COVID-19: Tangled in Uncertainty and Fear

COVID-19: Tangled in Uncertainty and Fear

20.2.2020

[This article has been originally published in Spanish in El Periódico]

 

The Danish physicist Niels Bohr used to say: “It is difficult to predict, especially the future.” The incapacity to predict how the COVID-19 epidemic will evolve has led to the suspension of the Mobile World Congress in Barcelona. This is a clear sign that the scientific evidence and communication efforts by experts and authorities are proving insufficient for an effective risk management. It is ironic that a high-tech sector such as mobile telecommunications has preferred to stay home, when never before have so many people had access to such an amount of real time information on an outbreak and after the authorities of the most affected country, China, have taken the most drastic public health measures in the last 100 years. The result is a global epidemic of mistrust, a prelude to fear and even to open conflict.   

If we want to understand what is happening, we need to put aside our reductionist view- centred on the linear relationship between message and response- and adopt a systemic vision based on networks and connections, much more appropriate for the analysis of global complexity

If we want to understand what is happening, we need to put aside our reductionist view- centred on the linear relationship between message and response- and adopt a systemic vision based on networks and connections, much more appropriate for the analysis of global complexity. Barabási and Albert, among other scientists, introduced over 20 years ago the concept that “the rich get richer”, an analogy to explain the growth of networks in which the most popular or influential individual establishes a greater number of connections, thereby amplifying his or her recognition and influence.

How is this paradigm of the connected society related to the dynamics of the global response to the COVID-19 epidemic? In his book entitled Complex Networks (2009), the director of the Complex Systems Laboratory at the Pompeu Fabra University, Ricard Solé, describes the spread of virus and epidemics from a complex systems analysis. His observation that stopping transmission requires disabling nodes with the highest number of connections, rather than fighting the virus, is particularly relevant. In other words, we must identify and protect the most active and connected nodes if we want to protect the system as a whole.

Family walking at Macau's Senado Square wearing protective face masks due to coronavirus (Covid-19) outbreak. Photo by Macau Photo Agency on Unsplash.

The news on the unfolding of the epidemic, the new scientific knowledge, the response by politicians and health authorities, the positioning of multiple economic and social agents, and many other historical and cultural factors behave as the elements of a complex but fragile system. In it, uncertainty and mistrust become a highly transmissible agent, spreading at great speed through a myriad of highly influential nodes, those with the highest number of connections. Their thorough characterisation, drawing from big data and the analysis of contents and global communication actors, would be a valuable initiative to identify where it would be most effective to inoculate elements that generate a sense of security and trust, thereby stopping the spread of uncertainty and fear. This has clear implications for the analysis of governance models, including the case of China.

The characterisation of influential nodes, drawing from big data and the analysis of contents and global communication actors, would be a valuable initiative to identify where it would be most effective to inoculate elements that generate a sense of security and trust

Viruses, outbreaks and pandemics are here to stay, and will continue to shape human evolution. It is only with our collective intelligence and cooperation, and a sense of transparency and solidarity with other countries, that we will better understand our interdependence and respond in a more effective way.

More information

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Photo: Hello I'm Nik in Unsplash