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327How
Should We Allocate Health and Social Resources During a Pandemic?
possibility of the intervention actually creating more vulnerabilities. It
is the same with assuming that all individuals develop immunity once
infected. The modellers might easily reply that the assumptions are
meant to produce approximations rather than exact projections, or that
they could introduce variations of vulnerability to become infected.
The issue here is that they did not in February 2020. While it may be
possible to assume equal vulnerability in a small group of people to
assist with a small outbreak, modelling an entire national population
of millions should have made the issue of inequality in vulnerability to
exposures, infection, and deaths both obvious and required.
The second aspect to note is that as this particular model
assumed generic biological bodies, it was not able to present any anal-
ysis on social distribution patterns. The analysis was only able to pres-
ent aggregate numbers of infected and immune, infected and dead,
and susceptible before the pandemic dies out. Once again, rather than
just increase the population size to the country level, if the model was
also able to project vulnerability for death by social group or social
class variables, it may have been able to project the scale of deaths
of vulnerable populations. Moreover, if that were to have been done,
it seems plausible to imagine that the national response, at least in
the U.K., may have marshalled additional resources early enough to
prevent deaths among vulnerable groups. Instead, only after deaths
began to occur, and it was obvious that the people dying were older
and from racial and ethnic minority groups, that socio-demographic
data started to be collected and analyzed.
Mathematical modelling of infectious diseases have suddenly
become influential scientific evidence in the U.K., U.S., and many
other countries. While important, even the modellers agree that they
have severe limitations; forecasts have to be presented, and received,
with caution. To be more reflective of the context, and hopefully
more accurate, some research groups incorporate more information
into their models, including more diversity of individuals. But even
those models are limited in their ability to incorporate inequalities in
vulnerabilities to infections created by a range of natural and social
causes. Without doing so, these infectious disease models will con-
tinue to erase vulnerabilities and, in turn, recommend policies that
are generic. Furthermore, they will be unable to recognize the poten-
tial additional burdens that interventions such as physical distancing
might distribute to those already vulnerable as well as across many
social domains.
VULNERABLE
The Law, Policy and Ethics of COVID-19
- Titel
- VULNERABLE
- Untertitel
- The Law, Policy and Ethics of COVID-19
- Autoren
- Vanessa MacDonnell
- Jane Philpott
- Sophie Thériault
- Sridhar Venkatapuram
- Verlag
- Ottawa Press
- Datum
- 2020
- Sprache
- englisch
- Lizenz
- CC BY-NC-ND 4.0
- ISBN
- 9780776636429
- Abmessungen
- 15.2 x 22.8 cm
- Seiten
- 648
- Kategorien
- Coronavirus
- International