A Critical Review and Evaluation on a 2006 Anthrax
Preparedness Study
Reducing Mortality from
Anthrax Bioterrorism: Strategies for Stockpiling and Dispensing Medical and
Pharmaceutical Supplies
by D. Bravata et al. 2006
How antibiotics and medical supplies are
stockpiled and dispensed is critical in an effective response to an anthrax
bioterrorism attack. As seen from recent history, this is a very real
possibility that requires adequate regional and national preparation. Since there
is a lack of unanimous consensus on how to achieve this, Bravata et al’s model
aims to evaluate the costs and benefits of alternative strategies for
maintaining and dispensing local and regional inventories of antibiotics and
medical supplies for responses to the aerosol release of Anthrax utilizing an
Excel based compartmentalization method followed by a Monte Carlo sensitivity
analysis. Bravata et al looks at four different strategies including strategies
enhancing bioterrorism event detection, increasing local and regional dispensing
capacities, increasing local inventories of antibiotics, and increasing the
national inventories deployed to the site of an attack. The model reveals that
following an outbreak, mortality is critically dependent on the local
dispensing capacities, that cost-effectiveness of some strategies to prepare
for bioterrorism is sensitive to the probability of a bioterrorism attack and
the rate of adherence to treatment, and that when dispensing capacity is low,
surveillance strategies to enhance attack detection does not result in reduced
mortality. On this same run of thought, VMI times only matter where there is a
large dispensing capacity and treatment adherence rate. Bravata et al’s work is
logically sound and even without a quantitative model, common sense is a good
validation of her results; however, there are things that can be both improved
upon and interesting questions that Bravata’s work underscores.
It is clear from the model and
discussion of the results that the answer to whether or not a given strategy is
cost-effective or is largely dependent
on the rate-limiting step which could either mean the adherence, dispensing
capacity, probability of an attack, and even the extent/scope of the attack.
Bravata does a great job in highlighting this variability; however, what might
be more useful and even worthwhile is doing this same simulation given the probability
of an attack based on geographical location. It is of no doubt that there are
certain areas of the US that are more predisposed to a bioterrorism attack than
others. Also, the model simulates a society where there are 5 million people.
It would be worthwhile to see how cost-effectiveness of different strategies
vary depending on the size of the local area—for example an urban area versus a
rural area. In general, most response strategies have only looked at urban
areas and have not included rural communities, where cost-effective strategies
are sure to be different. To that end, I
believe that this study should research probabilities of bioterrorism exposure
given each geographical location based on population and probability of attack
to make the model more precise and conclusive in this balancing act, though as
discussed in an earlier blog post, delineating these probabilities can prove to
be difficult. Another interesting study point for the future would be to look
at adherence of treatment stratified by age. Is there a more effective strategy
on what population should receive antibiotics first?
The things aforementioned are things to
be considered as next steps from this initial model; however, within this model
are a few limitations. It does not consider the events in which the anthrax is
antibiotic resistant, multiple attacks at once which may affect the VMI and
Push Pack(MedKit) delivery, the addition of a low-cost antibiotic, or anthrax
vaccines. This study may also be out of date given the recent advancement in technology.
In terms of national security, it would make sense to update the model with
current parameters and data. Based on a few of the data points the study
mentions, the following few blog posts will deal with assumptions and
conclusion made by the study.
The study mentions that in its
evaluation of the most effective and cost-effective strategies in dispensing
medical treatment after an anthrax bioterrorism attack, it did not consider
anthrax vaccine as a treatment option. The use of vaccine may improve treatment
adherence rates, thus lowering mortality rates. To this end, we will explore
vaccination as a countermeasure to such an attack and its potential impact. Next,
the study notes that the strategy of sending additional Push Packs to the
attack site until the VMI becomes available only results in a small reduction of
mortality. As such, it may be interesting to see other effects of Push Packs,
especially in a low-scale attack when not as many individuals require prophylaxis.
Furthermore, Push Packs only seem to have an effect on reducing mortality if
they were to arrive at the attack site 12 hours after initial request. In the
event that there is a delay, it is clear from the paper that Push Packs do not
have an effect on reducing mortality rates, but are there alternatives to
salvaging a delayed shipment of push packs? Are there any other negative or positive
externalities with its existence? Finally, although the study models that
surveillance strategies to enhance detection do not result in reduced mortality
when dispensing capacity is low, it does make a marked reduction in communities
with high dispensing capacities through ongoing syndromic and environmental
surveillance. An exploration of different surveillance strategies and their current
limitations may help realize needs for future generations of biosurveillance
programs.
____
Bravata,
Dena M., Gregory S. Zaric, Jon-Erik C. Holty, Margaret L. Brandeau, Emilee R.
Wilhelm, Kathryn M. McDonald, and Douglas K. Owens. "Reducing Mortality
from Anthrax Bioterrorism: Strategies for Stockpiling and Dispensing Medical
and Pharmaceutical Supplies." Biosecurity and Bioterrorism 4.3
(2006): 244-62. Print.
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