: why do populations that look similar often have very different HIV epidemics?
The mega model helps address this. In part, this diagram takes a look at how we can modify our approach to problems and adjust our actions along what is occurring in a group or individual’s time line. Without getting too complicated, his argument is that for every phase in a timeline, we should be examining what is actually happening for people during each phase or ‘window’ of the continuum. This is done by considering each phase by analysing 1. Behaviours of groups/individuals 2. Networks that affect group/individual decision making and 3. Biological influences that impact on health changes/disease processes during each window.
An example might be a woman is sexually active at age 14, has casual partners for 2 years, commences sex work in a brothel for 4 years and then ceases sex work. In addition to larger influences, say limited access to education or gender violence, these timeline windows or phases can be examined for influences. Behaviour might include early sexual debut, Networks she interacts within might be intergenerational relationships and Biologically, an immature cervix and high levels of inflammation play significant roles on the trajectory of her timeline. Different influences at each window will be affecting her individually but they can also change how a program or intervention might be aimed.
By examining the nuances of individual and group timelines, you can negotiate and recognise the smaller differences that can greatly influence group outcomes.
Essentially, we should be approaching problems in a flexible manner that considers all angles of influence for a group or individual PRIOR to instituting a program. This would help stop a ‘one size fits all’ approach while recognizing and accounting for variables that have previously gone unrecognized or acknowledged in program or study development. This will allow us to closely examine the influence of individual or group variables more fully.
It is much simpler than it sounds! Of course, everyone has their favourite method but I saw this as a thoughtful approach to research and project development.