Disease Detectives B/C

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Re: Disease Detectives B/C

Postby yang573 » January 11th, 2017, 5:20 pm

Something something no posts.

George sneezed in Lucas' face and Lucas caught his cold. Ptady, who was sitting across the room, also gets sick.

What two types of transmission are responsible here? Be specific.
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Re: Disease Detectives B/C

Postby Private Wang Fire » January 11th, 2017, 7:49 pm

Something something no posts.

George sneezed in Lucas' face and Lucas caught his cold. Ptady, who was sitting across the room, also gets sick.

What two types of transmission are responsible here? Be specific.
Are we gonna revive this :o (answer)
Lucas - droplet Ptady - airborne
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Re: Disease Detectives B/C

Postby yang573 » January 17th, 2017, 3:42 pm

Something something no posts.

George sneezed in Lucas' face and Lucas caught his cold. Ptady, who was sitting across the room, also gets sick.

What two types of transmission are responsible here? Be specific.
Are we gonna revive this :o (answer)
Lucas - droplet Ptady - airborne
That is correct. Your turn.
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Re: Disease Detectives B/C

Postby Private Wang Fire » January 17th, 2017, 4:23 pm

You are conducting a study on [some disease] when a helpful friend tells you age may be a confounding variable.

1. What is confounding?
2. How can you modify your study design to account for this?
3. Which test statistic would you use after data collection?
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Re: Disease Detectives B/C

Postby Unome » January 17th, 2017, 4:32 pm

Something that I know!
1. If a variable is associated with both the exposure being tested and the disease/treatment being studied, but is not causally related to the exposure, then it is a confounding variable, or confounder. 2. Stratify or match the participants by age group, or just restrict the study to a certain age group (though the second may create further confounders). 3. Not sure exactly what's being asked; is this asking for a type of statistical test?
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Re: Disease Detectives B/C

Postby Private Wang Fire » January 17th, 2017, 4:39 pm

Something that I know!
1. If a variable is associated with both the exposure being tested and the disease/treatment being studied, but is not causally related to the exposure, then it is a confounding variable, or confounder. 2. Stratify or match the participants by age group, or just restrict the study to a certain age group (though the second may create further confounders). 3. Not sure exactly what's being asked; is this asking for a type of statistical test?
yup! Number 3 should be:
Cochran Mantel-Haenszel (statistical test for stratified data) (idk how to calculate it or use tho lol)
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Re: Disease Detectives B/C

Postby Unome » January 18th, 2017, 5:17 am

About #3
Does that count as a test statistic? I always thought of those as being like Fishers exact or chi-squared, and Cochran-Mantel-Haenszel being a method of finding risk. And calculating it is iirc somewhat like a weighted mean using the total population of each stratum (I know this because my partner BS'ed it at the last tournament and got full credit - unfortunately her attempt at BS'ing a chi-squared problem didn't work as well :geek: )
In preparation for MIT, here's an [strikethrough]extended[/strikethrough] semi-extended case study (hopefully my question actually makes sense, I don't know much about writing these types of questions)
An investigator is collecting data on an outbreak of botulism in the town of Milford in southern Delaware. The investigator suspects that a steak joint in the town may have been transmitting the disease. The investigator determines that of the 12 living cases (3 cases have died, and the investigator couldn't find information about them) 7 of them can remember having eaten at the steak joint. Using as a control a sample of 18 people randomly selected from Sussex County (the southernmost of Delaware's three counties), the investigator determines that 2 of those people remember having eaten at the steak joint. 1. What type of study is this? 2. Give three potential sources of bias in the study, and explain how each of them affects the data. 3. Choose one of the sources of bias that you listed above and explain how the study should have been conducted to mitigate that bias. Assuming that the study was conducted accurately (without systematic biases) and the same data was collected: 4. Choose an appropriate measure of risk, explain why the measure is appropriate, and calculate it (show work). 5. Choose an appropriate measure of statistical significance, explain why the measure is appropriate, and calculate it (show work).
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Re: Disease Detectives B/C

Postby yang573 » January 21st, 2017, 7:34 pm

Yeah, I'd call CMH RR and OR as a form of analysis/adjustment rather than a statistical test.
answers of dubious correctness
1. case-control 2. rumination bias - exposure of controls may be underrepresented; Neyman's bias - dead not included, possibly underrepresenting the exposed group; interviewer bias - nature of questions asked may lead to overrepresentation of the exposed group 3. Neyman's bias: find a medium 4. Odd ratio is used because incidence can't be calculated. The actual size of the exposed group is unknown OR = ad/bc = [(7)*(18-2)] / [(12-7)*(2)] = 11.2 5. I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them. :P
My question is, how does a steak joint transmit botulism? Canned beef?
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Re: Disease Detectives B/C

Postby maxxxxx » January 21st, 2017, 8:12 pm

I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them. :P
On the statistics handout from soinc.org it lists the equation for z tests, so I'd assume we're expected to know how to calculate it. I'm pretty sure the only ones we're just supposed to understand are CMH, Fisher's Exact, and McNemar's.
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Re: Disease Detectives B/C

