Coronavirus data and pandemic

We end the month of November, the month dedicated to data, with a recommendation. This is an article written in four hands by ICT journalist Karma Peiró, and Ricardo Baeza-Yates, who is a Ph.D. in Computer Science and Director of Data Science at Northeastern University in Silicon Valley.

Entitled ‘Seven Lessons to Fight Pandemic Data’, the authors list what has not been done well enough regarding the pandemic and the treatment and communication of data. As they say, “a country’s democratic measure is measured by the transparency of its data.” Below is a short summary of each, and we invite you to consult the original article by clicking on the title.

1. Data collection errors: Without data it is not possible to understand how the pandemic is progressing, but without knowing how it has been obtained either.

2. Inaccuracy in the data: Any analysis is inaccurate and any conclusion must be considered very carefully.

3. Chaos to account for deaths: What is the cause of death if a person had a previous illness and dies of COVID-19?

4. Temporal paradoxes: The pandemic is a very dynamic process that depends on many factors, starting with civic education.

5. The importance of transparency: The transparency of data is a reflection of the level of democracy of each government and the trust of citizens. Hiding data only creates mistrust and political problems.

6. Privacy in times of pandemic: Is data privacy the price we have to pay to survive a pandemic?

7. The obsession to compare: If the criteria are different from one country to another, it is very difficult to compare them, even if they measure the same.