In a Pandemic, Migration Away from Dense Cities More Effective than Closing Borders

During the COVID-19 pandemic, closing national borders and borders between states and regions has been prevalent. But does it help? In a paper in Chaos, researchers decided to put this hypothesis to the test and discover if confinement and travels bans are really effective ways to limit the spread of a pandemic disease. Specifically, they focused on the movement of people from larger cities to smaller ones and tested the results of this one-way migration.

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Smart Devices to Schedule Electricity Use May Prevent Blackouts

Power plants generate electricity and send it into power lines that distribute energy to nodes where it can be used. But if the electricity load is more than the system’s capacity, transmission can fail, leading to a cascade of failures throughout the electric grid. In the journal Chaos, researchers show demand side control may be an effective solution to stabilizing the reliability of power grids that use a mix of energy generation sources.

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Random Effects Key to Containing Epidemics

To control an epidemic, authorities will often impose varying degrees of lockdown. In the journal Chaos, scientists have discovered, using mathematics and computer simulations, why dividing a large population into multiple subpopulations that do not intermix can help contain outbreaks without imposing contact restrictions within those local communities. When infection numbers are high, random effects can be ignored. But subdividing a population can create communities so small that the random effects matter.

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Interactions Within Larger Social Groups Can Cause Tipping Points in Contagion Flow

Contagion processes, such as opinion formation or disease spread, can reach a tipping point, where the contagion either rapidly spreads or dies out. When modeling these processes, it is difficult to capture this complex transition. In the journal Chaos, researchers studied the parameters of these transitions by including three-person group interactions in a contagion model called the susceptible-infected-susceptible model. In this model, an infected person who recovers from an infection can be reinfected.

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Finding Right Drug Balance for Parkinson’s Patients

Parkinson’s disease is most commonly treated with levodopa, but the benefits wear off as the disease progresses and high doses can result in dyskinesia, which are involuntary and uncontrollable movements. To better understand the underlying reasons behind these effects, researchers created a model of the interactions between levodopa, dopamine, and the basal ganglia, an area of the brain that plays a crucial role in Parkinson’s disease. They discuss their findings in the journal Chaos.

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COVID-19: Second Wave for Some; Others Remain in First Wave

As the COVID-19 pandemic continues, some locations have experienced decreasing numbers of cases followed by an increase. In the journal Chaos, mathematicians report a method to analyze these numbers for evidence of a first or second wave. The authors studied data from all 50 U.S. states plus D.C. for the seven-month period from Jan. 21 to July 31. They found 31 states and D.C. were experiencing a second wave as of the end of July.

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Betrayal or Cooperation? Analytical Investigation of Behavior Drivers

When looking at humanity from a macroscopic perspective, there are numerous examples of people cooperating to form various groupings. Yet at the basic two-person level, people tend to betray each other, as found in games like the prisoner’s dilemma, even though people would receive a better payoff if they cooperated among themselves. The topic of cooperation and how and when people start trusting one another has been studied numerically, and in a paper in Chaos, researchers investigate what drives cooperation analytically.

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Why Does COVID-19 Impact Only Some Organs, Not Others?

In severe cases of COVID-19, damage can spread beyond the lungs and into other organs, such as the heart, liver, kidney and parts of the neurological system. Beyond these specific sets of organs, however, the virus seems to lack impact. Ernesto Estrada aimed to uncover an explanation as to how it is possible for these damages to propagate selectively rather than affecting the entire body. He discusses his findings in the journal Chaos.

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Can Social Unrest, Riot Dynamics Be Modeled?

Episodes of social unrest rippled throughout Chile in 2019. Researchers specializing in economics, mathematics and physics in Chile and the U.K. banded together to explore the surprising social dynamics people were experiencing. In the journal Chaos, the team reports that social media is changing the rules of the game, and previously applied epidemic-like models, on their own, may no longer be enough to explain current rioting dynamics.

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Twitter Data Reveals Global Communication Network

Twitter mentions show distinct community structure patterns resulting from communication preferences of individuals affected by physical distance between users and commonalities, such as shared language and history. While previous investigations have identified patterns using other data, such as mobile phone usage and Facebook friend connections, research from the New England Complex Systems Institute looks at the collective effect of message transfer in the global community. The group’s results are reported in the journal Chaos.

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Countries Group into Clusters as COVID-19 Outbreak Spreads

Mathematicians based in Australia and China have developed a method to analyze the large amount of data accumulated during the COVID-19 pandemic. The technique, described in the journal Chaos, can identify anomalous countries — those that are more successful than expected at responding to the pandemic and those that are particularly unsuccessful. The investigators analyzed the data with a variation of a statistical technique known as a cluster analysis.

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Brexit’s Effect on Research Networks: Lower Local and Global Efficiency, Reorganization of Research Communities

Brexit has affected trade and security, but scientists wanted to know how it might also affect the EU Framework Programmes for Research, known as Horizon 2020. In this week’s Chaos, authors examined a network of 19,200 research organizations to determine how removing U.K. organizations affects three Horizon 2020 programs: Excellent Science, Industrial Leadership and Societal Changes. They looked at percolation theory, and networks were examined in terms of global efficiency, local efficiency and mesoscopic-scale effects.

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