In my previous post, I described my methodology for estimating the number of Covid cases, hospitalizations, and deaths by age cohort in Massachusetts. That post details the issues associated with determining these estimates because of lack of consistency and transparency in the data published by the state. This post begins the analysis based on these estimates.
Figure 1 shows an estimate of the weekly incidence of Covid cases for four different age cohorts (under 40, 40 to 59, 60 to 79, and 80 plus) starting May 30th. Prior to that, case incidences for people 80 and over are very large relative to current figures – this makes current trends less easy to discern on a graph. (The case incidence rate for people 80 plus in Massachusetts peaked at over 1,000 per 100,000 per week in late April, meaning that over 1% of people of that age were being diagnosed with Covid each week). The population estimates I use to calculate incidence rates are the same as those the state uses for its age cohort calculations in the weekly public health report.
Figure 1 clearly demonstrates the dramatic change in case incidence over time for those 80 and over, with a sharp decline through the middle of July so that this cohort now has low case rates compared to those under 60. The other age groups have similar rates through June, but these rates have diverged since, so that people between 60 and 79 now have low relative case incidences. In short, Figure 1 shows the both the shift in cases from older to younger populations, and the increase in cases for all age groups after Labor Day.
Figure 2 shows the percentage of confirmed and suspected cases for each age group, starting April 4th because there are no scaling issues here. It shows the shift to younger people in a different way – the percentage of cases in those under 40 grew from about 30% at the beginning of April to roughly 60% currently, while the percentage of cases for those 60 and older has declined from over 30% in April to just over 10% now. Figures 1 and 2 may seem contradictory for those 80 and over. However, over half the state is under 40, and only 4% is 80 and over – meaning that the case incidence rate for those over 80 could be very high, but cases in that age cohort remain a relatively small fraction of total cases.
Figure 3, which shows the ratio of the case percentages to population percentages for each cohort, illustrates this in a different way, essentially combining the information in Figures 1 and 2. For the state as a whole, this ratio must equal 100%, so a figure over 100% means that a particular age cohort has a higher share of the cases than one would expect based on its population, and a figure under 100% means that the age cohort has a lower share of the cases than one would expect based on its population. If cases were proportional to population for each age group, these ratios would be exactly 100%.
Figure 3 perhaps best shows the shift in the dynamics of cases by age, as cases for those those under 40 went from well below average in April to above average (and the most over-represented cohort) now. Conversely, those 80 and over, who at one point were 17% of cases with only 4% of the population, now have much lower relative risk for being diagnosed with Covid. That also holds to for those between 60 and 79, but the change has been less dramatic. This is presumably because seniors are now either less likely to be in situations where they can be infected by Covid, or because they take more stringent precautions when in these situations.