(From Behavioral, Sept 2000, by Brian Buschman)
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1o prevention of illness is through health education and preventative measures to stop people from getting sick in the first place.
2o prevention is prompt recognition and treatment of the illness. This is often done through screening and general physicals.
3o prevention is through rehabilitation and working to limit the spread of the disease.
Epidemiology is the study of distribution and determinants of disease it is based on the assumptions that:
1) Disease does not occur by chance.
2) It is not randomly distributed in the population.
1) Descriptive studies evaluate the distribution and trends of a disease.
2) Analytic studies find causal relationships between diseases.
3) Experimental studies are those such as vaccine and therapy studies.
1) Explain why epidemics occur
2) ID health needs
3) ID why disease epidemics occur
4) Establish criteria for diagnosis.
5) Evaluate health programs.
6) Predict future health needs.
1) Etiologic agents like bacteria, virusus and such are needed.
2) A reservoir with the etiologic agent can propagate such as in the human body. They may be symptomatic or asymptomatic.
a. Convalescent carriers are asymptomatic but still carry the disease.
3) Portal of exit is how it gets out of one person and into another. They include:
a. Respiratory tract.
b. GU
c. GI
d. Skin
e. In utero
4) Methods of transmission may be direct contact, droplet spread, vector spread (virus, tics, etc) vehicle spread (toys, door know) or aerosol.
5) Portal of entry may be any of the methods of entry.
6) Requires a susceptible hose.
The epidemiological triangle demonstrates three parts that must exist for an epidemic to occur. They are an agent, a host and the environment where the agent can spread.
Type I curves graph the occurrences that come within one incubation period. They help determine the number infected at a given time and place.
Type II curves graph the total cases across multiple incubation periods.
Sensitivity is trying to rule in all cases.
Selectivity is trying to only rule in true positives. (Trying to rule out.)
Positive predictive value is the chance that a positive test is actually a positive case.
Negative predictive value is the chance that a negative test is actually negative.
Accuracy is the percentage of the people that are correctly identified.
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