Getting control of COVID-19 will take more than widespread vaccination; it will also require better understanding of why the disease causes no apparent symptoms in some people but leads to rapid multi-organ failure and death in others. It will also require better insight into what treatments work best and for which patients.

To meet this unprecedented challenge, researchers have created a mathematical model based on biology that incorporates information about SARS-CoV-2, the virus that causes COVID-19, and about the various treatments that have been tested in patients with the disease.

Science Daily reports that the model and its important clinical applications are described in the journal Proceedings of the National Academy of Sciences (PNAS). It is the work of researchers at Massachusetts General Hospital (MGH), in collaboration with investigators from Brigham and Women’s Hospital and the University of Cyprus.

Their work provides valuable insight into issues such as the effectiveness of antiviral and anti-inflammatory drugs at various stages of the disease. It also explains why younger patients with healthy immune systems tend to recover from COVID-19. They have found that these patients have a lower risk of oxygen-blocking blood clots forming in their lungs.

In contrast, people who have higher levels of inflammation at the time of infection — such as those with diabetes, obesity or high blood pressure — or whose immune systems are somehow impaired, tend to have poor outcomes.

Based on their findings, the researchers have been able to propose the best course of treatment for older patients and those with pre-existing conditions.

Their work shows how tools originally developed for cancer research can be useful for understanding COVID-19. The team is further developing the model and plans to use it to examine the dynamics of the immune system in response to different types of COVID-19 vaccines as well as cancer-specific comorbidities that might require special considerations for treatment.