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By: Lucas Poulissen, Project Manager
2020 started a lot different compared to other years. In Wuhan, a city in mainland China, a virus had spread uncontrollably and became a global pandemic marked by a turbulent period of government restrictions and travel bans. During this crisis, media coverage on the SARS-CoV-2 virus did not stop and became part of our daily lives. Data and data visualization played a central role in this process. In this article, we will go over the role of data in the battle against Covid-19 and the perception of truth.
It would be wrong to say that the virus is gone, but the impact of it became less over time. People get used to living with it and vaccinations made it possible to take up our lives again. In the background, data on the virus such as number of cases, deaths, hospitalizations, and vaccination coverage are omnipresent and dictate decision-making on the highest level. Many countries introduced parameters such as daily hospitalizations, Covid intensive care patients and infection trends, all of them functioning as data points/variables.
Every upside has its downside. Although data can be a means for actionable insights and process optimization, it is also a source for fake news. The way data is collected, represented or interpreted can cause more harm than good. Some people speak of this as the ‘post-truth digital era’. No control over the digital world makes it possible to widely spread false information with a single click of a button. Throughout the Covid crisis, various politicians used this to reignite polarization and provoke disruption in the political landscape.
Collecting representative data can be a difficult process from time to time, let alone global standardization of data definitions. A clear example that comes to mind is the data reported on SARS CoV-2 deaths in Belgium. The data was always relatively high when compared to other countries in the world followed by a negative image of the Belgian health care sector. However, if we look at this in detail, Belgian authorities made the decision to count all deaths that could be the consequence of Covid-19, resulting in a high number of deaths. In this way, the death of an old person was often linked to Covid but could not be checked due to a lack of testing capabilities. Other countries only counted the people where Covid was found and was a direct cause of death.
Be critical and cautious when interpreting data that is presented to you. Questions that may help are ‘What is the action behind this dashboard/data?’ and ‘What is the source behind this data?’.
At Modis our technical teams work together with our business analysts towards the common goal of representing accurate & meaningful data via data analytics and dashboards, to deliver actionable insights and serve business needs.