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As far as persuasive goes, the entire film was very convincing of the fact that the doctors were under-resourced and over-worked. The part where the doctors were trying to perform a surgery and didn't have the right kind of drill to relieve the pressure in the brain was pretty compelling. Here we would never consider drilling into someone's brain without the proper sterilization, apparatus, or drill, but in such a low resource clinic, its the only option. That just shows how desperate the doctors were to perform their craft andbest serve their patients. Another part that was convincing was the portion where the doctors argued about reusing gloves. It was a bit hard to understand the argument, as the concept is just baffling to me as a hcp, but the fact that they had to disagree over washing and reusing gloves is proof of their desperation.

The article explains how a team of medical staff treated (and consequently killed) a number of patients following the flooding of a hospital in New Orleans. The staff in question overdosed the patients to put them out of their pain as they saved other patients who were more likely to survive. The article calls into question the process of triage and how we go about it. Who has the authority to make these decisions, and what lines do we draw between ethics and compassion. The article provides a play-by-play of the events leading up to the flooding, and relevant policies that existed and have been created related to this incident. 

The author seems to rely strongly on personal experience and belief to make broad statements about the situation following chernobyl. Most of the article is about the author and their experience with the issue, rather than the objective data and observations of others. This makes the arguments seem rather close-minded and almost biased. 

The app serves as a platform for medical professionals to share rare cases and conditions they have treated.

This policy is specific to the Bethel Township EMS and Fire Department, but other groups on the US have similar policies. Its a bit of a hot topic. 

The program was created in reaction to the disaster at Fukushima-Daiichi, with influence of the lessons learned post-bombing in Hiroshima. Hiroshima University specializes in radiation casualty medicine and works to improve medical care in response to nuclear emergencies. This program was specifically made to generate leaders capable of directing relief efforts while keeping the clear goal of reconstruction post-disaster. 

Food stamp (SNAP) rolls increased over the years, and the article addresses that this is a sign of poverty.  The USDA is an agency that administers food stamps.

In Baltimore, researchers found that racism and poverty especially affected African Americans without insurance. In order to address this, they removed boundaries to care within the medical system and community so that poor patients could receive the care they needed without economic trouble. Along with this, they also established a system that relied on the community as a whole for care, taking the social stigma away from AIDS/HIV care and building ties as a whole. Within a few years, many disparities disappeared among the studied population.

Another study in rural Haiti was used to develop the PIH model of care. This model relies on an accompagnateur who is trained in drug delivery and supportive care. This allows care to be given within a village, not a clinic, and improves access to care. This model has worked to improve patient care and outcome in Haiti, Peru, and Boston.

In Rwanda, structural violence has perpetuated to transmission of disease from mother to child for decades. Access to resources such as clean water and formula, along with public health agencies promoting the merits of breastfeeding, have made it challenging to address MTCT. However, when researchers asked mothers if they would like these resources, they were eager to receive them and wanted to help in preventing further transmission. 

The data acquired in this study can be used not only for improvement in policies and training for healthcare workers, but also to examine the risk factors for the disease. One example is the age and gender disparities in those nfected. These could be explained by the typical age and gender of healthcare workers, but could also show a trend in risk when coupled with patient data. The data on the districts and their infection rates can be used to help pinpoint the origin of infection.