Ganesh Kumar |

Visualization tool for Covid-19 Pandemic Response

Challenge & Selection

Data is crucial for our understanding of the world, and particularly for the emergence of  phenomena such as the COVID-19 outbreak in 2009. A viral pandemic is not a scenario in which  intuition can provide a sense of how the spread is advancing, nor are feelings a sufficient  approach to dealing with and ultimately overcoming such an unforeseen enemy. The tool I used  was the tool of Visualization or more commonly called as the Visual thinking aid for collecting,  analyzing, sharing and ultimately making use of the data needed for the pandemic response in  2009. This collected data needs to be efficiently conveyed to all sorts of individuals and groups,  from lay people to experts and everything in between. Visualizing collected data can make its  dissemination easy, and can help others understand quickly what has taken others so long to  collect and analyze. After all, a picture is worth a thousand words.

Application

I'm not an epidemiologist, and I have no interest in pretending to be one; there's enough of that  going on right now. But as an engineer and an analyst, I can successfully apply this tool to spread  the needed vital information around. John Burn-Murdoch works on data visualization for the  Financial Times. He has recently garnered a following and appreciation for his COVID-19  visualizations, which are exemplars of how quality data visualizations can clearly and succinctly  tell a story. Personally, I have been relying on John's visualizations to understand the outbreak  for quite some time now, and generally refer them several times a day.

Following are the visuals that can be and are useful on day-to-day basis globally:

  Coronavirus mortality trajectories tracker for major countries

  Coronavirus mortality trajectories tracker for individual major countries, compared

  Coronavirus mortality trajectories in subnational regions

  Coronavirus case trajectories for major countries

  Coronavirus case trajectories for individual major countries, compared

A great example of how visualization can help people better understand the underlying data and  succinctly convey a story, can be observed by John’s Covid-19 case trajectories as shown below  for major countries visualization from March 13, 2016 — which charts the cumulative number of  confirmed cases, by number of days since 100th case.

Ganesh Kumar |

What are some helpful takeaways from the above?(Which would have been difficult to observe  without the visual aid)

  The US infection trajectory overtook China's on approximately the 14th day after the US  reported its 100th case

  Turkey seems to currently be on an alarming trajectory, with a doubling rate of less than  2 days

  A number of Asian countries have had early success in flattening their curves

  Italy, once the undisputed epicenter of the disease, seems to be having some success in  starting to flatten their curve as well

  It's easy to see confirmed case doubling rates, at current trajectories, given the overlaid  broken lines, from daily, to every 2 days, to every 3 days, to weekly (US is doubling almost  every 2 days; the UK is doubling approximately every 3 days)

Important thing here to note is that how to effectively use any given tool for example why the use  of log scale and the choice of using absolute numbers rather than population-adjusted rates.

  In the initial outbreak phase, a virus like this spreads exponentially not arithmetically, i.e.  a log scale is the natural way to track the spread

Ganesh Kumar |

  When a person ponders this chart, they’re asking "are these two countries on the same  course", or "how many days till a country X is at Y cases", not "how many pixels represent  100 cases" etc.

  Covid-19 spreads from person to person; it’s not like cancer. It’s exogenous. Generally,  and especially early in outbreak (first few weeks), higher per-capita numbers just mean  smaller country, not anything different about how that country’s dealing with Covid-19.

Insight & Approach

What I have learned from this challenge is how visualization tool can help bridge the gap between  the amounts of data available to how quickly and easily it can be understood. With regards to the  coronavirus pandemic response, this tool will help with resilience and efforts for the future. The  data scientists can rely on this tool to monitor and aid machine learning data sets for  epidemiological response. Areas of high vulnerability around the globe can be strengthened for  future health response systems. Data visualization can also be helpful to prioritize where the  Covid-19 items such as masks or PPE kits are needed.

Thus one cannot simply estimate the impact of data visualization tool can have during this ongoing  pandemic response and how interactive and innovative aids for visualization be used to gather,  integrate and share the data with the world.

(Mayo, 2020)

References  Mayo, M. (2020). COVID-19 Visualized: The power of effective visualizations for pandemic storytelling.

Retrieved from KDnuggets News: https://www.kdnuggets.com/2020/03/covid-19- visualized.html

