Week 8 Flashcards

1
Q

outbreak

A

An outbreak or epidemic exists when there are more cases than expected of a particular disease among a specific group of people and/or in a given area, over a particular period of time

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2
Q

pandemic

A

world wide epidemic

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3
Q

epidemic

A

more cases than usual

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4
Q

outbreak

A

same as an epidemic; may be smaller number of cases, area or population

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5
Q

cluster

A

group/aggregation of cases usually in one specific location

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6
Q

endemic

A

permanent/regular disease incidence

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7
Q

why do outbreaks occur?

A

New appearance of an infectious agent (Or toxic material) from the environment or from an infected source
Arrival of susceptible people to an environment with an endemic pathogen
Introduction of effective route of transmission from source to susceptible population (e.g. climate change bringing new mosquito species)

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8
Q

oubtreak investigation had

A

primary goals
secondary goals
factors that impact our process and decision making

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9
Q

Outbreak investigation- primary goals

A

Identify pathogen or source
Control
Prevent future outbreaks
All the above in a timely manner

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10
Q

Outbreak investigation- secondary goals

A

Learn more about a disease

Training opportunity

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11
Q

Outbreak investigation- factors that impact our process and decision making

A

Case numbers
Disease severity
Risk to others
public/political/legal concerns

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12
Q

Steps of an outbreak investigation

A

Prepare for field work
Verify the existence of the outbreak
Confirm the diagnosis
Define and identify cases
Describe/orient data (person, place, time)
Develop hypotheses
Evaluate hypotheses
Refine hypothesis/perform additional studies
Implement control and prevention measures
Communicate findings

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13
Q

Step 1: prepare for field work

A
Epidemiological knowledge and homework 
What are the usual risk factors? Previous outbreaks? 
Supplies and equipment 
Competent laboratory 
Portable computer, phone, supplies 
Team composition 
Who should be in team? Who is in charge? 
Statistical advisors, public relations, local information 
Administrative 
Transport and communication 
travel, cash, credit cards 
immunisation, prophylaxis 
Personal
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14
Q

Step 2: verify existence of outbreak

A
Defined as ‘more cases than usual’ 
What is ‘usual’? 
Must have access to baseline data 
Specific to region 
Specific to current time 
Where are the cases? 
Surveillance: monitoring of disease in populations 
passive, active, sentinel (targeted) surveillance 
Sources of information: 
Surveillance records 
local/state health departments 
Other registries (Hospital discharge records, death records, cancer or birth defect registries)
Clinicians 
Labs
Schools
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15
Q

Some causes of false alarms

A

Change in surveillance/policy of reporting
Change in case deifinition
Improved diagnosis (new test, increased GP awareness, new doctor in town)
False positives from errors in diagnostic tests
Increased public awareness (media coverage leading to demand for tests)
Increased reporting (performance incentives)

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16
Q

Step 3: confirm diagnosis

A
Review clinical findings 
Review lab results of cases 
Be as specific as possible about the causative agent
‘outbreak strain’ of bacteria/virus 
May need specialised lab input 
Talk to cases
17
Q

Step 4: define and identify cases

A

Case definition is important and can change
Sensitive vs specific
Components include:
Clinical features (bloody diarrhoea)
Person- who to include and exclude
Place- place of residence, where they ate
Time period of interest
Lab results
Divide into:
Confirmed- usually lab confirmed
Probable- lab results not available
Possible- often less stringent clinical criteria
Case finding
Use as many sources as you can
Health care facilities and labs
Alert the public and ask cases to identify themselves
Identify people in place of interest at time of potential exposure and directly contact them

18
Q

Barriers to case detection

A
Lack of public understanding 
Lack of communication with the public 
On existence of outbreak 
On role of imported health care workers 
Community distrust 
Lack of inclusive planning for outbreak resolution
19
Q

Step 5: describe and orient the data

A

Time: draw an epidemic curve
Number of cases on y axis
Time on x axis
May provide hints about source of outbreak
Place: map the data
Person: explore data according to personal characteristics

20
Q

Steps 6-8: develop/test/refine hypothesis

A

What is the source of the infection?
Case control or cohort study?
Other investigations?

21
Q

step 9: control and prevention

A
Once source of outbreak has been identified, aim to break links in chain of infection 
Do as soon as possible 
Examples: 
Remove contaminated food 
Sterilise contaminated water 
Spray mosquitoes/destroy breeding sites 
isolation/treatment of cases 
Immunise contacts/susceptibles 
Prophylactic medication 
Behaviour modification
22
Q

step 10: communicate findings

A

Must occur throughout outbreak investigation
Investigation team/partners/press/public
Prepare timely reports
Initial oral briefing (at time leaving the field)
Final written report
Publications
Clearly state facts
Beware of legal implications
Aim to improve practice

23
Q

Down stream factors

A

helping done in the moment
road design, safety enforcement, excessive speed, driver fatigue, alcohol consumption, use of illicit drugs, use of a mobile phone, absence of effective trauma care

24
Q

upstream factors

A

what is done to prevent happening again
car use as influenced by fossil fuel energy policies, taxation on alcohol, policing traffic laws, resource allocation to hospital trauma units

25
Q

linear regression

A

outcome variable must be continuous

exposure may be numerical or categorical

26
Q

strong negative

A

-0.8 - -1

27
Q

moderate negative

A

-0.5 - -0.8

28
Q

weak negative

A

0 - -0.5

29
Q

weak positive

A

0 - 0.5

30
Q

moderate positive

A

0.5 - 0.8

31
Q

strong positive

A

0.8 - 1

32
Q

linear regression assumptions

A

Outcome variable follows normal distribution (evaluated using histogram or box plot)
Relationship between outcome and covariate is linear
Constant variance of outcome across different values of the covariate remains the same across different values of the covariate

33
Q

residual/prediction error

A

difference between observed and predicted values

34
Q

coefficient of determination

A

r^2