Computer Simulation Shows Mutant Strains of Corona Responding to Human Behavior!

Using artificial intelligence technology and mathematical modeling, a research team led by Nagoya University has revealed that human behavior such as lockdown and isolation measures influence the evolution of new strains of the coronavirus. The SARS-CoV-2 virus that causes Covid-19 has become transmissible earlier in its life cycle.

The results of the new study, published in the prestigious journal Nature Communications, provide new insights into the relationship between people’s behavior and disease-causing factors, according to the specialized medical website “Medical Express”.

Like other organisms, viruses evolve over time; The one with the survival advantage dominates the gene pool.

Many environmental factors influence this development; including human behavior. By isolating sick people and using lockdowns to control outbreaks, humans can alter the evolution of the virus in complex ways.

Predicting how these changes will occur is critical to developing adaptive treatments and interventions. An important concept in these interactions is viral load, which refers to the amount or concentration of virus present in one milliliter of body fluid.

In SARS-CoV-2, high viral load in respiratory secretions increases the risk of droplet transmission. Viral load is related to the possibility of transmitting the virus to others; For example, a virus like Ebola has an exceptionally high viral load, while the common cold has a low viral load. However, viruses must perform a careful balancing act, as increasing maximal viral load can be beneficial, but excessive viral load can make individuals too ill to transmit the virus to others.

In this context, a research team led by Professor Shingo Iwami at the Graduate School of Science at Nagoya University used a mathematical model with artificial intelligence elements to analyze previously published clinical data to identify trends. They found that the SARS-CoV-2 strains that were most successful at spreading had an earlier and higher peak in viral load. However, as the virus evolved from pre-alpha variants to delta variants, the duration of infection was shorter.

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The researchers also found that a decrease in the incubation period and an increase in the proportion of asymptomatic infections recorded due to viral transformation affected the evolution of the virus. The results also showed a clear difference. As the virus evolved from the Wuhan strain to the Delta strain, the researchers found a 5-fold increase in peak viral load and a 1.5-fold increase in the days before viral load reached its peak.

Iwami and colleagues suggest that changes in human behavior in response to the virus, designed to reduce transmission, increase selective pressure on the virus. It transmits SARS-CoV-2 mainly during asymptomatic and pre-symptomatic periods, which occur early in its infectious cycle. As a result, the peak viral load advances to this period to transmit more effectively at earlier stages, before symptoms appear.

When evaluating public health strategies in response to COVID-19 and potential future pandemic pathogens, it is important to consider the impact of changes in human behavior on virus evolutionary patterns.

The study concluded by stating that “human behavior may contribute to the evolution of the virus in a more complex way”, pointing to the need to re-evaluate the evolution of the virus due to the possibility of new strains of the coronavirus. The complex relationship between clinical symptoms and human behavior.

In turn, the researchers hope their research will accelerate the development of test systems for adaptive treatment, effective screening and isolation strategies.

  • Nadia Barnett

    "Award-winning beer geek. Extreme coffeeaholic. Introvert. Avid travel specialist. Hipster-friendly communicator."

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