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Entering into the hands-on design portion of my project has tested my approach to setting the stage for this malarial burden narrative, and encouraged me to consider the importance of accuracy as I aim to uphold certain standards of visual ethics as an information designer.

As I was considering the danger of misrepresenting data/information, I found that this can easily surface in regards to how the data is framed within the narrative. This matter of “framing” information and data is imperative to leading the audience to a fitting and influential conclusion. The catch — that power can be easily misused to lead a viewer in a false direction and to a completely fabricated understanding.

In both the sketches below, it is a mere matter of insufficient labeling that has rendered these graphs both incomplete and imprecise. The graph (on the left) has overlooked an important descriptive of the “children under five in sub-Sahara Africa.” This pie chart is far too optimistic and does give a realistic and current view of the RTS,S vaccine’s influence. This 50% efficacy stat only exists in regard to the population of children in Africa who participated in the third stage of the clinical trials. Of course, one would like to assume that these same findings would be mirrored in the rest of the population, but at this point, the RTS,S vaccine’s success is based on findings within the control group and estimated future outcomes.

The pie chart (on the right) attempts to relay the positive estimated future of the RTS,S vaccine once it reaches production in the general market. However, the error here is subtle. The RTS,S vaccine is a means of prevention and will only be available for children under five (because this is the demography on which it was tested). To say that the RTS,S vaccine will halve deaths by malaria is nearly accurate, but it needs to be accompanied by the included fact that it will accomplish this by preventing these individuals from contracting the disease. This vaccine is not meant to treat those who have already contracted the disease (this population must be addressed through a different form of medical aid). The hope, however, is that in time, fewer children will contract this disease, drastically lowering the malaria mortality rate by reducing the population at risk. Part of this mistake can be averted in properly setting the stage for this narrative by introducing malaria, how one contracts it, and what the RTS,S vaccine can play in this unfortunate replay.

This next sketch deals with properly identifying the audience in the initiative to act and correctly framing the result as a “estimated outcome.” It would be easy for a viewer to see this graph as a two-way intersection, where the route with the RTS,S vaccine at play will generate the estimated and visualized results. However, there is a great deal at hand in how this outcome will come to life — not only must the funding for the vaccine be sufficient, but this pre-cure must also get into the hands of the people in need. Not only is there a financial need to take this vaccine from petri dish to production, but there is a great deal of medical expenses involved in offering needy families this solution, especially during this time of economical crisis, both throughout the world and in their individual lives (what comes as a result of malaria’s financial burden).

I’m not sure how important it is to include this information in the data representation. However, it doesn’t subtly hurt to remind the audience that the story doesn’t stop here. In 2015, even if RTS,S reaches production status, it doesn’t end this global malaria burden at point blank. There are other factors involved in telling people that the solution exists and helping it reach the right hands. I guess this fills a sense of “moral obligation” in not allowing the data and its proffered conclusion to act as blinders for the audience, giving them a dulled sense understanding that it isn’t as simple as it looks. This isn’t like an arcade game — if you put the coin in, it lights up and plays and works, and if you don’t give it proper credit, the results aren’t the same. There is a whole system of nuts and bolts under the visible surface that relies on other resources and parts of the machine to make the outcome consistent with the message: coin versus no coin.

Also, this graph is deceiving in some respects as it needs to present the information to the audience as a whole. This is not an individual decision; it is a global choice. And if this option, to fund the vaccine, isn’t adopted and chosen by all, we will never reach that optimistic outcome. Once again, it isn’t as simple as a coin-operated machine. The message needs to include the prompt to spread the news and to encourage others to join in lifting this global malarial burden.

This blog post has helped me reevaluate my data in light of how I present it to the audience. It is has brought to my attention several key factors in creating an effective and accurate narrative. This story needs explicit wording, that is both blunt and cuts to the quick. It needs appropriate identifiers (such describing the audience itself, the geographical location, the groups of individuals, etc.).

Data can be applied to new situations only if these aspects are kept in mind and the purpose is properly and effectively conveyed to the audience.

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