Introduction to Epidemiology: History, Terminology & Studies | Lecturio

[Music] hello and welcome to epidemiology one of the most exciting and fastest growing of the medical sciences of course I'm biased I'm an epidemiologist but maybe after you hear a little bit about it you'll feel the same way as me I think about epidemiology that makes us so fascinating is first of all in my opinion it's the only medical science that probably doesn't involve a hall of medicine and also some epidemiologists are sort of like medical detectives there on the ground collecting data talking to people solving mysteries about what causes a diseases in a population it can be quite sexy quite exciting kind of like a police investigator except around medicine so today we're gonna learn about the differences between descriptive and analytical studies in epidemiology we're a little bit about historical origins of Epidemiology where it came from and maybe even where it's going and we're also going to learn a little bit about the triumphs of FBI ology because I think it's important to brag a little bit about the things that we've done for society over the last couple of hundred years so when we talk about epidemiology is traditional to define it first it's difficult to define however this is one particularly popular definition is offered by the Centers for Disease Control in Atlanta Georgia and they say that epidemiology is the study of the distribution and determinants of disease or health status in a population okay Wikipedia offer is a little more complicated definition calling it the branch of medicine that deals with incidence distribution and so forth I would add in prevalence and mortality and so forth it gets complicated pretty fast and pretty dry most tests book definitions of epidemiology land somewhere between the two poles of the CDC in Wikipedia I will offer you another definition in my opinion it's the science of science or if you want to be a little drier it's the science of looking at the health of populations rather than of individuals hopefully this will all be clear to you or we're done the lecture our story begins in the early 19th century in London England when a man named John Snow whose name you might have heard of decided to investigate a cholera that was happening in London at the time now back then we didn't know a lot about what caused diseases there is a few theories some were more fantastical than others but there was a lot of evidence to support many of the theories Jon Snow's innovation was that he was going to use maps and numbers to describe the epidemic of the outbreak now to us today that seems kind of rational kind of boring kind of everyday back then it was a revolutionary so what he did was he figured out that back in London in 19th century several neighbourhoods were being served by water pumping stations and he reasoned that probably cholera was waterborne and he took the time to figure out which pumping stations were providing what water to what neighborhoods his investigation led him to conclude that one particular pump the Broad Street pump was likely responsible for most of the cholera outbreaks in that city you can go to London today and actually visit the Broad Street pump there's a plaque there that says this is the spot where epidemiology was born or something like that it's quite fascinating I encourage you to go if you can let's look a little bit at the history of disease before we continue before john snow and his brethren made their innovations and discoveries it was thought that diseases were caused by miasma what's miasma it's some kind of fantastical poisonous magical vapour or mist that would emanate from swamps of the ground and people would shut their windows at night so nothing into their houses and cause them to be sick and it had a foul smell associated with it miasma doesn't really exist we know that today because we know that diseases are caused by infectious agents microbes pathogens bacteria viruses we know this because around the same time that John Snow was making his investigations the microscope made his first appearance and we could see these microbes in action so as a revolutionary time let's look a little bit at the data that Jon Snow collected he looked at the number of houses being served by a variety of pumping companies the south work and Voxx the company the land of company and other companies in London he saw that each was servicing a different number of houses and he counted the number of deaths from cholera experienced by those neighborhoods to most people the number of deaths alone were sufficient to tell the story that's not where John snows stopped he divided the number of deaths by the number of houses being served in each neighborhood and got a quotient a ratio a proportion again to us today that's an obvious thing to do back then it was a revolutionary it was an innovation and by looking at the quotient the proportion he discovered that a majority of deaths were being caused by one particular pumping station and he narrowed it down to one pump the Broad Street pump and today that's what we have the signs of Epidemiology it's the science of using non-medical tools mathematics paper your mind your hands your feet to learn something about disease but otherwise you would not have known so today we have different kinds of epidemiologists I mentioned that John Snow was a kind of outbreak investigator a medical detective of some kind most physicians who are epidemiologists are clinical epidemiologists and they bring to bear a variety of perspectives they bring to bear the choices made by their patients the the clinical research and practice experience that they have and also the experiences of their mentors to make decisions for small groups of people usually in a clinical environment Public Health epidemiologists are people like John Snow these are the individuals who investigate outbreaks who figure out which sandwich at the picnic gave you diarrhea who figure out what's probably causing that causing that outbreak of disease in that community over there they are also the ones who plan the vaccine schedules for a community and population epidemiologists look at large disease trends in a population the incidence and prevalence the risks factors that cause diseases and so forth obviously if there's a lot of overlap in all these different types of epidemiologists and there are newer emerging types of epidemiologists today epidemiology is forging partnerships with political science with economics with computer science and genetics it's a fast evolving and diversifying science so before I continue I want to talk about how we know what we know is important to understand where our discipline fits into the science of knowing and we call this paradigms paradigms of research paradigms of knowing when