A research team from Nagoya University in Japan has uncovered new insights into the relationship between human behavior and the evolution of SARS-CoV-2, the virus that causes Covid-19. The study, published in Nature Communications, shows that confinements and isolation measures can influence how the virus evolves.
The coronavirus has evolved to become more transmissible earlier in its life cycle, a finding that highlights the importance of understanding how people’s behavior affects disease-causing agents. By isolating sick people and using lockdowns to control outbreaks, humans can alter the evolution of the virus in different ways.
One important concept in this interaction is viral load. This refers to the amount or concentration of a virus present per ml of a body fluid. In the case of SARS-CoV-2, a higher viral load in respiratory secretions increases the risk of transmission through droplets. Viral load relates to the potential to transmit a virus to other people, with viruses like Ebola having an exceptionally high viral load, while the common cold has a low one.
The research group used mathematical models with an artificial intelligence component to analyze previously published clinical data. They discovered that successful SARS-CoV-2 variants had an earlier and higher peak in viral load as well as a shorter duration of infection. Additionally, they found that changes such as decreased incubation period and increased proportion of asymptomatic infections also affected virus evolution when mutations occurred.
Iwami and his colleagues suggest that human behavior changes designed to limit transmission were increasing selection pressure on the virus. As a result, SARS-CoV-2 became more transmissible during asymptomatic and pre-symptomatic periods earlier in its infectious cycle. When evaluating public health strategies for future pandemics or outbreaks caused by coronaviruses or other pathogens, it is crucial to consider how changes in human behavior may impact virus evolution patterns.
In conclusion, this study highlights how human behavior affects disease evolution patterns and underscores the importance of considering these factors when developing adaptive treatments and interventions for future pandemics or outbreaks caused by coronaviruses or other pathogens.