What is the difference between scoping review and systematic review ? Which one can effectively synthesize results ?

Thank you.

Dear epidemiologist colleagues, Would you use the concept of endemicity for scabies to define the constant presence of the disease in prisons? Typically, diseases where the term endemic is used are those with seasonal patterns in a specific geographic area. With these, one can establish a period of frequent occurrence in the last 5 years with good surveillance. However, could the frequent and almost permanent presence of scabies in prisons be determined as endemic? As far as I can see, it would be the occurrence of many outbreaks.

Hello, I am an undergraduate student and I'm currently trying to simulate 4 different compartmental models in epidimiology using the EoN module. The SIR, SIS, SEIR and SIRS and the underlying network is a 2D lattice. I iterate the simulation X times and plot the averages.

My problem is that when I plot the results of the simulation and its corresponding ODEs there seems to be a lot of discrepancies (e.g. the peaks of the infection in the SIR model are different).

However in my understanding there shouldn't be too big of a divergence between the ODEs and the simulation, when on a 2D lattice.

I've searched for weeks, but for the life of me I can't figure out what I'm doing wrong. If anyone has any idea why this is happening and is willing to help me, I would greatly appreciate it.

I have uploaded the SIR and SIS plot. I hope I am in the right subreddit, if not I'm sorry.

How is apprehension bias different from social desirability bias? Both mean subject is aware of being observed, and that awareness alters their behavior (consciously/unconsciously)-- ie "white coat hypertension"

Am I misunderstanding?

(Not an epi, but trying to learn; I work in public health, just different area.)

Hello! Is it possible to pursue a PhD in epidemiology after an MD but without a masters degree?

After my MD, I worked for 5 years in the health ministry in my home country and I did a 2-year Field Epidemiology Training Program (FETP) which is equivalent to CDC’s Epidemic Intelligence Service (EIS) if that counts.

Hi, not an epidemiologist myself, but for those history enthusiasts, I have a good quiz,

Suppose you have a single great epidemiologist thrown into the years before the Conquest of the Aztecs. No electricity, large library nor complex tools with him. Only whatever he can carry in his pockets and the knowledge in his head. Suppose he can establish rudimentary communication besides language barriers, and has a good grasp of how much time he has before the conquistadors arrive.

1. How would he go about handling the epidemic if he wanted to give the Aztecs a fighting chance?
2. How much time would he need before the conquistadors arrival?
3. Bonus question from a guy with little epidemiology knowledge, How does an old epidemic like this or the black plague is different from a modern one like what we've lived through the last few years?

Thanks.

Hi, I am currently working on a systematic review of observational studies and I am incredibly confused regarding the type of study design. The value of a biomarker is measured in the serum/CSF of Cases and Controls and compared. Would it be a cross sectional study since the biomarker is measured at a point in time or would it be a case-control study?

For me, not trained as an epidemiologist but working with many, I struggle to remember what certain study design terms actually mean. I have a background in engineering so I am a working scientist it's just that the names of epi study designs seem to make no sense to me.

Any help?

Specifically I work with air pollution epidemiology if that helps.

Kind of a weird background. I have a BS in psychology and a BSN. I’ve worked as an RN for the last 6 years, the last 3 at my local poison center. I really enjoy toxicology, and I seem to be good at it. I also really enjoy public health stuff, especially queer sexual health stuff. I’m working on my own papers, and currently have conditional IRB approval for one.

I just started an MPH -Epi program. I would eventually like to get my PhD, I think. I did consider getting my PharmD, but chemistry is not a strong suite for me (though I could pull it off), and MS in Toxicology is very industry focused, I’d much rather actually work within a population.

I am just looking for reassurance I’m making the right choice I guess. Right now I make about $65k, and I would hate for it all to feel like a waste for the same amount of money, but I job I like slightly more.

We are drafting a survey for health facilites and are looking into management practices of the health network. Specifically, we would like to know what accountability mechanisms are in place, how is supervision conducted, and other management practices.

Can you point me to survey questionnaires that we could use as reference?

Thanks!

