Discussion
Having a clear understanding of the historic recovery in the community
is a critical piece of information to policymakers as higher levels
mitigate the impact associated with relaxing the social constraints. A
published piece of work not yet reviewed shows serology results from
1/4/2020 carried out on 3,300 people in Santa Clara California that show
40-80 times as many people in the community have had the disease than
was reported by their testing program (14)
The analysis shown in Figure 2 highlights that current lockdown measures
are reducing the daily R-value down to well below one. However, to
commence relaxing these measures, we suggest several principles need to
be in place to ensure the R-value of COVID-19 does not rise above 1,
triggering a second pandemic (there is general acceptance that the
disease will inevitably become endemic).
Figure 3 highlights how the disease progression varies across UTLAs and
how that impacts the infection rate and its relative speed of change.
Regions with history of the most cases/population have the lowest
infection rate RADIR and lowest rate of change in
infection rate ΔIR.
Social distancing behaviour and rules implementation could be expected
to vary across different communities/groups, and as the different UTLAs
have varying amounts of these different communities, examining the
variation of infection rate across UTLAs one would hope to see which
community groups were responding well and which were responding less
well to social distancing. Figure 4 shows the only factor that could be
related to the RADIR in this analysis was the historic
number of confirmed number infection/,000 population suggesting that
some of the reduction in reported cases is due to the build-up of
immunity due to larger numbers of historic cases in the population.
An important comparative R-value reference would be another coronavirus
endemic infection, influenza. During seasonal periods, research
indicates that influenza has an R-value of around 1.3 (15) and can
result in the highest periods up to 200 additional deaths per day above
mortality from other causes, although these figures are constrained by
the provision of flu vaccine which is available particularly for the
high-risk group. However, if the current pandemic can be switched to a
similar mortality rate (with carefully phases social behaviour policies
in place, along with population testing) then unlocking can be managed
in a politically and socially acceptable way. Some observations around
this included
- The principle of self-isolation following infection/symptoms is now
well in place in the population
- The track and contain mechanisms to identify next line contacts of
infected people can also be increased with technical support
- The vulnerable groups can continue to be isolated with their 13-week
restriction kept in place but supported by the general population
- Health service is now better able to cope with the load
Adding to this, experiences with different pandemic policy frameworks
suggest that a looser more flexible approach to social activity can be
managed if high-risk groups are more carefully protected. This is
particularly pertinent given the news this week that elderly care homes
are a significant area of both infections and pandemic mortality (16).
The speed of the unlocking process will depend on the level of
unlocking. However, what is clear is that with the potentially reduced
at-risk population any further peaks will be lower. We looked in UTLAs
at the potential determinants of the ADIR and found that the only factor
that related to this was the historic number of confirmed number
infection/,000 population. This suggests that removing the lockdown from
areas with higher historic caseloads should present a lower risk of
R-value reversal.
However, a ‘one size fits all’ approach to pandemic policy does not
consider the variation in both infection rates and impact across
localities. When the data at the regional level is analysed there seems
to be a wide variety of R-values and slope of extrapolated R-line over
time, implying that unlocking needs to have a certain level of
‘tailoring’ of social behavioural policies and testing to be effective.
These differences are likely to be due to differences in local factors
such as infection drivers and underlying population morbidities. This
has been explored in a separate publication by the same authors (17).