Wait, did a ‘blood plague’ in World Of Warcraft actually help scientists better model COVID?

Long before COVID, in 2005, the World of Warcraft game developers accidentally introduced an extremely virulent, highly contagious disease into this game which then spread to infect the entire fantasy world and caused a virtual pandemic.

As remote as it may seem from what happens in the real world, the spread of this virtual disease seemed to have potential relevance to understanding real-world epidemics.

Disease modeling has played a crucial role during the COVID pandemic in helping to anticipate the spread of an entirely new infectious disease among the population.

Infectious disease models use mathematical equations to describe how infectious diseases, humans, and the environment interact. We can then assess what is likely to happen if we let an epidemic run its course or try various public health intervention options to see their effect on transmission.

This approach allows us to peer into an uncertain future to assess the likely impact of control strategies on disease outcomes.

World of Warcraft and the plague of corrupted blood

In the online game World of Warcraft, the disease that was introduced and spread widely throughout the virtual world was called Tainted Blood.

This introduced disease was meant to be limited to a particular area of ​​the virtual world, as a “debuff” spell used by the dungeon “boss” Hakkar the Soulflayer, to pose an additional challenge to players. When facing the boss, players were affected by the spell that would take their lives periodically.

However, to the surprise of the game developers, the characteristics of this virtual world, the nature of the introduced disease and the unexpected behavior of the players led to a rapid spread of this infection to the game in general. Players unknowingly spread the infection to their animal companions, who were then able to infect other players in the wider game.

The developers did not predict that panicked players would travel great distances to densely populated areas and spread disease there. Some players displayed altruistic behavior, came to the aid of their friends, and became infected. The disease spread widely and rapidly.

There were also a number of people who intentionally spread disease for no apparent reason. A large-scale pandemic occurred throughout the game, with high rates of infection and death.

Given the extent to which players inhabited their virtual characters, this phenomenon led some researchers to speculate that playing infectious disease outbreaks might be a way to gain insight into human behavior during a pandemic.

Data derived from observing players’ actions in the virtual realm in response to an introduced virtual disease threat could be incorporated into real-world disease models, they suggested, to better explain the unpredictability of human behavior.

In fact, many of the behavioral drivers of infectious spread identified in the gaming outbreak have also played a role in the spread of COVID.

The key issue is that despite the sophistication of disease models, the biggest source of uncertainty in these models comes from trying to account for human behavior.

Disease and COVID modeling

The COVID pandemic has highlighted how complex and varied our responses to infectious disease threats are. Differences in social cohesion, trust in governments, and political priorities can drive these responses.

Some high-income countries, such as the United States and the United Kingdom, which were expected to be well positioned to respond to the pandemic, performed poorly. Other low-income countries, such as Vietnam and Thailand, performed exceptionally well despite having fewer resources. To make things even more complex, as the pandemic continues to unfold, public perceptions have also been changing.

So how do we collect the data needed to better model human behavior?

Since the beginning of 2020, many countries have implemented real-time behavioral surveys as a way to understand attitudes and behavioral response to the pandemic, including cooperation with social measures ordered or recommended by authorities.

What have we learned about COVID from World of Warcraft?

Have virtual epidemics been used to inform infectious disease models and make them more “realistic”?

Despite some initial enthusiasm about using observed player behavior in virtual fantasy worlds to improve epidemic models, we have not seen such data used in any meaningful way.

Despite the parallels between player interactions in virtual worlds and the real world, online behavior varies significantly and may still be too far removed from reality to be of any practical use. In particular, the potential for unlimited experiences in online gaming is very different from the real world. Despite the theoretical interest, the idea hasn’t really taken off.

While behavioral data from virtual worlds may not be relevant enough to inform real-world disease models, the need to better predict human behavior remains very important. The pandemic has shown us how unpredictable our responses are.

An excellent example of this was the rush to stockpile toilet paper. Nobody would have foreseen this phenomenon before the pandemic, and it was totally irrational, but it was replicated around the world. While this is a somewhat obscure example, what stands out is the unpredictability of human behavior. There is no doubt that if we can better understand human behavior and include it in our disease models, we will be in a better position to predict disease outcomes and the impacts of public health interventions.

Unfortunately, in the real world we don’t have the luxury that the World of Warcraft game developers did. When they couldn’t stop the spread of the tainted blood disease, they simply restarted the game to end the pandemic and return to normal life. If only!The conversation

Jodie McVernon, Doherty Professor and Head of Epidemiology, University of Melbourne and Hassan Vally, Associate Professor, Epidemiology, Deakin University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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