Predicting viral spread is essential for addressing a pandemic, and this itself is a complex process. However, may models do not account for what happens if a pathogen mutates and how this alters the information and may change the speed at which a virus spreads. Scientists from College of Engineering, Carnegie Mellon University demonstrate how important evolutionary information about a pathogen is.
All viruses eventually mutate, often by introducing random mutations into their genes. With the novel coronavirus SARS-CoV-2, this is a strain of the species severe acute respiratory syndrome-related coronavirus (SARSr-CoV). There are already two forms of the virus.
The new research involved creating a mathematical theory that accounts for evolutionary changes in relation to pathogens. The theory was then put to the test against thousands of computer-simulated epidemics involving real-world networks, such as a hospital. This looked at the various factors involved in the transmission of a disease.
The two main models involved a network that exists between students, teachers, and staff at a US high school, plus a different network in a different setting and in a different country. This second network was one between staff and patients in a hospital in Lyon, France.
These simulations help to fine-tune the theory and create the basis for a model through which accurate simulations can be run.
According to lead researcher Professor Osman Yagan: “These evolutionary changes have a huge impact. If you don’t consider the potential changes over time, you will be wrong in predicting the number of people that will get sick or the number of people who are exposed to a piece of information.”
With the current global concern over the novel coronavirus, the model can play a role provided that accurate real-time data relating to the path that the virus is taking is inputted and the model is given time to run.
The main limitation with the coronavirus has been the lack of a robust and detailed timeline of records of suspected, probable, and confirmed cases and close contacts, especially from the source area in China.
The research has been published in the journal PNAS, with the science paper titled “The effects of evolutionary adaptations on spreading processes in complex networks.”