we talk about paradigms we're talking about how our discipline interacts with the world and understands knowledge and evidence and truth there are several dimensions to a paradigm and I'll suggest you that there are three main pillars philosophically of how to define a paradigm the first is ontology and that's how we how we experience reality is reality defined by my imagination your imagination or is your reality defined by some objective truth of a universe then we deal with epistemology and that's how we acquire and process knowledge do we know about the universe from interrogating it from talking to people from collecting data and then we have our methodology may be the ways in which we design our studies that determines how we understand the universe the important part about all this is that paradigms of research allow us to define how the world works and how we extract knowledge from it a psychologist a political scientists an economist an anthropologist and epidemiologists interact with the world a bit differently in defined knowledge a bit differently we define the questions that we ask a bit differently as well when we look at evidence-based medicine we're going to phrase a research question and the paradigm of knowledge from which we arise helps us define the types of questions that we can ask our paradigm of research also tells us what is publishable and what isn't because it defines what constitutes knowledge what constitutes proper evidence and epidemiology is I hope you will conclude with me all about how we rank evidence and understand truth in essence a paradigm tells us how the world is structured and tells us what determines meaning and significance epidemiology exists within something we call the etiologic paradigm which is a kind of positivism and it purports that there exists external objective truth that we can access via art our methodologies our science our study designs and we can measure risk factors and things that cause outcomes smoking causes cancer this behavior will cause this other kind of outcome that's the nature of the epidemiologic etiologic paradigm I bring this up because it's important that we remember that epidemiology and any discipline for that matter is about one half to knowledge there are a variety of paths to knowledge different disciplines have their own paths it's important that we don't descend into arrogance when we consider the evidence that we choose to base our medical decision-making on so let's now change gears a bit and talk about terminology it's important that we get our our words straight before we can talk more deeply about epidemiology and how to use it when we're in mathematics versus clinical research versus laboratory research versus epidemiology some common concepts often have different names so we have clinical research and mathematical relationships and and in this domain we have independent and dependent variables so an independent variable is free to be whatever it wants but it determines the value of dependent variables in epidemiologic research a variable that predicts an outcome is an exposure you're exposed to something which may lead to an outcome you can be exposed to a contaminant a pollutant may be something in your food and the outcome could be a disease a cancer or some other kind of behavior so again traditionally we have independent variables that lead to dependent variables in epidemiology these are exposures leading to outcomes the example that I'm fond of making all the time is that smoking is an independent variable you are free you're independent to smoke if you want to or not smoke if you want to but the smoking causes a certain outcome and that outcome could be lung cancer now an exposure that increases or decreases the likelihood for developing a certain outcome or disorder calmly diseases we call that a risk factor now go back to Jon Snow again Jon Snow discovered that water from this pumping station was likely associated with cholera he didn't know how it worked he didn't understand the biology the mechanism by which water caused the disease he just knew that this water was a risk factor for getting the disease and this really is one of the foundations for Public Health epidemiology we can measure statistically the relationship between risk factors and outcomes and thus we can control the risk factors and maybe then control the outcomes without knowing of the relationship without knowing the mechanism of how that risk factor caused the outcome or in fact if it was indeed causal for example smoking causes lung cancer we know this because there's a strong statistical association between whether or not you smoke and whether or not you are likely to get lung cancer you don't have to know the science or the biology or the mechanism of how the smoking causes the lung cancer it helps it's useful we recommend that we figure this out we don't have to know in order in order to have a public health intervention epidemiologically I can control the risk factor and thus reduce the likelihood of the outcome sometimes when people say the epidemiology of a disease what they actually mean is the description of that disease and that brings us to talking about descriptive epidemiology or descriptive study by the way I don't like it when we say the epidemiology of a disease it's a limiting description of the full breath and majesty and complexity of what the science of Epidemiology brings to the table but when they say descriptive epidemiology what we're talking about is the who who gets that a disease or an outcome the what what is that the getting the where where is it happening and when when is it happening notice that there is no why they're just as for w's who what where and when when we're into the why we're into a deeper kind of investigation descriptive epidemiology only cares about describing the WHO where and when so let's think of an example let's just let's aside that we're going to investigate the prevalence of left handedness among students in your neighborhood who we're dealing with students what left handedness where the place where you live your neighborhood and when right now we care about measuring this prevalence this distribution right now and so the thing that I'm measuring the things I'm ascertaining is right now 23% of students in your neighborhood are left-handed that's a very simple and relatively useless observation but a good description of descriptive epidemiology now I want to talk a little bit about the way the study designs our texana mised how we categorize them because a large part of Epidemiology is in designing studies to acquire the evidence that fits within our research paradigm so the first large delineation I want to draw attention to is qualitative versus quantitative studies in qualitative research that's the world of social sciences