measuring health & disease Flashcards
false + vs false −
false positives can be caused by:
- similar disease agent ➞ confusion
- previous exposure
- lab/test error
- ensuring low false positives important for diseases w/ $$ tx or tx that cause suffering
false negatives can occur from:
- timing ➞ early in subclinical stage ➞ might not be long enough for immune system to begin response
- immunocompromised indiv don’t produce antibodies so tests cannot pickup
- ensuring low false negatives important for highly transmissible & severe diseases with extreme consequences
- ex: PRRS
proportion of the population diseased and exposed
proportion of the population exposed
proportion of the population diseased
true prevalence
actual level of disease prevalence in the pop
* cannot know ➞ estimate using AP
apparent prevalence
what prevalence appears to be based on the test
* how many people in the pop that T+
sensitivity
proportion of D+ that T+
* how accurate the test is at identifying diseased indiv
* ↑ Sn ➞ indiv that T+ are D+
specificity
proportion of D− that T−
* how good a test is at identifying non-diseased indiv
* ↑ Sp ➞ indiv that T− are D−
predictive value
probability of disease given the test result
positive predictive value (PPV)
probability/proportion of T+ that are D+
negative predictive value (NPV)
proportion of animals who T− that are D−
↑ prevalence =
↑ PPV & ↓ NPV
more dis in pop ➞ more indiv will T+ so less indiv will T−
↓ prevalence
↓ PPV & ↑ NPV
less dis in pop ➞ less indiv will T+ so more indiv will T−
AP < TP
underestimates TP of disease ➞ more false T− so D+ are missed
AP > TP
overestimates TP of disease ➞ more false T+ so D− animals are falsely dx
what measures do we use to quantify disease in populations?
- amount of dis
- morbidity: # of infxt - mortality: # of deaths from dis
- temporal distribution
- geographic/spatial distribution
- prevalence
- incidence
- cumulative incidence
- approximate incidence
prevalence
number of instances in a known pop at a specific point in time
* snapshot in time
* diseases with long durations
* identifying common dis in pop
* evaluating control strategies
incidence
number of new cases in a known pop over a period of time
* preferred over prevalence
* dis w/ short durations
* important for:
* understanding disease development and transmission (temporality) * predicting risk of disease (change in health status)
cumulative incidence
proportion of non-dis animals at beginning of study that become dis during the study
* aka avg risk of developing disease during a time period
* who is getting diseased over time
* risk of disease
incidence rate
how quickly new cases develop over time
* closed pop only
closed populations
defined for entire study ➞ no additions or loses
* more control
* less bias
* dis-free animals at start = at risk
* preferred over open
open populations
animals enter/leave throughout duration of study
* hard to keep sample size ➞ difficult to track long term
* stable only if additions = withdrawals over time
* not as rigorous
* cannot calculate disease risk from open pop
study designs
descriptive: describes
* summarize & describe data
* no comparisons
* hypothesis generating
* frequency & distribution
* cannot make conclusions about associations btwn E & O
1. case report: rare or new conditions/dis involving 1-2 animals
2. case series: collection of an (4+) w/ same rare condition/dis
3. descriptive surveys: to estimate freq & percentages of diff variable
analytical: compares
* explore relationships & associations
* test hypotheses
1. experimental: control treatments & manipulate envir
2. observational: natural experiments
-no control over treatment or animals
-no manipulation of envir
-focused on exposures (E) & outcomes (O)
