POL101Y March 26th.docx

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14 Apr 2012
POL101Y March 26th
- Early 2003, in the Guangzhou outbreak one third of infected patients were health care workers,
including Dr.L.J.K, went to Hong Kong and on the flight infected someone who went to Toronto,
who infected all of Toronto and so on
- Diagnosis?
- History of exposure…and fever above 38 degrees celcius
- Cough,dyspnea
- Malaise,myalgias
- Diarrhea
- And others…but no definitive markers and no consensus
- Treatment: isolation, ventilator support, antivirals,corticosteroids
- Sars is caused by a coronavirus, a virus that similarly cause a common cold type of syndrome
- Sars is a zoonosis, a disease that travels from animals to humans, very hard to get insight on the
disease if it never existed in human history
- November 2002 to july 2003
- 8098 people worldwide probably had sars in 29 countries and 774 died
- Canada: 438 probable cases, 44 deaths (all in Toronto)
- Flu kills 750-2500 canadians a year- triple that number of sars
- Learning from sars: renewal of public health in Canada
- National advisory committee on sars and public health
- Mandate: Draw lessons from sars outbreak, and explore longer term approaches on how best to
enhance canada’s response to future public health challenges
- Public health: under supported for 20+ years, multiple reports ignored
- Broad population health challenges
- First nations and Labrador inuit 62% overall: Canadian counterparts- 31
- Political leadership matters (clement (minister of health at the time, chretien etc.)
- We did learn something! H1N1 2009-2010
- Government machinery matters
Unprecedented Politics: Mitigating risk in an uncertain world
- There was great uncertainty about the cause cholera
- Value at risk (VAR) model
- Risk analysis: VAR of $100 million with 99% confidence
- Took all of the variables that affect the market and through a math equation made it into one
number that showed the chance of losing or not losing the total value of your investment
- Measurement of market confidence
- Systemic equilibrium
- The VAR model is great for normal times (assumes normal distribution)
- What about the 1%?
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