DISCUSSION 1
1. This covers a lot of information from the history of epidemiology through in-depth topics on how to appropriate evaluate disease occurrence through quantitative means. This discussion, you need to build a community health profile of the deficits in your community. Community Health Assessments (CHA) and Community Health Improvement Plans (CHIP) have become all the rage in health departments. The Centers for Disease Control and Prevention have required every health department to engage in CHIPs and CHAs as a part of their accreditation process.
There are robust sets of aggregated data out there both in raw form that you can download and manipulate on your own or in a pre-digested mode that has already been summarized and provided for you. Some resources that you may find helpful:
- Kids Data
- CHIS
- County Health Rankings
- BRFSS
- CDC Wonder
- YBRSS
You can use as many or as few of the above resources as you want, or you can use Journals and other data sources to help you meet this requirement.
In this discussion, you are going to assess a community of your choosing (County or State level) and select two areas in which they have poor data outcomes. You will then compare either the County to the State or the State to the Nation to build you evidence that there is an issue. This post must contain some measurement of epidemiology in some fashion. It cannot be subjective and it must be based on rates, ratios or some other type of quantitative measure. The initial post must be between 350 - 500 words
DISCUSSION 2
2. We are exploring sensitivity and specificity . This can let you know the limitations of a test for a disease. More and more labs, hospitals, and public health agencies are moving to molecular methods to test for disease, but often for screening tests we use test like EIA or other rapid immunogenic tests.
Your goal:
Select a disease
- Find the prevalence of that disease in the US
- Find a screening test for that disease and the manufacturer's reported sensitivity and specificity
- Apply that proportion to a random population of 100,000 people
- Calculate the predictive positive value and the predictive negative value
- Answer the question: Does it make sense to screen for this disease using this test and based on the natural history of the disease why or why not?
Example: How to work the math alone
Disease X occurs at a prevalence of 10 per 100,000 population.
Screening test Y has a sensitivity of 95% and a specificity of 80%.
Step 1:
|
|
Disease (+)
|
Disease (-)
|
|
Test (+)
|
95%
|
20%
|
|
Test (-)
|
5%
|
80%
|
|
|
10
|
999,990
|
Step 2:
|
|
Disease (+)
|
Disease (-)
|
|
Test (+)
|
9.5
|
199,998
|
|
Test (-)
|
.5
|
799,992
|
|
|
10
|
999,990
|
From this point, you can easily calculate the predictive positive and the predictive negative values. The real challenge is going to look at the natural history of the disease, cost of the test, treatment of the disease and determine if screening is appropriate. If it is appropriate or not, you have to provide researched justification as to why it is not or is and if there are certain groups it would be best to screen or prioritize why or why not.
All research should be cited and appropriately supported.
The initial post must be between 350 - 500 words
DISCUSSION 3
3. We are exploring study designs. The textbook has a list of limitations of various study designs. Your goal for this week is to look up a recent article in the NU library. It must be a primary peer-reviewed article, no meta-analysis or review articles are acceptable. In the discussion section of the article, there should be a discussion of the limitations of this article. How do these limitations compare to the limitations presented in the textbook?
In a post that is at least 350 words, please summarize the article, the limitations, and reflect on where the authors may have missed some limitations based on the textbook readings.
The initial post must be between 350 - 500 words
DISCUSSION 4
4. Analytic epidemiology is all about looking at risk factors for specific diseases. We have measures such as relative risk, odds ratio, population attributable risk etc. Select a disease that interests you and evaluate 3 to 4 primary peer-reviewed articles or meta-analyses on the disease. Report back on what the measures of association are for this disease. Do articles report different values for the same exposure? Why might this be?
The initial post must be between 350 - 500 words
DISCUSSION 5
5. This week you were introduced to three complex theories that are used to advocate for a cause and effect relationship between exposures and diseases. These three models of cause and effect are:
- Hill's Criteria for Causation
- Rothman's Pie Model
- Web of Causation
Each of these models can be worked for a specific exposure and disease relationship to make an argument for a causal relationship. In this week's discussion, you are going to select a specific cause and effect model and apply it to a disease of your choice. Please note that you will have to be specific. Remember, epidemiology is a quantitative discipline. If you are going to talk about strengths of association you are going to have to discuss the results sections of the articles that you are reading.
Hill's Criteria Guidance
If you are going to select HIll'scritiera you will have to write a brief paragraph justifying a specific exposure and disease relationship. You will need to use journals, meta-analyses, and web sources to answer each criterion. If you have an issue understand the criteria or how to answer it precisely, please reach out to your instructor immediately. Hill's criteria will work on any disease.
Rothman's Pie Model Guidance
Instead of selecting a single cause and looking at the role it plays in disease causation, you will be looking at the interplay between many different cases and using the terminology gone over in lecture to apply it to the disease you selected. Also, think of the PAR statistic. How could that be used to explain the slice of the pie that any one given risk factor explains the largest proportion of the etiology of the disease. This model works best for chronic diseases either communicable or non-communicable.
Web of Causation Guidance
You will need to include a picture of the web for your specific disease, and then explain the web and how each of the factors interrelate. Also, think of the strings in the web. Some studies will show you the statistics of association of each string in the web. You will definitely want to work in statistics into this post, as with the other selections. You will need journals and websites to assist you here.
The initial post must be between 350 - 500
DISCUSSION 6
6. We will be exploring policy evaluation. Now, as we have discussed in the Collaborate sessions there is a hierarchy in study design. Random Clinical Trials have the least threats to internal validity, but depending on how they were sampled could have the greatest threats to external validity. As we evaluation epidemiological and experimental literature, you will begin to notice that no single policy or program is made from a single publication.
The United States Preventative Services Task Force (USPSTF) are responsible for performing huge meta-evaluations of policies regarding screening and other preventative medicine practice.
Go to the USPSTF's website:
https://www.uspreventiveservicestaskforce.org/
Select a disease or a health policy and read their statements. Also, read what their grading system means. What are your thoughts on the stance they have taken given the literature they evaluated to come to their decision? What types of research or other organizations have you found that disagree with their stance? What additional research needs to be done to provide a more definitive answer, if any?
The initial post must be between 350 - 500 words