RUDN scientist explained what determines the severity of an infectious disease

Scientist RUDN Vitaly Volpert, together with a colleague from the USA, developed a mathematical model that describes in detail the interaction of the virus with the cell’s defense systems. The study, published in an authoritative journalJournal of Theoretical Biology, allows us to take a new look at why some infections proceed acutely and end quickly, while others take on a chronic form.

When a virus enters the body, an invisible battle eye unfolds. The cells of our body produce special proteins — interferons, which send an alarm signal. In response to this signal, hundreds of so-called interferon-stimulated genes (ISG) are activated. Their task is to create an environment inside the infected cell where the virus cannot multiply and release new copies into the tissue. Some genes “lock” the virus inside the cell, others prevent it from copying its RNA, and a third group accelerates the self-destruction (apoptosis) of the infected cell.

But the virus does not give up. It develops its own tricks to suppress the work of ISG. This “game of numbers” inside each infected cell largely determines how severe the disease will be and whether the body will be able to completely clear the pathogen.

Mathematics of cellular warfare

To understand complex mechanisms, scientists have created a new mathematical model. Unlike classical approaches, where all infected cells are considered the same, the new model separates them for the first time based on two key parameters: the number of viral particles inside the cell and the activity of protective ISG.

“Imagine a city where every house (cell) is in one of many states — from fully infected by the virus to having mobilized all its defenses. Our model allows tracking exactly how cells move between these states depending on intracellular processes. This provides us with a computationally efficient tool that can simulate the development of the infection and predict it within minutes,” —Vitaliy Volpert, head of the scientific laboratory of the Faculty of Physical and Mathematical and Natural Sciences RUDN.

The proposed approach turned out to be universal. It was tested on real data from patients with COVID-19 (dominant before the appearance of the alpha strain variant) and with HIV. The model accurately reproduced the dynamics of viral load — both in cases of acute infection and in chronic cases.

Interferon paradox

One of the most unexpected conclusions was the behavior of the system under different intensities of interferon signaling. It is logical to assume: the more active the defense, the faster the organism copes with the virus. However, calculations showed that this is not always the case.

“We have encountered a paradoxical effect: a strong interferon response may contribute to the persistence of viruses. This does not mean that interferons are bad. It means that in therapy, especially in chronic infections, balance is important. Too aggressive stimulation of one’s own immunity can lead to prolonged illness rather than its cure,” they writeAuthors of the work.

Effectiveness of ISG

Researchers also assessed how effectively ISG suppresses virus replication. It turned out that there is a critical threshold: if ISG effectiveness is below 67–80%, the viral load decreases slowly and linearly. But as soon as effectiveness exceeds this threshold, each additional percent of protection leads to a sharp, exponential reduction in the amount of virus.

“This is probably related to the security system in the fortress. While the protection is weak, attackers still find loopholes. But if you build reliable defense, even a slight strengthening gives a colossal effect. Our model shows that to control a severe infection, a high antiviral effectiveness is definitely necessary,” —Vitaliy Volpert.

One more important aspect is the speed at which the virus leaves the infected cell. If the virus “gets trapped” inside and does not leave, it accumulates, which leads to the death of the cell and prevents the infection from spreading. However, if the secretion is too active, the virus quickly leaves the cell, but does not have time to multiply within it.

The model showed a nonlinear dependence: the maximum overall viral load (the area under the curve reflecting the “severity” of the infection) is achieved at a moderate secretion rate. This discovery may be significant for drug development: blocking the virus release is a standard strategy, but the modeling results suggest that in some cases, on the contrary, accelerating the virus release from cells could reduce its intracellular replication and the overall load on the organism.

From theory to practice

The created model differs not only in the depth of elaboration of biological mechanisms but also in computational efficiency. It allows simulating 30 days of infection in less than a minute on a regular computer. This makes it a convenient tool for studying individual features of disease progression as well as for searching for optimal drug targets.

“It is easy to adapt ours to specific viruses. In the future, we plan to supplement it with blocks describing the pharmacokinetics of drugs and adaptive immunity. This will allow not only to predict the course of infection but also to select personalized treatment schemes, choosing between interferon stimulators and antiviral drugs that affect secretion and replication,” they notedauthors of the work.

The work of scientists demonstrates how modern mathematics helps to decipher the finest mechanisms of interaction between humans and viruses. Understanding the “rules of the game” inside the cell is the key to developing more effective strategies to combat infections, whether well-known ones like COVID-19 and HIV or future epidemic threats.