COVID-19 Deniers Explained Through Diffusion and SIR Model
Link: https://www.wsj.com/articles/covid-19-disbelief-saddles-health-care-workers-with-another-challenge-11606991401
The COVID-19 pandemic has changed the lives of people worldwide. While millions are suffering from the disease there is a considerable amount of people who deny its existence as a whole. Despite scientific explanations, it is still difficult to gain a consensus on how to combat the disease. The article, “Covid-19 Disbelief Saddles Health-Care Workers With Another Challenge” shows the traumatic effects of denying COVID-19. Despite hospitals hitting record-high numbers, a recent study from the University of South California showed that only 4.6% of respondents strongly agree that wearing a mask will help them slow down the spread. On an even more alarming note, a Gallup Panel survey of 2,985 adults found that around 42% of Americans preferred to not get vaccinated later this year. Moreover, it is a stressful time as misinformation is continuously shared on social media and family groups. People have reported to remove themselves from friend groups to prevent hearing a version of the truth they do not agree with. The root of this issue may have stemmed from the polarizing views provided by politicians around the country. Some say that this virus was created to influence the 2020 election and others, such as Anthony Fauci, say that this virus should be taken as seriously as possible.
At the core, COVID-19 is a disease of misinformation. There is information spread around America with varying degrees of accuracy. Hence, various clusters of people have developed their own beliefs. The most common view supporting COVID-19 being a hoax is the belief that COVID-19 is the same as the flu. In this post, we will debunk the belief that COVID-19 and the flu are the same and discuss the nature of information diffusion.
To begin, we need to understand why COVID-19 is not the same as the flu. Firstly, the death rate and symptoms are much worse than the traditional flu. Meaning that one’s chance of survival is lower with COVID-19. Secondly, following the SIR model, the difference between COVID-19 and the flu can be shown. Starting with a patient 0, the disease starts to spread with each person patient 0 infects. There are 2 important variables k, the number of people who interact with an infected person, and p, the probability of infection. The R0 (R-naught) is the measure of how a disease spreads. This is calculated from k*p. The higher the R0 the more invasive the disease. The flu’s R0 is 1 and COVID-19’s R0 is 2.5. Hence, COVID-19 is much more infectious than the flu. Therefore, using the SIR model, these 2 diseases are not the same.
Moreover, from the perspective of diffusion, it makes sense why certain people would deny the existence of COVID-19. Each social group can be thought of as a cluster of nodes. The threshold theory states that there needs to be a certain number of people in one’s social circle that believe in an idea for that idea to spread. Hence, it is oftentimes hard to spread through dense clusters where everyone does not believe in the idea. The threshold for each community is different. For example, the threshold is lower for college campuses and states like New York. However, certain states in the middle of the country may not believe the existence of the disease. Hence, they have a higher threshold. Simply explained, these states are considered dense clusters where outside information cannot penetrate their current information bubble. Overall, this post has proved that COVID-19 is not the common flu and why it is hard for information to penetrate certain communities.