Why do bacterial and viral infections seem to occur in seasonal cycles? What factors impact this occurrence? And what role does the Sun play in the entire process?
About the Research
An interdisciplinary research team set out to find answers to the above-mentioned questions. Furthermore, the researchers come from The Italian National Institute for Astrophysics, The University of Milan, The Lombardy Regional Agency for the Environment, and The Don Gnocchi Foundation. Through their combined efforts they built a theoretical model that shows how epidemic prevalence and evolution depend on the Sun.
Fabrizio Nicastro from INAF said the following in regards to the model built by the interdisciplinary team.
“Why do many viral respiratory epidemics, such as influenza, develop cyclically during autumn and winter only in the temperate regions of the globe’s northern and southern hemispheres, while they seem to be present at all times – albeit with lower prevalence compared to the seasonal cycles in the temperate regions – in the equatorial belt? And what triggers and determines such seasonality? In our work, we propose that what causes the seasonality of airborne-transmitted epidemics is exactly the same mechanism that causes seasons on our Planet: the amount of daily solar irradiation on the Earth”.
The main reason why the Sun makes viruses less dangerous during the warmer months is because of UV light. That is, it is a well-known fact that UV light deactivates many different kinds of viruses and bacteria. The actual extent to which the UV light deactivates the virus and bacterium depends on the particular type of pathogen. However, it is a general rule that damaging effects of sunlight are stronger in regions where there is more radiation.
Furthermore, one more factor may impact the strength of the epidemic and this is the so-called antigenic shift. That is, the virus may mutate over time and this will make the host’s existing antibodies noneffective in addressing the infection. The researchers claim that both factors contribute to periodic spikes in infections.
The researchers working on this model claim that they will be able to apply it in real-life situations. That is, the model can help predict how an epidemic may spread, and when it will lower in intensity. Such information can help us be better at determining policies we need to stop the spread of life-threatening infections.