Decoding the Challenges of Data Literacy: Lessons from COVID-19 Vaccine Trials

Abstract

Covid-19 Vaccine Trials Are a Case Study on the Challenges of Data Literacy article. Langhe (2020) analyses Pfizer/BioNTech press release on covid-19 from three perspectives. Big data is often smaller than it appears, two on how precision can undermine the accuracy and finally on the need to distinguish between prediction and post-diction. Langhe argues that it is easy and very dangerous to misinterpret big data, especially when the report comes in percentages rather than figures through the lenses of big data are often smaller than it appears. Citing the example of the vaccine efficacy reported in Nov 2020, the author confirms that though the sample size involved over 43000 participants, the over 90% vaccine efficacy involved only the number of participants who got infected with covid-19. The author emphasizes proper calculations to ascertain how the vaccine efficacy percentages became realized. The over 90% efficacy involved 8 out of the 94 participants who contacted and prevented the virus. He, therefore, calls for consideration of huge sample sizes to allow for results that express greater confidence in the effectiveness of the study under consideration as the smaller sample size in any study undermines the confidence of the results efficacy. The second perspective emphasized how precision can undermine accuracy, citing a great example from the November 2020 vaccine efficacy report. As this report announced over 90% of efficacy, later releases on Sputnik V vaccine involving 40 000 volunteers and Moderna vaccine involving 30000 participants announced 92% and 94.5% efficacy. The change of language by offering exact figures/precise percentages proves more appealing, thus undermining the accuracy of the initial report. On this note, the author emphasizes the need to be more careful with data interpretation to make the right decision in the long run. According to Langhe, most data presentations tend to sacrifice accuracy for precision, thus requiring the target...