the world of political science and sometimes Health Sciences that's when we're dealing with descriptions that are qualitative words themes things like that quantitative research is in numbers statistics and that's where we're going to live we're going to live in the world of quantitative research in epidemiology amongst quantitative studies we have descriptive versus analytical studies now descriptive studies we've talked about already that's the who what where and when right and one example of a descriptive study is a cross-sectional study which we will describe in greater depth later but I just did an example left hand is my neighborhood that's a cross-sectional description of a particular phenomenon when we are looking at two different variables or more variables and how they relate to one another then we're into the world of analysis into analytical studies now descriptive studies dealt with one variable really describing left-handedness analytical studies are looking at two variables or more and a relationship between them amongst a little study there are two other categories observational or experimental amongst observational studies there are three perhaps four large categories the case control the cohort different kinds of cross-sectional studies and possibly this thing called ecological study all of which we will learn more about in another lecture the distinguishing characteristic of observational studies is that we observed them the universe unfolds and we observe we don't determine who does what or who gets what all we do is we watch and we marvel in the way the universe unfolds experiments on the other hand that's when we do get to interfere a bit the classical experiment in epidemiology is the randomized control trial or the RCT also called clinical trials there are other kinds of experiments as well there are quasi experimental designs or natural experiments and we'll talk about more of those in a future lecture as well now when the layperson thinks about an experiment they mean any kind of study any kind of investigation whenever you may all just talk about an experiment we mean something very particular we're talking about when we manipulate a variable so perhaps we are deciding who gets a drug versus who gets a placebo or who gets to smoke for who doesn't smoke whenever we are telling people what to do we are conducting an experiment we manipulate something we manipulate variable the observational studies we don't we left the universe unfold as it would be that people choose what they're going to do we may select them based upon what they're doing but we don't tell them what to do an experiment involves us changing a variable well now that we've covered the differences between analytical and descriptive studies and difference between observational and experimental studies let's look at some historical examples in particular I want to talk about the triumphs of Epidemiology one in particular and it's this you may recognize this photo may recognize this disease this is smallpox one of the great scourge ha's of humankind one of the great burdens of human civilization and smallpox is particular because it is the first human disease deliberately eradicated by human beings and we did this in 1980 in large part due to some innovative approaches by epidemiologists heroes I would argue so as I mentioned smallpox was defined to be eradicated by the w-h-o in 1980 but attempts to do so go back decades before then in 1975 this individual or Hema Banu I think she's from Bangladesh was the last person to contract natural smallpox and since then we don't know of any individual who has contracted natural smallpox so we're pretty confident the smallpox has been eradicated I'm sufficiently old that I still have a mark on my shoulder from my smallpox vaccine it left a large mark but young people today don't have that mark they don't have that burden because we have eliminated the need for that vaccine I love this particular quote by Thomas Jefferson in a letter to Edward Jenner in 1806 he says and the the the critical part of this letter is the last sentence future nations will know by history only that the loathsome smallpox has existed it's important because Edward Jenner devised the first workable smallpox vaccine in the early 1800s and Thomas Jefferson implies in his letter that due to that vaccine we will no longer have a smallpox problem but it took another hundred and eighty years for us to truly eradicate smallpox so clearly the solution for beating back this disease wasn't simply the technology of vaccination it was something a little more complicated more profound more interesting and that's where the science of Epidemiology came in it was a need to compute the numbers of people who need to be vaccinated to truly eradicate the disease and this was made possible because of something called herd immunity herd immunity is when individuals in a population are immune to a disease and thus prevent other individuals who are not immune from getting contact with that disease if you think about a herd of cattle those at the center of the herd will never have any contact with anyone outside of the her because they're protected by those on the periphery so long as those on periphery are immune or have been vaccinated then the ones in the center don't need to be in other words not everybody in the herd needs to be vaccinated just a certain proportion epidemiologists stepped in and computed that proportion that was needed to insure that smallpox would be eradicated let's look at the timeline of smallpox in human civilization going back centuries if not millennia smallpox was a major scourge of humankind in the 18th century attempts at finding a treatment made some great progress with Edgar Jenner creating the first variation attempts but back then 400,000 people would die every year at least it was quite the killer a third of the survivors though became blind and so they lived on with disability so it's not just about the disease killing people it's not just about the mortality it's also about the morbidity and it's important that we keep in mind that when we're looking at the impact of disease it's not just the deaths we care about it's the effects on the quality of life that matter the people who survive also developed an immunity to smallpox this is an important consideration when we talk about eradicating the disease once you got it you're not going to get it again we can cross you off the list of someone who needs to be inoculated so Edward Jenner took interest in in cow pox which was a kind of small pox at cattle had and he noticed that people who were milking cows would be exposed to cow pox and tended to be immune to smallpox as a result so he got the idea that exposure to this particular infection of cow pox may imbue an individual with