Networks and epidemics: when the going gets tough

Massimo Conte is Editorial Coordinator of Complexity Education Project; the italian version of article has been published here

“That’s the network, baby. And there’s nothing you can do about it. Nothing!”

The paraphrase of Humphrey Bogart in the movie “Deadline” is a good start to talk about the spreading of Coronavirus 2019-nCoV, become the main headlines of media around the world in the last weeks. The many networks we are part of (and which make trade and business possible in the globalized world) have expanded both our possibilities and those of viruses: people and information can travel through a network, as well as pathogens.

Looking at the first weeks of a crisis that has rapidly turned into global, we can identify two levels of analysis:

1. the recognition and management of the biological event;

2. the narration and public perception of the same event.

Analyzed these two aspects, we’ll try to understand how the systemic vision of the science of complexity and of networks can help us understand and interpret the global phenomena of which we are active spectators.

1. Facts: the biological epidemic

Propagation networks

Let’s start with a “topological” issue: viruses are spread through vectors, that is, subjects moving in time and space allowing pathogens to pass from a sick person to a healthy one. The transmission of an epidemic therefore depends on the transmission network, i.e. contacts between healthy and infected people. For example, the terrible black plague Yersinia pestis of 14th century took some years to spread from Asia, from where historians speculate began the contagion, up to Europe.

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Credits: wikipedia

The history of the same contagion could be represented as a map where the nodes are the infected cities, and the lines are their connections with other cities.

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Credits: Nature, “Network theory may explain the vulnerability of medieval human settlements to the Black Death pandemic”

The appalling plague epidemic was brought to Europe from today’s Crimea in 1347, probably by Genoese merchants who tried to escape the disease. Later the plague spread to the rest of the continent, favored by the escape of the many who hoped to escape the outbreak.

Things are very different nowadays, thanks to the global interconnection of transport in the world in which we live. As the New York Times shows, in 2020 China has about four times more passengers than 2002, at the time of the spread of SARS. In other words, it is more interconnected. A more widespread and diffused transport network increases the risk of infection, in the case of a virus that is transmitted through personal contact.

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Credits: https://www.nytimes.com/interactive/2020/world/asia/china-coronavirus-contain.html

An interesting reading to understand how outbreaks spread and how it is possible to predict the spread of diseases is “Charting the Next Pandemic. Modeling Infectious Disease Spreading in the Data Science Age”, written (among others) by Alessandro Vespignani, currently Director of the Network Science Institute at Northeastern University in Boston, and great expert in the application of network science to epidemiology.

The book provides an introduction to the modeling of complex computational systems for the global spread of infectious diseases. Recent advances in computational science and the growing availability of real world data are making possible to develop realistic scenarios and real-time predictions about the global spread of emerging threats to health.

Given a set of initial conditions for the local outbreak of a new potentially pandemic pathogen, the chronology of the arrival of the epidemic in each country is mainly determined by the human mobility network that joins different regions of the world.

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Credits: Pastore y Piontti, Perra, Rossi, Samay, Vespignani, “Charting the Next Pandemic”

The picture above is the forecast scenario for the spread of a hypothetical pandemic flu broking out in Barcelona. The central hub is Barcelona airport and the surrounding ones are the main hubs directly connected. The color indicates the time, that is the diffusion speed: the darker the color, the sooner the infection occurs. Hence the importance of a global approach in assessing emerging threats to health, in order to intercept and promptly face the possible evolution of the next pandemic.

Data and time

As for earthquakes, based on the magnitude of which we estimate the damage, also for the management of epidemics data are fundamental for making predictions. Vespignani, this time in “L’algoritmo e l’oracolo” (The algorithm and the oracle in english) explains how for the Ebola virus his team was able to predict the evolution of the epidemic well in advance, using precise km2 maps to elaborate the diffusion predictions. But to do this you need data: many, precise and continuous. Let’s do an example in a completely different field: always using computational models, but having updated and continuous data available, in recent years it has been possible several times to guess the results of the talent shows, based on the debates and hashtags present on social networks.

There are also those who have thought of eliminating a disease by exterminating the vector species, releasing into the environment sterile mosquitoes created in laboratory. This is the objective of the Target Malaria project, the non-profit organization financed by the Bill & Melinda Gates Foundation. However, as Massimo Sandal tells in “La malinconia del mammut” (The melancholy of the mammoth in english) these attempts of genetic editing are controversial, because the complete elimination of one or more species of mosquitoes could lead to unexpected and unpredictable ecosystem consequences: the disappearance of mosquitoes may cause the collapse of migratory birds that feed on them and the species of fish that feed on their larvae, with further effects on fauna and flora of a given natural system.

