2.3
Contagion
factors
Dissemination
Factor (K)
https://cmmid.github.io/topics/covid19/overdispersion-from-outbreaksize.html shows
that overdispersion k is < 0.2 possibly 0.1 and R0 >
1.4 that indicates that 80 % of infections are caused by 10
% superspreaders.
https://wellcomeopenresearch.org/articles/5-67/v1
That
means 80 % of secondary transmissions originate from
10 % of superspreaders.
Lloyd-Smith,
J., Schreiber, S., Kopp, P. et
al. Explain how this was already the case for
sarscov-1. They also remind that for a k value around 0.1
containment maybe obtained at ((1-1/R0)/2). This means that herd
immunity is could be obtained depending on R0 value of an outbreak
anywhere between 14 % and 39 % of sensitive population
in most countries that have been prone to an outbreak. (Analysis
of outbreaks explored later on this paper shows us how some
countries, regions are somehow very insensitive to respiratory
disease outbreaks)
https://doi.org/10.1038/nature04153
A
shenzen study confirms such overdispersion by observing that
8.9 % of cases caused 80 % of infections
https://www.thelancet.com/pdfs/journals/laninf/PIIS1473-3099(20)30287-5.pdf
Successfully
controlling superspreading may bring such epidemics to extinction
as with SARSCOV-1.
Social
susceptibility
M
GABRIELA and M GOMES show how populations are not homogenous in
susceptibility, in the sense that « superspreaders » the
10 % are often highly connected individuals and beyond
biological aspects they need to be connected to « super
spread ». If they are connected they are also more exposed
and thus more likely to be infected early and more likely to
spread early causing a much higher spread rate in the first phase
of the epidemic where they become infected, spread, become immune.
An
example would be a bus driver
who sells tickets, maybe more exposed, once infected he may
contaminate a few dozen people. After he recovers he
no longer infects anyone. Once most bus drivers have
become immune the epidemic slows down.
This
« natural
selection » of superspreaders would mean that herd immunity
could be as low as 5 % to 35 % depending on R rate which
is dependent upon factors that lead to propagation and severity.
https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v3.full.pdf+html
Based
on his paper N
Lewis tests susceptibility notion for Stockholm and reaches a herd
immunity estimate between 7 % and 24 % depending mostly
on correlation between susceptiblity and infectivity of
individuals based on an R0 of 2.4.
Carefull
analysis
across countries, and taking into account that it was shown the
virus was present in France since early December 2019 and
indications it may have been present possibly weeks or months
before, it does seem that R value and severity of this virus may
vary significantly.
It
may actually have a very low natural Rn that has maintained it
active for a long time without being visible. This R value may
vary slightly between seasons. The rare severe cases may have been
confused with flu, pneumonia or other infections. Its mildness may
have maintained it invisible until a set of conditions united for
repeated consecutive super-spreading leading to this epidemic and
consecutive world panic.
Although
there
was a case in France early December, the epidemic was invisible in
terms of over-mortality until March 16th and Hospitalizations
until March 1st to peak in terms of death week 14 between March
30th and April 5th as
per Insee Data and EuroMomo. This is a combination of a very slow
epidemic with an R that could be as low as 1.4 that picks up
suddenly with and R that may have tripled when the right
conditions of clustering accumulated.
Changes
in R and severity maybe associated to changes in populations
density, activation of HVAC, multiplications of reunions in closed
spaces (ski vacation, occasional holiday gatherings, changes in
commuting), presence or absence of competing/multiplying of other
pathogens, UVs, vitamin D levels, relative humidity, mucosa,
seasonal diet and other factors that have not been identified.
Such factors may impact the virus itself or the host in terms of
propagation, receptivity, course, symptoms or severity thus in
turn impacting contagion and R value.
Clinical
observations
hint that infections have become milder in Europe. Since there is
no indication of any mutation, this maybe because of natural
selection mechanisms such as a minor evolution in the virus or
that most vulnerable were infected more easily. This is often
observed in epidemics towards the end. It may also be because
spring or summer make the hosts transmit less viral load or resist
better.
Association
between
susceptible and superspreaders would have been very strong if most
transmission happenned because of social contacts. This would have
taken the bus driver, cashier or the teacher, the waiter, the
trainer, the physician, the nurse…. out of the equation very early
on.
Much
of the superspreading
seems to be related to places discotheques, hospitals, schools,
dorms, slaughterhouses, malls, transport, supermarkets…..Workers
of such places are more susceptible and more likely to superspread
as they spend more time and have more contacts with others in such
places. Yet, it could be anyone who spends enough time in such a
place. HVAC may make dissemination more complex as it may become
random within the place. This reduces impact of
such an association.
Such
association
remains significant because much of contagion seems to require
prolonged exposure and/or significant viral load. A cashier in air
conditionned supermarket would
be more exposed and would catch it earlier to pass it on
earlier as it would stay longer in the supermarket.
Once most non resistant cashiers of supermarkets have
become immune, they no longer contribute to superspreading.
Superspreading becomes rarer in supermarkets. A customer may
occasionnaly be at the
origin of a cluster but as he spends less time his impact, in most
cases would be relatively low compared to the cashier infecting
customers all through several days, then infecting other cashiers
whom in turn would infect other customers.
A
very similar situation would happen with a bus driver, transport
salesperson, restaurant waiter, slaughterhouse employee, dorm
inhabitant, Mall employee……
Sensitivity
and
resistance
Another
significant factor in contagion is Population resistance, that is
the presence of a population whom, under normal circumstances
would not get infected because of past immunity or other reasons
as observed in the past.
Evidence
points
to that children are less likely to contract the virus and less
likely to transmit it.
