That Triangle Again

As well as the often-mentioned “R Naught” number there is a “K Distribution” number used in Epidemiology which seems particularly important in transmission of SARS-CoV-2.  These mathematical terms are simplified by the below diagrams.  Where “R0” describes the average transmission distribution from infected case to susceptible contacts, “K” describes the variance, or pattern, of virus transmission.  The K number is more important in Covid because as few as 10-20% of infected Covid cases have been found to be responsible for 80-90% of transmission, meaning the R number can mask the way transmission is dispersed.  Up to 70% of infected Covid cases seem to not infect another person.

When experts say “Covid doesn’t transmit in the same way as Influenza”, they are referring to the R0 and the K.  Influenza follows closer to an R0 transmission pattern and Covid follows a K pattern.  These diagrams helped me make simple sense of a complicated concept.

A good article explaining these numbers, and where I found the pictures, is The Conversation: Is the K number the new R number?  What you need to know.

This seems relevant in many ways including the over-dispersion that continues to occur in aged care homes where it seems that infected cases are more infectious, perhaps with high viral loads caused by immune suppression, which they then emit in enclosed spaces and close proximity to other susceptible contacts.  Hopefully this can inform policy around how best to protect nursing home residents from the virus whilst at the same time allowing them to maintain social contact with family.  I recently saw video footage of a 104 year old woman begging to be allowed to see her family after months of isolation.  Many aged care related deaths this year are reportedly due to loneliness and isolation causing hopelessness, depression, confusion and malnutrition, which seems to me, to be at least as cruel as dying from a respiratory virus?  Public health always needs to consider protection of the population as a whole rather than focusing on a single disease.

Again, the Epidemiological Triangle has it covered.  Compare over-dispersion of Covid in nursing homes with the under-dispersion occurring in many places, and you can’t help but wonder which factors are influencing this massive difference?  We are not all at equal risk from Covid (the same is so for most diseases) and there are many reasons why.

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