2. The story: the infodemic

The behavior of the Chinese government in the management of the early stages of the crisis has similarities with what the Russian Communist Party apparatus did in Chernobyl: rigidity and inability to recognize the initial problem, almost until the total official repression of the event, with the illusion to be able to check the information flow; subsequent awareness, with evidence of incredible efficiency afterwards. The scenes of the deserted Wuhan quarantined are very reminiscent of the mass evacuation that took place in Prypiat.

As the Chernobyl TV serie tells, when there is an unexpected crisis event (a “Black swan”, Taleb would say) it is essential to:

  • promptly recognize the event;
  • prepare a response that save the population and mitigate the risk;
  • manage and communicate the crisis.

Giancarlo Manfredi, in his short book Infodemia. I meccanismi complessi della comunicazione nelle emergenze (Infodemic. The complex mechanisms of communication in emergencies in english), tells that although today there are protocols for the management of contagion, in crisis situations even before the health risk, the main one is the possible “infodemic”, that is, the viral diffusion of false, partial or erroneous information able to cause the collapse of relations in civil society.

As is being experienced these days with the Coronavirus 2019-nCoV, together with the viral-biological epidemic (which mainly affected — data updated to 7/2/2020 — almost only Chinese patients, as indicated by the precious daily reports of the World Health Organization) an information epidemic is growing exponentially.

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Credits: WHO, report of 7/2/2020

The global dimensions of the facts have now exceeded the “normal” newsworthiness criteria, conditioned by the proximity of the event: a disaster that involves fewer people but takes place in a geopolitically or culturally close place is more newsable than a similar event that happened more far. These criteria dissolved with the media overexposure of the Coronavirus 2019-nCoV: the perception of the risk due to the transmissibility and impalpability of the virus made China seem closer than ever. Therefore, any issue of territorial sensitivity is lacking, so an event perceived as distant is not a news. But when the geographically distant event is (hyper) perceived as a risk that may have a consequence for the local public, the priority changes.

In the crisis storytelling, the perception of risk has been conveyed by the mass media. Two key aspects emerge:

  • the mass hysteria for the novelty, which we may call the “Welles effect”, in reference to the radio play “The war of the worlds” directed and played by Orson Welles in 1938, with the narration of the alien invasion imagined by H. Wells in its novel (although the “myth” of mass panic caused by radio has been the subject of debate over time);
  • the growing expectation, looking for the smallest signs of the presence of an enemy not yet arrived but deeply feared, which we could call the “Bastiani effect”, referred to the Bastiani Fortress of “Il Deserto dei Tartari” (The tartar step in english) written by the italian writer Dino Buzzati, within the which the main character Giovanni Drogo waits for the enemy long told but never seen before.

In the redundant and dramatic media storytelling of the weeks between January and February 2020, we have heard of a global pandemic now inexorable and unstoppable. The fear of the event (amplified by overexposure in the media) precedes the experience of the event itself, which is currently still statistically marginal in Europe (at 7/2/2020 only 270 cases out of 31481 were found outside of China).

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Credits: WHO, report of 7/2/2020

It emerges the issue of the disperception of an event about a topic of which people don’t know enough. The italian scientific journalist Barbara Gallavotti in her book “Le grandi epidemie, come difendersi. Tutto quello che dovreste sapere sui microbi”(The great epidemics, how to defend yourself. Everything you should know about microbes in english) reminds us that microbes usually evolve faster than our effort to fight them, and that historically as humans we have always lost. Only in the last century have we developed tools that can protect us from infections that exterminated our ancestors: vaccines and antibiotics.

Over the centuries, many times Europe brought the contagion where its conquests were spreading. As Jared Diamond explains in Guns, Germs and Steel, in 16th century the Amerindian populations were exterminated by the viruses (smallpox, typhoid, flu, diphtheria, measles) brought by the conquering Europeans: together with technological knowledge of firearms, epidemics gave them an unbeatable advantage.

3. The complex vision: let’s try to understand better what we are talking about and how we can interpret facts

Networks: when the going gets serious

Let’s take a step forward to get to the central theme of this article: the need for better divulgation and knowledge of complex systems and networks. Coronavirus 2019-nCoV is a virus that has made a Spillover, passing from animals to humans. Being a “new” virus for humans, it can spread through the network of subjects “susceptible” to contract this respiratory infection.

