#TechTalksWithMelwyn – Can Good Looks Save The World From COVID-19?
Surprised by the title? Don’t be. For every superhero movie that you have watched, good looks seem to be the norm, and today on #TechTalksWithMelwyn we really want to know if good looks are enough to save the world from COVID-19!
We all expect the world to come together to fight COVID-19, but why haven’t we heard of some Avengers or Justice League being assembled to save the world (starting with New York of course). Turns out, the first thing that comes to mind is the world’s governments; who are currently preoccupied with anything from containment, re-opening the economy, threatening others for medicines & cutting WHO funding, to altogether denying COVID-19 (Brazil, Nicaragua, Mexico). In all fairness, governments around the world are doing their best to share their strategies and findings within their localized groups such as OECD in the EU and NATO, and by extension to their allies and a larger majority of UN members.
So will that gorgeous girl next door or the Clooney look-a-like from down the street save the world from Corona? To be honest, I don’t know but good-looking data will definitely help out. Data Visualization, in its simplest form, is the graphical and pictographic representation of information using data. Scientists around the world are teaming up to share visualizations and datasets that will help us understand and sequence the COVID-19 genetic structure so we can identify either a cure or a vaccine. Open Science Prize winners of 2017, Nextstrain.org, have created an open-source toolkit that enables bioinformatics and visualization and allows researchers to weave a narrative around the patterns in the data. The specialty of this method is that you can see your visualization update as you read the text that describes this dataset.
Previously reserved for executive reporting and news channel broadcasts, visualization has worked its way into the scientific community to better represent excruciating details that were involved in a research paper or thesis. Tools such as Tableau, Qliksense, and R Markdown are simplifying the process of creating visualizations to such an extent that anyone with basic computer skills can create their visualizations and graphs.
A still from the animation, above, shows how users can have an interactive experience with the data and visualize the evolution of diseases. Nextstrain allows medical researchers from around the world to share open-source datasets & visuals to collaborate and potentially mimic the successes of South Korea, Kerala (India), and Germany. This method of data sharing has 4 distinct advantages over existing practices:
- Scientists and researchers present ideas and inferences on data that are a part of lengthy whitepapers and must be peer-reviewed before being published by any journal. While this process can take years, sharing the datasets with visuals is a much quicker method to share initial findings and metrics.
- Since most medical research requires random sampling across a large population, researchers can collaborate and have a global footprint almost immediately.
- Using open-source data, researchers can avoid the political and bureaucratic hurdles of getting access to reliable data in a timely fashion.
- It overcomes the unwillingness of individuals to share their data with government agencies and instead entrust it to scientists who are accustomed to working with anonymized data
While the cure to COVID-19 may still be in the works, data visualization helps solve the two main problems that we currently face – capital and skilled resources. In the near term, visualizations help engage donors and raise capital for expensive research and FDA approvals that allow more scientists to keep their work open-sourced and free to use. In the long term, visualization can help make certain fields like epidemiology seem “sexy” enough to attract more students and research PhDs so we can stop the next epidemic before it becomes a pandemic. Have you ever had to explain large amounts of data or numbers to a group? Tell us in the comments how you managed to get your point across.
