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The curve calculated using a “reproduction matrix” (turquoise) reflects the actual infection rate (black) much more accurately than previous models (yellow and blue). Graphic Credit: Empa |
The reproduction number R is often used as an indicator to predict how quickly an infectious disease will spread. Empa researchers have developed a mathematical model that is just as easy to use but enables more accurate predictions than R. Their model is based on a reproduction matrix that takes into account the heterogeneity of society.
"Your friends have more friends than you do", wrote the US sociologist Scott Feld in 1991. Feld's so-called friendship paradox states that the friends of any given person have more friends on average than the person themselves. This is based on a simple probability calculation: Well-connected people are more likely to appear in other people's social circles. "If you look at any person's circle of friends, it is very likely that this circle contains very well-connected people with an above-average number of friends," explains Empa researcher Ivan Lunati, head of the Computational Engineering laboratory. A similar principle served Lunati and his team as the basis for a new mathematical model that can be used to more accurately predict the development of case numbers during an epidemic.