a kind of immunity to smallpox so in the 1950s the world took notice that maybe it was time to have a more militaristic administrative attempt to control smallpox globally in 1967 a decision was made by the whu-oh to attempt to eradicate and remove this scourge from the human experience altogether and as I mentioned in 1980 this was accomplished w-h-o had eradicated smallpox entirely a great triumph so to review that timeline in 67 we began the eradication progress process and back then 15 million people were developing smallpox every year but 2 million died every year and today no one dies anymore from smallpox so one of the important qualities of Epidemiology is through the observational process we can determine risk factors and likely causes of disease I say likely causes because I use that word cause very carefully we'll talk later on about how we define what a causal factor is but an absence of knowing for sure that something causes something else we called a risk factor and we talked about associations rather than causations so many times we don't know the cause of a disease but we can associate it with various exposures for example streptococcal infection is often followed by rheumatic fever and sometimes rheumatic heart disease so we can prevent rheumatic heart disease by preventing spread kakaako infection even if we're not entirely sure what the causal mechanism might be we know that rheumatic fever is more frequent amongst army recruits than in school children so now we know the population to focus on and when an intervention is most likely lung cancer and smoking is the classic example it was fought in courts for many years about whether or not tobacco really was a cause of lung cancer and we're pretty sure that it is but in absence of solid laboratory evidence we had mountains of epidemiological observational evidence showing that people who smoked tended to have lung cancer more so than people who didn't smoke the power of observation in many cases overcomes the need for solid specific causal information observational epidemiology is also useful for understanding morbidity and mortality from diseases in the population as a whole we can associate lifestyle factors like driving without a seat belts or eating too much fat or having too many calories in our diet or being too immobile and not moving enough with other kinds of negative health outcomes we don't need to know that in order to be able to control the outcome by controlling lifestyle choices and risk factors let's talk about some of the important tasks that epidemiologists are engaged in well the first the most important thing that a population epidemiologist cares about is disease surveillance most modern countries have several complicated surveillance programs and action all the time including something called a notifiable disease registry that's when a list of key diseases are made so that anytime a health professional encounters one they must by law inform the government or whoever's in charge of that surveillance program that they saw a case in this way we have a solid idea of whether or not our country or population has a particular disease some of the key ones include tuberculosis or hiv/aids or even Ebola now has made the list in recent months in most countries disease surveillance allows us to detect whether or not an epidemic is happening it allows us to detect whether or not a disease is changing its profile in a way it allows us to predict or detect any time the population is changing its behavior with respect to certain diseases as well epidemiologists are also involved in diagnostic tests we're going to go into greater detail on diagnostic tests in a further lecture but know right now that these tests involve computing things like sensitivity and specificity deciding whether or not we can use this test in this context or whether or not a test is viable as a screening tool to identify individuals who are good candidates for further investigation further on epidemiologists are also useful in trend analysis and we're going to talk a little bit more about trend analysis in a second this is when we look at the changes in diseases over time or over populations and try to ascertain some wisdom from looking at the changes in the numbers without actually investigating individual cases and also one of the important things that clinical epidemiologists and population epidemiologists do is designing studies so very often a researcher will contract an epidemiologist to go over their study design and there protocols to make sure that everything is method logically sound now let's look at some of the issues and trend analysis here's an example from US data this is the changes in mortality rates of white women and lung cancer as you can see from 1973 to 1995 the mortality rates were going up dramatically this is white women in America dying of lung cancer if you look at black women well the rates are kind of the same so there's no reason to expect white women and black women to be physiologically different so this is not surprising if you look at breast cancer white women the rates have come down slightly from 1973 to 1995 with a black women they've gone up that's interesting here's all the data in one slide we see that there are no changes or no differences between white and black women except with respect to breast cancer that's very interesting and there could be a host of reasons for this observation including something we call detection bias that's when we're looking for more cases so we find more cases and again we're talking more about detection bias in a future lecture about biases but the point I'm trying to make here is that trend analysis allows us to know what questions to ask allows us to ascertain that there's probably something happening here that I need to investigate further so what have we learned as a result of this lecture well you've learned the origins of Epidemiology you know that it began in England in the early 19th century with a bit of medical detective work by John Snow and since then it's evolved into a host of other realms including clinical epidemiology and genetic epidemiology and population epidemiology and data science and all these other categories of Epidemiology that maybe you're interested in now now you can distinct between descriptive and analytical studies description of Epidemiology remember is when we're describing a scenario we care about the who the what the where and the when analytical studies is when we are drawing relationships between two variables and now you can identify the different types of epidemiologist the clinical epidemiologist the popular epidemiologists and Public Health epidemiologists [Music] you

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Length: 29min 13sec (1753 seconds)

Published: Mon Oct 02 2017