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A new mathematical model developed by researchers at Empa has the potential to improve the accuracy of predictions regarding the course of infectious diseases. The model challenges the traditional reliance on the reproduction number (R) to forecast epidemic waves.
The limitations of R
The R value represents the average number of people an infected individual can infect. If R is greater than one, the number of cases increases exponentially. Conversely, if R is less than one, the number of cases decreases. While this model offers a basic understanding of an epidemic’s trajectory, it fails to account for the complexities of real-world scenarios.
Introducing the reproduction matrix
The new model incorporates a reproduction matrix instead of a single R value. This matrix acknowledges that not all infected individuals have the same capacity to spread the disease. People with more social contacts, for instance, are more likely to transmit the infection to others. These individuals are referred to as “superspreaders” and can significantly influence the initial stages of an outbreak.
The researchers at Empa divided the population into groups based on age. People between the ages of 10 and 25 generally have the most contacts, according to the study. The model acknowledges that this grouping is a simplification and doesn’t account for the nuances of real-world interactions.
The benefits of the new model
The reproduction matrix offers a more nuanced understanding of how epidemics spread. This can lead to more accurate predictions of infection peaks, allowing for more effective implementation of preventative measures. The model can also be applied to study the spread of ideas and behaviors within a society.
The researchers tested their model with COVID-19 data from Switzerland and Scotland and achieved promising results in predicting infection peaks. While the model is currently in its initial stages, it has the potential to revolutionize our understanding and response to infectious diseases.
This is just a summary of the research, you can find more details in the Journal of the Royal Society Interface paper titled “Emergence of the reproduction matrix in epidemic forecasting” by Hossein Gorji et al.
