Respiratory infections: how does a virus spread inside a body and through the population?
Each year, the flu impacts up to 20% of our population, and the COVID-19 pandemic has shown just how devastating respiratory infections can be.
The JRC's latest research in this field is not just about understanding these threats; it's also about anticipation and preparedness for future epidemics.
Four new JRC epidemiological and viral kinetics models were designed to better understand the complexities of how respiratory infections spread and to guide their management. These theoretical frameworks are particularly critical because of the relentless evolution of viruses, which calls for constant vigilance. Take COVID-19, for instance. The world has faced multiple variants since the pandemic began, each with its own set of challenges. JRC’s models can now assist in understanding how the virus spreads within a host and within a population and determine specific counter-measures.
The viral kinetics model investigates the complex interplay between viruses and the human immune system. It gives an enhanced description of the immune response, such as waning immunity (i.e. the natural decline of the immune response after infection) allowing for reinfection events, and shows that the immune response to viral infection is a strongly individual-specific process.
An immuno-epidemiological approach that embeds the level of immunity in the epidemiological population dynamics model provides a framework to optimise vaccination strategies taking into account the associated socio-economic impacts. The findings suggest that early, robust vaccination efforts are crucial in the initial outbreak stages. As the outbreak evolves, maintaining immunity becomes a balancing act between vaccination and the natural development of herd immunity, occurring when a significant portion of a population becomes immune to an infectious disease.
The spatial epidemiological model evaluates mobility restrictions, showing that for populations with intensive natural contacts between people, the optimal contact restrictions are low. The optimising decision-maker may also look at herd immunity development. Also, it shows that more testing does not always lead to more optimal contact restrictions.
A fourth model addressed the highly debated infection risk due to exposure to infectious airborne respiratory droplets by inhalation. It provides a technical insightful risk analysis by showing the link between fundamental models of individual airborne infection and epidemiological models. JRC scientists show how the epidemic infection risk depends on the pathogen latent period and the event time, the time infection occurs. The shorter the latent period, the greater the infection risk, according to the results.
These insights allow for a more nuanced epidemiological interpretation of infectious disease outbreaks embedding the dynamics of infectious respiratory droplets. This work and its implications is widely reflected in a recent report of the World Health Organization (WHO) on pathogens that transmit through the air.
Anticipating future epidemics, like the bird flu
Our models are also applicable to the study of emerging respiratory infectious diseases, such as the bird flu. Even if their potential to adapt to humans remains very low, our modelling frameworks are designed to help assess and manage such risks, should they ever increase. The ongoing H5N1 bird flu epidemic has been a global issue since 2020, resulting in the culling of millions of poultry and other birds in an attempt to control the virus.
To conclude, these new JRC’s modelling frameworks assist in refining public health policies by providing insights into transmission dynamics and aiding in the development of effective interventions. They ensure that we will be ready to respond when the next epidemic hits our planet.
Related links
On modelling airborne infection risk. Royal Society Open Science (2024)
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