Article: Tuesday, 8 December 2020
The general discussion on the COVID-19 pandemic is closely connected to the interpretation of data and statistics. At the same time, there is evidence that statistics are often not well understood – or can even be misinterpreted – which may result in less well informed and potentially inappropriate decision making. New research by Prof. Daniel Metzger and Dr Mikael Paaso from Rotterdam School of Management, Erasmus University (RSM) and Dr Vesa Pursiainen from the University of St. Gallen studies the influence of statistical literacy (the ability to understand and reason with statistics and data) on risk perceptions and willingness to comply with government-imposed restrictions like social distancing.
Given the global rise in new COVID-19 cases and the lack of effective medical treatments, current attempts to control the spread of the virus rely on non-pharmaceutical interventions (NPIs), such as social distancing, mandatory facemasks, school closures, large-scale lockdowns of populations, or closing borders. The success of these NPIs often depends greatly on voluntary compliance by the population. Moreover, now that vaccines have been successfully developed and approved, it is likely that in most countries vaccination will be voluntary, implying that compliance will still be an important part of bringing down the number of infections.
Much of the data and statistics on infection and mortality rates, or for estimating undetected cases, are difficult to understand as well as estimate accurately. At the same time, anecdotal evidence suggests that parts of the population – including politicians and journalists – have difficulty interpreting key data and drawing valid conclusions from them. For example, commentators have frequently expressed surprise at the rapid spread of the virus despite it being completely consistent with exponential growth. A frequent argument against further restrictions in the autumn was that even though case numbers were rising rapidly, hospitalizations remained low, with many objectors being apparently unaware of the lag between the number of infections and hospitalizations. When the number of infections increases expotentially, there is a risk of overwhelming the capacity of the health system.
The findings suggest that individuals' estimates of the risk of COVID-19 infection and the way they behave with respect to social distancing systematically differ depending on their statistical literacy. People who are more statistically literate react more strongly to new information about infection numbers in their locality by adjusting both their estimates of risk and their corresponding behaviour. They are also more likely to adhere to social distancing, independent of the local infection risk. This is notable given that more statistically literate individuals are generally less concerned about the risk of infecting themselves with the virus or of getting seriously ill. They are, however, more concerned about the risk of infecting others or their loved ones becoming ill. More statistically literate people are more likely to comply with a curfew because they want to avoid infecting more vulnerable people, whereas less statistically literate people are more likely to comply out of fear of punishment.
These findings suggest that statistical literacy is associated with a better understanding of the threat posed by the virus, as well as with the ability to follow changes in the current situation and to more accurately incorporate new information in the formation of expectations. It also seems that a better understanding of the risk translates into a more acute sense of protecting others from infection. This might be an important observation in the efforts to get a sufficient part of the population to comply with non-pharmaceutical interventions, even when the mortality risk for most people is substantially lower than it is for the elderly and other high-risk groups.
Voluntary vaccinations may become important to contain the virus in the future. Using an earlier wave of the LISS panel, the study shows that more statistically literate people generally consider flu vaccinations more important. These people also have a higher level of confidence in science and in healthcare. These results, while somewhat anecdotal in the context of COVID-19, might prove important for the uptake of a potential vaccine, especially one that has been developed with a highly condensed timetable.
There are several mechanisms through which statistical literacy might affect risk estimates and behaviour. It may directly affect the ability to interpret available data and statistics. It may also help to acquire and process relevant data. Consistent with these ideas, the researchers find that less statistically literate people are less satisfied with communication by the government during the pandemic, as well as with media and science. This underscores the importance of group-specific communication about the pandemic.
Overall, the results are consistent with the view that governmental efforts to control the virus using mobility restrictions and other non-pharmaceutical interventions are likely to be affected by how well people understand the actual levels of risk that the policies are based on, as well as by how information and policies are communicated.
Therefore governments or health organisations might be able to increase the effectiveness of communication, measured by overall compliance with their recommendations, by focusing more intensively on underinformed groups and by using more targeted communication strategies.
More effort is needed to convey statistical information in an efficient way and to explain reasons for specific governmental measures or recommendations.
The study suggests three tips:
Communication strategies should be group-specific
There should be a bigger focus on communicating to less statistically literate people
It appears to be important to explain relevant statistical concepts in more detail and increase awareness of common mistakes and fallacies.
The paper is currently available as a working paper under the title The Role of Statistical Literacy in Risk Perceptions and Behavior During the COVID-19 Pandemic
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