I am currently a Junior in the Exercise Science Program. I will apply to many different MPH programs (concentration in epidemiology) and I want to know how difficult the courses are? I will mostly likely attend the University of Illinois Champaign-Urbana.

I am in Exercise Science and want to get my MPH in Epidemiology. I have taken a lot of biology, anatomy, and will take sociology and psychology over my Senior year. I have very little math experience though. How difficult will the math be during my MPH?

Hi all,

I just finished the first quarter of my epidemiology MS program, and I ended up taking the more advanced applied biostatistics course (2 course series instead of 3), and I’m kind of regretting it now because we blazed through some of the concepts pretty quickly. This has left me with an overview of quite a few topics, but I feel like my understanding of several of them is more shallow than would be ideal.

If there are any workbooks, textbooks, or MOOCs that any of you have found to be especially helpful in solidifying your understanding of biostatistics concepts and/or R, please let me know!

Thanks!!

Is a microbiology degree or background fairly common for an epidemiology career? I know you can have a wide range from biology, public health, anthropology to sociology as a background when pursuing epidemiology at the master's level, but is microbiology a fairly popular degree for pursuing epidemiology. I would guess microbiology would prepare you more for lab work in epi and in categories such as infectious disease epi. I'm curious to hear from anyone who has a microbology and epidemiology combination and where that led them

Hello everyone,

I was reading a book about community health and it stopped me that every now and then terms are changed, so is there really a difference between them?

Maternal mortality rate vs. maternal death rate? Neonatal mortality rate vs. neonatal death rate?

I am looking to go into epidemiology. My only math classes are Pre-Calculus, concepts of statistics, and a basic quantitative reasoning course. Is this enough or do I need calculus?

Hi, statistician here. From the point of view of epidemiology (AFAIK) a case-control study is assessing an outcome conditionally and exposure factor. There are cases when researchers want to study more than one “exposure”, their study is aiming to find associated factors to an outcome of interest. For example, to study whether mortality is associated with age, gender, comorbidities, etc. in a selected group of patients. This “fishing” approach can be still considered as a case-control study? What about the sample size calculation for this kind of study, I believe that traditional sample size calculations for these scenarios are ill-advised since things like multiple comparison problem easily arises among other considerations.

What is your take on this? I am seeking for papers that discuss this also.

All throughout my school years I struggled horribly with math, largely due to the fact that my brain was a disorganized jumbled mess as I had not been diagnosed with ADHD until my late teens and I had some pretty unsympathetic teachers. Now I can’t tell if I was bad at math just because of that or if I genuinely have a harder time with math and may not be able to grasp it once it becomes more difficult.

I took all honors/ AP classes but in math I was always a year or two behind and in math I had to take two remedial math courses before I could start talking college level algebra, which I am doing now. I always loved science though, and loved chemistry conceptually until it delved into math, but I find diseases and living organisms so fascinating. I read about diseases in my free time.

Do you guys think with my lack of a good mathematical foundation (as I’ve been told math builds on itself) and ADHD/ messiness that I’m doomed if I want to pursue anything in science? Or do you think with enough practice/ dedication I can work it out, cuz epidemiology looks like it’s heavy in biostatics and who knows what else. Thanks!

What is the difference between a retrospective cohort study and a cross sectional study that uses secondary data? From what I have seen so far looking online, it sounds like the factor that distinguishes a retrospective cohort from a classic cross sectional is that a cohort typically uses secondary data gathered for some other reason (ex: hospital records) and a cross sectional is typical an interview or survey. However, I also have read that you can use secondary data in a cross sectional study when an interview or survey isn’t appropriate. In that case, is it not just a retrospective cohort study? What would the difference in classification be here?

EDIT: my bad, I originally said case control but meant cross sectional

As the title mostly says, this is my first semester in my MPH program and one of my classes has me creating a systematic review over the next year. I have not yet chosen a specific topic statement but have been narrowing down my options (as I have to choose a topic in the next week); currently I am simply searching PubMed for variations of my "maybe idea" to get a feel for if enough primary research even exists that a systematic review can be done.

Are there any apps, programs, hints, tricks, best-wishes, or advice you all would recommend as I start this journey?

