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Froggie wrote:

roykim wrote:I know that the rules for the next season aren't out but at least for this season, were their any instances where competitors had to apply Kaplan-Meier analysis to given data?

I did disease for two years and I don't know what that is.

B division barely has statistical analysis anyway, so you're good

This might be a little bit early, but should participants in Division C know Koch's Postulates? I'm new to this event and did research on everything mentioned in 2019's rules, which included Hill's criteria for causality; thus, is it necessary to research the postulates? Also, this question has definitely been asked already, but to what extent do participants in Division C need to understand statistical analysis? Thank you!

jxxu20 wrote:This might be a little bit early, but should participants in Division C know Koch's Postulates? I'm new to this event and did research on everything mentioned in 2019's rules, which included Hill's criteria for causality; thus, is it necessary to research the postulates? Also, this question has definitely been asked already, but to what extent do participants in Division C need to understand statistical analysis? Thank you!

It wouldn't hurt to know Koch's postulates, as it may come up as it comes as part of the history of epidemiology, but I haven't seen it on a Div C test as of yet.
The wiki is a good place as it lists what advanced statistics are important, but doesn't really explain how to use those. I'm pretty sure the advanced statistics are covered in the WHO textbook, and are likely also covered in the CDC textbook. Tests can basically give you a set of data and ask you to apply a statistical analysis measure to it, so knowing the advanced stats is pretty helpful.

amk578 wrote:

jxxu20 wrote:This might be a little bit early, but should participants in Division C know Koch's Postulates? I'm new to this event and did research on everything mentioned in 2019's rules, which included Hill's criteria for causality; thus, is it necessary to research the postulates? Also, this question has definitely been asked already, but to what extent do participants in Division C need to understand statistical analysis? Thank you!

It wouldn't hurt to know Koch's postulates, as it may come up as it comes as part of the history of epidemiology, but I haven't seen it on a Div C test as of yet.
The wiki is a good place as it lists what advanced statistics are important, but doesn't really explain how to use those. I'm pretty sure the advanced statistics are covered in the WHO textbook, and are likely also covered in the CDC textbook. Tests can basically give you a set of data and ask you to apply a statistical analysis measure to it, so knowing the advanced stats is pretty helpful.

You should know what Koch's Postulates are.

I'm not sure what you're meaning by advanced stats though. Which statistics/tests are you referring to?

Hi, I was wondering if anyone could please explain how to find the predicted date of exposure based on just an epi-curve? (with no info about the actual disease). Thanks!!

astercats7 wrote:Hi, I was wondering if anyone could please explain how to find the predicted date of exposure based on just an epi-curve? (with no info about the actual disease). Thanks!!

That seems impossible unless you have some knowledge of the incubation period of the disease so that you can count back from the peak of the epidemic (assuming a point source epi-curve)

UTF-8 U+6211 U+662F wrote:

astercats7 wrote:Hi, I was wondering if anyone could please explain how to find the predicted date of exposure based on just an epi-curve? (with no info about the actual disease). Thanks!!

That seems impossible unless you have some knowledge of the incubation period of the disease so that you can count back from the peak of the epidemic (assuming a point source epi-curve)

(Disclaimer: I don't know how true this is) I've read somewhere that the units of the x axis (the time) is equal to 1/4 to 1/3 of the incubation period of the disease. Say for example the units on the bottom of an epi-curve is 4 days between each mark (ex. month is January, and starts with 3, then 7, then 11, etc), then the incubation period for the disease is likely 9 to 12 days, and from there you can count back 9 to 12 days from the peak of the epidemic and find the predicted date of exposure?

warning im also really bad at this event don't take this into account 100%

UTF-8 U+6211 U+662F wrote:

astercats7 wrote:Hi, I was wondering if anyone could please explain how to find the predicted date of exposure based on just an epi-curve? (with no info about the actual disease). Thanks!!

That seems impossible unless you have some knowledge of the incubation period of the disease so that you can count back from the peak of the epidemic (assuming a point source epi-curve)

That’s what I thought lol

Anomaly wrote:

UTF-8 U+6211 U+662F wrote:

astercats7 wrote:Hi, I was wondering if anyone could please explain how to find the predicted date of exposure based on just an epi-curve? (with no info about the actual disease). Thanks!!

That seems impossible unless you have some knowledge of the incubation period of the disease so that you can count back from the peak of the epidemic (assuming a point source epi-curve)

(Disclaimer: I don't know how true this is) I've read somewhere that the units of the x axis (the time) is equal to 1/4 to 1/3 of the incubation period of the disease. Say for example the units on the bottom of an epi-curve is 4 days between each mark (ex. month is January, and starts with 3, then 7, then 11, etc), then the incubation period for the disease is likely 9 to 12 days, and from there you can count back 9 to 12 days from the peak of the epidemic and find the predicted date of exposure?

warning im also really bad at this event don't take this into account 100%

Thank you so much!!

This is my first year doing disease detectives, so I do not know much about this event other than what I read. However, it seems that the topic switches year to year. Does anyone know what the topic is for the 2019-2020 year?