In a groundbreaking study, a research group led by Nagoya University harnessed artificial intelligence and mathematical modeling to unveil the profound influence of human behavior on the evolution of COVID-19 strains. Their findings, recently published in Nature Communications, shed light on the intricate relationship between societal actions, such as lockdowns and isolation measures, and the development of more transmissible variants of SARS-CoV-2, the virus responsible for COVID-19.
Viruses, much like living organisms, undergo evolutionary changes over time, with those possessing survival advantages dominating the gene pool. Human interventions, including the isolation of infected individuals and the implementation of lockdowns to control outbreaks, play a complex role in shaping virus evolution. The ability to predict and understand these changes is paramount for the development of adaptive treatments and interventions.
Central to this interaction is the concept of viral load, referring to the concentration of a virus present per milliliter of bodily fluid. In the case of SARS-CoV-2, a higher viral load in respiratory secretions increases the risk of transmission through droplets. Viral load is closely tied to the virus’s potential to spread to others, making it a crucial factor in the dynamics of transmission. For example, viruses like Ebola exhibit an exceptionally high viral load, while the common cold has a lower one. Striking the right balance is essential for viruses, as an excessive viral load may render individuals too sick to transmit the virus effectively.
The research group, led by Professor Shingo Iwami at the Nagoya University Graduate School of Science, employed mathematical modeling with an artificial intelligence component to analyze previously published clinical data. Their findings revealed distinct trends in the evolution of SARS-CoV-2 variants. Variants that proved most successful at spreading exhibited an earlier and higher peak in viral load.
As the virus evolved from the original Wuhan strain to the Delta variant, the researchers observed a fivefold increase in the maximum viral load and a 1.5-fold increase in the number of days before the viral load peaked. Notably, the virus also exhibited a shorter duration of infection as it progressed through different variants. The decreased incubation period and an increased proportion of asymptomatic infections recorded during the virus’s mutations were identified as additional factors influencing virus evolution.
The study suggests that human behavioral changes, implemented in response to the virus to limit transmission, were amplifying the selection pressure on the virus. This phenomenon led to SARS-CoV-2 being transmitted predominantly during the asymptomatic and presymptomatic periods, occurring earlier in its infectious cycle. Consequently, the peak of viral load advanced to this earlier pre-symptomatic stage, facilitating more effective spread.
Professor Iwami and his colleagues propose that immune pressure from vaccinations and/or previous infections is not the sole driver of SARS-CoV-2 evolution. Instead, human behavior contributes to the virus’s evolution in a more intricate manner. This revelation underscores the necessity to reevaluate our understanding of virus evolution in response to changing human behaviors.
In evaluating public health strategies for COVID-19 and potential future pandemics, it becomes imperative to consider the impact of human behavior on virus evolution patterns. The research team anticipates that their findings will expedite the establishment of testing regimes for adaptive treatment, effective screening, and isolation strategies.
Source: Nagoya University