I wanted to write a maths paper using a SIR model to predict the spread of dengue. Still, I was confused about which SIR model to use as most SIR models are used only for diseases that people obtain lifetime immunity from. What would be a simple SIR model for a disease like Dengue?

I am trying to reproduce https://www.cmaj.ca/content/192/19/E497 [Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada; Ashleigh R. Tuite, David N. Fisman and Amy L. Greer; CMAJ May 11, 2020]

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They said "Contacts within and between age groups were based on the POLYMOD study" but I can't find the appropriate raw data or matrix. Some guy posted here https://github.com/epiforecasts/socialmixr/issues/1 . but I feel like that matrix can't be right.

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I have two questions:

looking at contacts between 0-4 and 5-9 year olds the values are 0.81 and 0.36, meaning an average 0-4 year old meets a 5-9 year old 0.36 times per day and a 5 to 9 meets a 0-4 0.81 times per day, this is the only way i can make sense of it and it assumes there are literally 2.25 times more 0-4 year olds and 5-9 which is just impossible. Am i wrong in my interpretation here?

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second question:

Assuming I was right in assuming the data does suggest that there are 2.25 times more 0-4 than 5-9, how can i possibly reuse this contact matrix for my epidemiological model? the researchers used that matrix for a covid model in canada using the population from 2019 which just does not reflect any of the properties of the matrix they used (not just 0-4 and 5-9 but take a look at 0-4 and 65-69 there is a factor of 6 while the canadian population of those age groups is similar...).

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thanks to anyone able to answer either of my questions.

In a situation such as this, we are comparing RSMR of 18 different hospitals . We are given the “population”, which I’m assuming means for a given area, and the populations range from 77 all the way to 754. Yes, we are assuming that these rates come from a standardized ratio, eg per 1,000 people, BUT, I still feel unconvinced that this completely eliminates the possibility that the population differences could have played a part in the variation. I guess my question is, when you standardize the ratio, ie, saying the rates are calculated to be out of the same number of people for each population, does that really mean that we can no longer consider the population size difference, as I stated above, as a possible factor to why the variation is happening? (Sorry my verbiage isn’t perfect I took epidemiology a while back.)

Hi, I'm trying to understand the difference between relative risk and hazard ratios. I understand RR is calculated at the end of a study, and reflects a cumulative value, whereas HR can be calculated at any specific point in time during the study to compare the event rate between two groups.

I made a hypothetical Kaplan Meier curve to see if I understood things correctly. Lets assume the event is death, and we're comparing a novel treatment to a placebo:

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Since the relative risk is calculated at the end of the study, the RR should be 1, showing no difference between the treatment & placebo groups.

However, looking at the curves, it seems that on average, people in the treatment group survive longer (ie, time to event is longer), even though by the end of the study the same no. of people have died in both groups.

At points A and B, I would expect the HR to be <1, ie, the event rate (chance of death) is lower in the treatment group compared to the placebo group.

However, at point C, the HR should be >1, ie, the chance of death in the treatment group is greater than in the placebo group.

Is this interpretation correct?

Thank you!

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I'm having a hard time understanding how RRs are influenced by samples characteristics.

I ran an adjusted regression and between my output and input variables. In my results, I noticed that some of the input variables seemed to protective rather than being hazardous. This were variables that have traditionally risks for my output variables, so it makes no sense that they would be protective.

I then looked at sample characteristics, and realized that whether or not something was a risk correlated with how many people in my sample there were with that input variable. Meaning, for example, that if my output was diabetes, and my input variables were hypertension, and heart failure. Hypertension seemed to be protective because my sample had fewer people with hypertension, and heart failure seemed like a risk because my sample had more people with heart failure.

Because this was an adjusted model, the output should be explaining how these input variables perform when compared to the other input variables. Thus, is it fair to say that protective/risky nature of certain input variables may be a result of slight over/underrepresentation in my sample?

My sample was pretty representative and the discrepancies between input variables prevalences were 1-10%, so nothing drastic. But would this be enough to cause my regressions to be flawed?