Social stress key to population’s COVID-19 infection rate, study finds – ScienceDaily

Mathematicians analyzed global COVID-19 data to identify two constants that can dramatically change a country’s infection rate.

An international team of researchers led by Professor Alexander Gorban of the University of Leicester used available data from 13 countries to determine the rate of stress response, or “mobilization” and the rate of spontaneous exhaustion, or “demobilization” .

Their findings, published in Scientific reports, show that social stress – which varied considerably among the countries studied – is at the origin of the multi-wave dynamics of COVID-19 epidemics.

The study analyzed data from China, United States, United Kingdom, Germany, Colombia, Italy, Spain, Israel, Russia, France, Brazil, India and Iran – and contributed to the new model system proposed by the research team, which combines the dynamics of the established concept of social stress with classic epidemic models.

Alexander Gorban is Professor of Applied Mathematics at the University of Leicester and Director of the Center for Artificial Intelligence, Data Analysis and Modeling. Professor Gorban said:

“We tried to use the pandemic for research and to quantify the social and cultural differences between countries. We have measured the extent to which countries are variable in two processes: the mobilization of people for rational protective behavior and the exhaustion of this mobilization with destruction of rational behavior.

“This is a serious lesson for educational development, for real policy planning and the like. Why has the mobilization in Germany and Israel been so much faster than in the United Kingdom? Why, according to published epidemic data, did some countries quickly mobilize, but also demobilize very quickly (Iran)?

“How do we convince people to mobilize and maintain their rational behavior? When and how should we teach these skills to our children? And what are we prepared to pay for these capabilities? Our research shows that we need to answer these questions and more. “

For each country analyzed in the study, researchers looked at 200 days of data, from 100 confirmed cases of COVID-19 in each country. They developed the SIR model for the spread of the disease, which takes into account the number of infected individuals relative to the number of “recovered” and “susceptible” members of the population, taking into account various patterns of human behavior.

Each country has demonstrated some form of wave one and wave two pattern, although the pattern does not take into account factors that become important later, including continuous improvement in biological protection methods (such as immunization), economic trends, and viral mutations. During the first 200 days, the dynamics of the epidemic are mainly determined by the contagiousness of the virus and the behavior of people.

Therefore, the researchers determined that the large difference in the spread of COVID-19 between countries is caused by social differences, in response to the established sociological concept of social stress.

This indicates that “sensitive” individuals will go through a cycle of three modes; ignorance (living without restrictions); resistance (individuals consciously and actively practicing social distancing measures; and exhaustion (the depletion of the person’s ability to follow social distancing measures).

The rate of repetition of this cycle is largely determined by a population’s stress response rate and the rate at which a population burns out from social distancing measures. Colombia, Iran and the United States had the highest “burnout rates” of the study countries, with the United Kingdom at the median rate.

China’s stress response rate was the highest of the 13 countries analyzed, reflecting the rapid and dramatic spread of the virus among the human population – after a large initial spike, cases and morbidity rates fell sharply due to ‘a response from the very unified society.

Prof. Victor Kazantsev, head of the team at Lobachevsky University that contributed to the study and head of the department of neurotechnology, Nizhny Novgorod, Russia, said:

“The COVID-19 pandemics have given people a better understanding of our behavior under global stressful situations. This knowledge will help humanity survive longer. Our work is a step in extracting this new knowledge from COVID-19 data. “

Dr Innokentiy Kastalskiy of Lobachevsky University and the Institute of Applied Physics of the Russian Academy of Sciences, added:

“This work is a first step in combining the modeling of social stress with the dynamics of epidemics. We should also take into account the dynamics of immunity, viral evolution and economics. Such models will provide us with tools to quantify different situations, evaluate solutions, and play different scenarios “in silico” to develop anti-epidemic strategies specific to a particular society: country, region or social group. “

Researchers say that ranking countries according to their ability to mobilize people for protective anti-epidemic behavior and maintain that mobilization for a considerable time can help predict the dynamics of future epidemic outbreaks and manage their impact on the population.

Leicester students of the Data Analysis for Business Intelligence MSc program will also use the models presented in the document to further analyze epidemics in all UN countries.