Scientists try to predict the spread of something across populations, When scientists try to predict the spread of something in a population, from coronaviruses to misinformation, they use sophisticated mathematical models.

They usually examine the first steps where the subject spreads and use this speed to project how far and wide the spread will reach.

This evolutionary change has major implications, researchers say. If you don’t take into account the possibility of change over time, you will incorrectly predict the number of people affected or the number of people exposed to information.

Most people are familiar with epidemics, but the information itself, which is transmitted at lightning speed through social media, can survive and “go viral” in the epidemic itself.

Some information is accidental, but others can develop organically if many people make small changes on the phone on a regular basis. Scientists try to predict the spread of something across populations.

At first glance, boring information can become a viral tweet, and we should be able to predict how these things spread.

In their study, researchers developed mathematical theories that took into account these evolutionary changes.

They then test their theories against thousands of computer-simulated epidemics on real networks such as Twitter to spread information or hospitals to spread disease. Scientists try to predict the spread of something across populations.

In connection with the spread of infectious diseases, the team conducted thousands of simulations using data from two real networks: a network of contacts between students, teachers and staff in American high schools and a network of contacts between staff and patients in hospitals in Lyon, France.

Although this research is not a silver bullet to predict the current spread of the corona virus or the spread of false news in a volatile political environment with 100% accuracy, real-time data is needed to track the development of pathogens or the information generated from the data is a big step.