How does actually a virus spread? How can we limit it? What strategies can actors responsible for public health adopt? Let’s see together some games and simulations to understand how viruses attack (and can be fought) through a network-based approach.

The no-vax approach, that caused social and political disputes in recent years in many countries, is now crushed by the spread of global events, before which it becomes difficult to support the freedom to decide whether to get vaccinated or not, based on individual risk / benefit. The infected people of Wuhan would probably have little doubt about it, if it were possible to have a vaccine available (for which it could take many months instead).

VAX! is an on line game on epidemic prevention. The displayed network is that of possible people at risk of contagion. Each node represents a person; each line is the connection between two people who come into contact. In other words, the social network of real encounters of a subject.

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Credits: game VAX!

In the game (which we highly recommend to try) you test yourself as a healthcare manager with constraints on resources and time. You can administer five doses of vaccine, that is, eliminating five nodes from the network of subjects at risk; in other words there are five moves ahead of the outbreak. Once the virus is found, it will be a struggle against time: the speed of propagation through the networks will risk making the virus uncatchable. Only if you have moved in advance, knowing the properties of the networks and identifying the most risky nodes, you will be able to contain the damage.

The interactive “I herd you. How herd immunity works” help to understand the mechanisms underlying vaccinations; it’s one of the many interactive pages of Complexity Explorables, a website providing models to understand the behaviour of complex systems.

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Credits: Complexity explorables

Herd immunity is an emerging property of a network system, thanks to which an unvaccinated individual (perhaps because he cannot be vaccinated) can still be protected if he is part of a group with a sufficiently high rate of vaccinated individuals. Because if the people he comes in contact with are vaccinated, it reduces his chances of coming into contact with the virus. The simulations allows to:

  • see the evolution over time of a virus spreading in a group (on the left in the picture above);
  • set the transmissibility rate and the spread rate of the vaccine (on the right).

The simulator is dynamic, in real time you can change the parameters and see what happens. Thus the concept of epidemic spreading becomes tremendously concrete and more understandable.

Finally, to experience in person and together with other friends what it means to fight a global pandemic, you can play Pandemic: it is a cooperative board game, in which all participants are part of a team called to save humanity from four global epidemics.

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Picture of Pandemic game board

The game board shows a map of the world, which could remember the most famous Risk game: in this case, however, understanding and using the properties of the networks to your advantage can make the difference between life and death. In fact, in the most critical moment of the game, an outbreak of an epidemic can break out in a city, which will then spread to the cities connected with it. One of the curiosities of the game is that players do not play against each other, but together they reflect and agree on the best strategy to eradicate the viruses identified.

A similar version, but with the opposite objective, is Plague Inc., in which the player’s aim is to create an epidemic that destroys humanity, working on pathogens with different abilities. Over time, for this reason, the game has been the subject of numerous criticisms. Curiously, in the last few days, with the explosion of the Coronavirus, became again one of the most downloaded games (despite being on the market for 8 years). It has opposite purposes compared to the previous Pandemic, but a common knowledge base remains: the understanding of how networks work.

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Credits of picture

Data, science and complexity

The information circulated since the detection of the Coronavirus 2019-nCoV has been many and in part too tied to emotions. Fortunately, many excellent examples of data journalism were also published in this period, useful for understanding data.

The Le Monde’s reportage “Coronavirus, Zika, Ebola… : quelles maladies sont les plus contagieuses ou les plus mortelles?” provides an illuminating graph in which the contagiousness and mortality rate of many of the most known viruses and bacteria are related: together with Coronavirus we find SARS, but also anger, plague, measles, chicken pox.

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Credits of picture

The New York Times, in the article How Bad Will the Coronavirus Outbreak Get? Here Are 6 Key Factors, shows in an animation the propagation of the virus, in the case of a medium-high spread rate (if every 5 infected people, in turn, they infect another 2.6).

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Credits of picture

This recalls the famous degrees of separation, made famous by the theory of the small world by the psychologist Stanley Milgram, according to which many complex networks are configured so that any two nodes can be connected by a path consisting of a relatively small number of connections.

Another example of the degrees of separation is the number of Kevin Bacon, who maps the number of jumps necessary to connect the American actor with any other actor who has shot a film (here a brief explanation). Those who want to experience firsthand how many degrees of separation are between Hollywood actors, will discover that surprisingly a good part of the mapped actors (for example the italian actor Roberto Benigni in the example below) have a Bacon number equal to 2: that is, they have acted with an actor who in turn starred with Kevin Bacon.