In
addition,
in the French aircraft carrier Charles De Gaulle case study, out
of a population of 1760 sharing common dorms, common corridors,
common cantines for a month, 1043 (59%) were infected, but the
other 41% tested negative in spite of having been exposed to the
significant viral load repeatedly. This is mostly a male rather
young population. It is possible this resistance maybe lower in
older population and probably higher in women and children.
It is also possible that a higher
fraction of the adult population that may be resistant to virus
under normal exposure.
Part of that protection may be due to
genetics, cross-immunity, past immunity or other factors.
https://www.cell.com/cell/fulltext/S0092-8674(20)30610-3
A Griffoni
« we
detected SARS-CoV-2-reactive CD4+ T cells
in ∼40%–60% of
unexposed individuals, suggesting cross-reactive T cell
recognition between circulating “common cold” coronaviruses and
SARS-CoV-2. »
« Importantly,
pre-existing
SARS-CoV-2-cross-reactive T cell responses were observed in
healthy donors, indicating some potential for pre-existing
immunity in the human population. »
https://www.medrxiv.org/content/10.1101/2020.04.17.20061440v1.full.pdf
J Braun
« We demonstrate the
presence of S-reactive CD4+ 52 T cells in 83% of COVID-19
patients, 53 as well as in 34% of SARS-CoV-2 seronegative healthy
donors (HD), albeit at lower frequencies »
https://www.biorxiv.org/content/10.1101/2020.05.14.095414v1
K
NG
« we
demonstrate
the presence of pre-existing immunity in uninfected and unexposed
humans to the new coronavirus »
https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.26098
L
Pinky H Drobovolny
« finding
that
SARS‐CoV‐2 replication is easily suppressed by many common
respiratory viruses. According to our model, this suppression is
because SARS‐CoV‐2 has a lower growth rate (1.8/d) than the other
viruses examined in this study. The suppression of SARS‐CoV‐2 by
other pathogens could have implications for the timing and
severity of a second wave. »
https://www.biorxiv.org/content/10.1101/2020.06.29.174888v1
T
Sekine, A Potti
Importantly,
SARS-CoV-2-specific T cells were detectable in
antibody-seronegative family members and individuals with a
history of asymptomatic or mild COVID-19. Our collective dataset
shows that SARS-CoV-2 elicits robust memory T cell responses akin
to those observed in the context of successful vaccines,
suggesting that natural exposure or infection may prevent
recurrent episodes of severe COVID-19 also in seronegative
individuals.
Serological
antibodies test show inconsistent results both with known cases
and comparatively with death counts making them unreliable to
indicate protected population. Bergamo and Madrid Serological
tests would indicate respectively 0.4 % and 0.92 %
lethality whereas Bergamo’s population is older than that of
Madrid.
Yet
they still give some indication that 14 % to 57 % of
hard hit regions have developped antibodies.
Based
on above findings, it seems reasonable to assume that a tranche of
populations ranging between 44 % and 70 % is resistant
to the virus or protected from it and is unlikely to be
contaminated and under normal or even severe exposure to the virus
because of genetics, epigenetics, cross immunity, cellular
immunity, T cells….
We
are assuming based on existing history of cases, existing
literature and usual reaction to other Corona Viruses
that those who recover become immune and either fully
protected or retain some memory protection making new infections
milder, shorter thus less contagious.
Clusters
Flu-like epidemics tend to
propagate in clusters and this has been shown to be true for COVID
as well in recent papers :
https://www.medrxiv.org/content/10.1101/2020.04.04.20053058v1.full.pdf
investigated
318 outbreaks involving 3 or more cases, all were indoors mostly
home and transport.
https://www.medrxiv.org/content/10.1101/2020.02.28.20029272v2.full.pdf
shows that closed environments promote
contagion and superspreading 18.7 times more than open
environments.
Epidemic clusters have been identified
involving closed places with people gathering with little air
circulation such as transport, worship places, slaughter houses,
companies, hospitals, care facilities, police stations etc. On a
more general level, major cities (London, New York, Paris, Madrid,
Milan etc) with factories, air conditioned offices, dense public
transport, regular social and religious crowded events offer
higher superspreading opportunities than medium cities or rural
areas where the epidemic un-noticed when no superspreading
happened
R
A. HOBDAY provides an interesting view as to fresh air and
sunshine hospitals mitigating contagion and even helping recovery
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4504358/
« Records
from
an "open-air" hospital in Boston, Massachusetts, suggest that some
patients and staff were spared the worst of the outbreak. A
combination of fresh air, sunlight, scrupulous standards of
hygiene, and reusable face masks appears to have substantially
reduced deaths among some patients and infections among medical
staff. »
Y
Li systematic review teaches us about effect of ventilation on
airborne transmission
https://pubmed.ncbi.nlm.nih.gov/17257148/
« There
is
strong and sufficient evidence to demonstrate the association
between ventilation, air movements in buildings and the
transmission/spread of infectious diseases such as measles,
tuberculosis, chickenpox, influenza, smallpox and SARS. »
Recent
manifestations across the world in countries with tens of
thousands of people gathering with close contacts in a very
restricted open air space with few masks did not lead to cluster
formation in spite of massive testing further confirming
contamination happens indoor. Melbourne manifestation is
particularly interesting as Melbourne is entering winter and
Australia is tracing regularly and has to this date managed to
keep virus under control.
Most
identified
clusters happenned in :
Health
Care
facilities or Hospitals
Slaughter
houses
Schools
Hotels
Social
facilities
Discotheques
Subway/Metro
Buses
Companies
Worship
places
Family
reunions
Gyms
Call
centers