Postby yang573 » January 22nd, 2017, 4:20 pm

I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them. :P
On the statistics handout from soinc.org it lists the equation for z tests, so I'd assume we're expected to know how to calculate it. I'm pretty sure the only ones we're just supposed to understand are CMH, Fisher's Exact, and McNemar's.
Oddly enough, I've never been expected to complete a statistical test, but I've been asked to perform adjustments. At states last year, I had to do a CMH-RR.
but here you go
Assume the conditions have been met. H0: p = 1/2 HA: p > 1/2 significance level: 0.05 SD(p-average) = sqrt( (p-exact * q-exact) = sqrt( [(1/2) * (1/2)] / 30 ) = 0.00617284 z = (p-average - p-exact) / SD(p-average) = ((7/9) - (1/2)) / 0.00617284 = 3.042903097 p of z = 0.001172 p < 0.05 Reject the null hypothesis. The proportion of cases among exposed is greater than 1/2.
I'm not sure I trust those calculations.

While working on this problem, I found this interesting read: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2938757/ I'm not sure if a z-test is appropriate with a contingency table; a confidence interval may be more suitable

Thinking about it, I think a Fisher's Exact Test would also work.
calculations
Assume conditions are met. H0: a/c = b/d HA: a/c =/= b/d significance level: 0.05 p = [(a+b)! * (c+d)! * (a+c)! * (b+d)!] / [a! * b! * c! * d! * n!] = [9! * 21! * 12! * 18!] / [7! * 2! * 5! * 16! * 30!] = 0.008469611 p < 0.05 Reject the null hypothesis. There is an association between the exposure status and disease status.
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Re: Disease Detectives B/C

Postby Unome » January 23rd, 2017, 4:40 am

I think a z-test would do, because you're working with proportions rather than numbers. I believe you're only required to understand statistics and not expected to calculate them. :P
On the statistics handout from soinc.org it lists the equation for z tests, so I'd assume we're expected to know how to calculate it. I'm pretty sure the only ones we're just supposed to understand are CMH, Fisher's Exact, and McNemar's.
Oddly enough, I've never been expected to complete a statistical test, but I've been asked to perform adjustments. At states last year, I had to do a CMH-RR.
but here you go
Assume the conditions have been met. H0: p = 1/2 HA: p > 1/2 significance level: 0.05 SD(p-average) = sqrt( (p-exact * q-exact) = sqrt( [(1/2) * (1/2)] / 30 ) = 0.00617284 z = (p-average - p-exact) / SD(p-average) = ((7/9) - (1/2)) / 0.00617284 = 3.042903097 p of z = 0.001172 p < 0.05 Reject the null hypothesis. The proportion of cases among exposed is greater than 1/2.
I'm not sure I trust those calculations.

While working on this problem, I found this interesting read: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2938757/ I'm not sure if a z-test is appropriate with a contingency table; a confidence interval may be more suitable

Thinking about it, I think a Fisher's Exact Test would also work.
calculations
Assume conditions are met. H0: a/c = b/d HA: a/c =/= b/d significance level: 0.05 p = [(a+b)! * (c+d)! * (a+c)! * (b+d)!] / [a! * b! * c! * d! * n!] = [9! * 21! * 12! * 18!] / [7! * 2! * 5! * 16! * 30!] = 0.008469611 p < 0.05 Reject the null hypothesis. There is an association between the exposure status and disease status.
Yeah Fisher's Exact was what I was going for, although I'm really not sure whether that makes sense. And I have no idea how one could get botulism from cooked steak, I just made up the scenario randomly without putting too much effort into a realistic scenario. Anyway, your turn!
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Re: Disease Detectives B/C

Postby yang573 » January 23rd, 2017, 2:33 pm

A slightly less ambitious question:

Foodborne illnesses are often characterized by _____. List three.
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Re: Disease Detectives B/C

Postby Unome » January 23rd, 2017, 2:42 pm

A bit vague
- a single source of an infectious agent (though this is more applicable to outbreaks rather than the infection per se) - the presence of toxins (not sure if this is actually a thing, but it seems pretty common) - improper food preparation (again, more for outbreaks, but I can't think of anything else)
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Re: Disease Detectives B/C

Postby yang573 » January 23rd, 2017, 7:11 pm

A bit vague
- a single source of an infectious agent (though this is more applicable to outbreaks rather than the infection per se) - the presence of toxins (not sure if this is actually a thing, but it seems pretty common) - improper food preparation (again, more for outbreaks, but I can't think of anything else)
That works. I guess it wasn't that good of a question. I was thinking of short incubation periods, gastrointestinal symptoms, and point-source outbreaks (which you said)
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Re: Disease Detectives B/C

Postby UTF-8 U+6211 U+662F » March 20th, 2017, 1:30 pm

Reviving: What are the three things that characterize an agent's potential to spread and cause disease?


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