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This digression aims to underline a property of many networks such as Social Networks or the World Wide Web: a very high interconnection between the elements, which makes it possible in a few leaps to reach even a node apparently very far from us.

Fallen into the web or without net?

In a nutshell, the communicative and emotional dynamics manifested during the first weeks of the spread of Coronavirus seemed very close to the atomic disaster psychosis in pure cold war style or Doomsday Clock, the metaphorical clock that measures every year what is missing at the end of the world. For the record, for 2020 it is set at 23:58:20, that is, one minute and forty seconds at the end of the world; the curious aspect is that the motivation for this concern is related to nuclear rearmament and climate change. Probably this estimate made at the beginning of 2020, before the explosion of the Coronavirus, today would undergo a further downward estimate.

Viruses have existed on earth long before man himself, and we have to live with it. We have seen how in a globalized world, everything spreads faster. It becomes essential to have greater awareness of the basic principles of complex networks, studied by Network Science, which has become more and more central over two decades to understand biological, physical and social phenomena.

The spread of Coronavirus made clear the concept of “butterfly effect” developed by the mathematician and meteorologist Edward Lorenz, and known to the general public in the formula “the flapping of a butterfly’s wings in Brazil can be enough to cause a tornado in Texas”. The metaphor explains how small variations in the initial conditions can generate large effects in a non-linear deterministic system (such as the weather, but we could also put the economy), making it difficult to make long-term forecasts.

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Picture: Lorenz attractor, a system of ordinary differential equations with chaotic solutions for certain parameter values and initial conditions; credits

The butterfly effect of our story could be a new local virus that turns into a national health crisis (for now) with global economic and political effects. From the Wuahn fish market to international stock exchanges, in just a few days. Effects of interconnected systems on different levels of scale, in which local crises make global fragility visible.

The Strategic Intelligence website, developed by the World Economic Forum, provides an interdisciplinary mapping of phenomena on a global level. Among the many precious maps, the one dedicated to “global health” shows as connected node also “Pandemic preparedness and Response”, that is the preparation and the ability to respond to a pandemic.

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Credits

Also in this case we have a network of interconnected and interdependent phenomena: global health passes from prevention and prepared reaction to the outbreaks of diseases and epidemics.

In conclusion

Pathogens are transmitted from one person to another; our interactions are the social network through which germs travel. But the same network of contacts can be used to map the path that a virus will make before this happens.

Essentially everything we’ve built around us is a network. This awareness can lead us to understand how to manage and change the world around us. Create predictive models, starting from tracking the paths taken by viruses, to predict where, how and when epidemics will erupt. Network science is (still) at the beginning of a revolution: recognizing patterns and emerging behaviors in a biological, social or technological system. Many of the systems surrounding us are complex systems such as cells, the brain, society, the Internet. Millions of connected elements, whose interactions allow them to function. Recognize the order emerging from apparently random behavior. The predictive power made possible by Network Science applied to epidemiological models could help fight both this ongoing pandemic and the next ones.

Once we understand the mechanisms of spreading of (biological) epidemics and (communicative) infodemics, what types of actions are possible to stop (or at least limit) the catastrophe?

What we can have is a prudent attitude: take seriously (both the virus and the information arriving) but without dramatizing more than necessary. The outbreak propagates according to network mechanisms; being aware that adequate quarantine mechanisms have been put in place so far at international level, we can (for now) be confident that the risk of large-scale global spreading is extremely low, in order to talk about Pandemic.

Equally, we can be infected by the infodemic of inaccurate, incomplete or false information that can amplify the effects of a problem, if we are not careful. In this case, we have the opportunity to “get vaccinated” through the use of critical thinking: verify the origin of the news that arrives and increase the number of our sources, trying to understand what mechanisms are behind the propagation. The same goes now for Coronavirus, but until last month it was about climate change (temporarily out from the mass media “radar”).

Although the number of infected could still be the tip of the iceberg, the Coronavirus epidemic will probably come back under control in a few months (as Sars, Bird flu and H1N1 have passed in past years). Similarly, we will have to get used to the continuous waves of infodemics, that is, waves of false news (or rather news that agree with the subjective point of view of a specific niche) spreading in our on line life; but which can then have consequences in off line life. Such as racist and xenophobic behaviors.

Ironically, it may be easier to cure the epidemic outbreak. For the second one, the vaccine lies in understanding the complexity of these global phenomena and accepting a systemic vision of an interconnected world in which (except for total isolation) it is very difficult to be outside invoking closed borders.

Editorial Coordinator of Complexity Education Project; Digital Learning Manager. Explorer in complexity, data visualization, network science

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