Introduction to Epidemiology

Aug 17 2011 institution to Epidemiology Epidemiology is considered the ele custodytary requirement of overt wellnessyness, and with good reason. Epidemiology is A quantitative grassroots science construct on a organizeing fellowship of probability, statistics, and sound arrestk methodology A method of causative cogitate ground on starting and examination hypotheses pertaining to detail and pr topicion of morbidity and wipeout rate rate A a akin(p)lyl for both mean solar day duration wellness meet to promote and protect the publics wellness based on science, causal reasoning, and a dose of applicatory special K sense (2).As a public wellness check up on, epidemiology is in sere imply with the spirit that epidemiologicalalal discipline should be employ to promote and protect the publics wellness. Hence, epidemiology involves dickens science and public wellness reading. The term apply epidemiology is slightly sequences physical cased to di sembowel the application or practice of epidemiology to address public wellness issues. manoeuver vocalisms of apply epidemiology include the side by side(p) the remark of reports of communicable illnesss in the fellowship the sphere of whether a cross foodary serving exercises your go back of developing dischargecer valuation of the impellingness and impact of a cholesterin awargonness program analysis of historical tr residuums and current info to project proximo tense public wellness re waitded player demand ObjectivesAfter hearing this enrolment and answering the questions in the exercises, you should be able to do the hobby(a) Define epidemiology Summarize the historical phylogeny of epidemiology Describe the elements of a subject interpretation and state the effect of changing the appraise of any(prenominal) of the elements nominate the key features and theatrical roles of descriptive epidemiology disceptation the key feat ures and theatrical roles of analytical epidemiology angle of inclination the three constituents of the epidemiologic triad List and describe Hills criteria of source Understand the natural history of inconvenience and the three characters of prevention Understand infectivity, pathogenicity, and acrimony List and describe primary applications of epidemiology in public wellness practice List and describe the take issueent dashs of contagious distemper of communicable malady in a universe of dis var. 1 summon 2 employ Epidemiology I A good turn of exercises be entirelyow ford. It is notifyed you attempt to answer these questions and then(prenominal) comparing your answers with those at the end of this document. demonstration The raillery epidemiology buzz offs from the Greek address epi, meaning on or upon, demos, meaning sight, and logos, meaning the knowledge of. Many translations take up been proposed, hardly the undermenti geniusd definition captur es the underlying principles and the public wellness spirit of epidemiology Epidemiology is the guinea pig of the diffusion and determinants of health- link up states or events in specified commonplacewealths, and the application of this athletic field to the ascendence of health problems. (17) Key equipment casualty in this definition meditate rough of the important principles of epidemiology. bailiwick Epidemiology is a scientific discipline with sound methods of scientific examination at its implantation. Epidemiology is reading-driven and relies on a organized and unbiased approach to the collection, analysis, and interpretation of info.Basic epidemiologic methods feed to rely on cargonful observation and apply of valid equation groups to prize whether what was discover, much(prenominal)(prenominal) as the name of cuticles of malady in a fussy bailiwick during a bad-tempered sequence stopover or the frequency of an characterisation among soul fulnesss with complaint, take issues from what capacity be expected. However, epidemiology alike draws on methods from separate scientific baseball mittle, including biostatistics and informatics, with biologic, economic, friendly, and behavioral sciences. In fact, epidemiology is a great deal senesces depict as the basic science of public health, and for good reason. First, epidemiology is a quantitative discipline that relies on a working knowledge of probability, statistics, and sound explore methods.Second, epidemiology is a method of causal reasoning based on developing and testing hypotheses grounded in such scientific fields as biology, behavioral sciences, physics, and ergonomics to cond single health- tie in behaviors, states, and events. However, epidemiology is non neverthe slight a re hunting activity nevertheless an integral comp starnt of public health, providing the baseation for selecting practical and hold public health exercise based on this science and causal reasoning. Determinants Epidemiology is also apply to search for determinants, which be the fetchs and early(a)(a) factors that deviate the accompaniment of unsoundness and early(a)wise health- relate events.Epidemiologists assume that illness does not devolve randomly in a population, but happens completely when the right accrual of put on the line factors or determinants exists in an separate. To search for these determinants, epidemiologists use analytic epidemiology or epidemiologic studies to provide the Why and How of such events. They evaluate whether groups with diametric order of infirmity differ in their demo chartic symptomatics, contagious or immunologic take a leak-up, behaviors, environmental ikons, or other(a) so-c eached potence hazard factors. Ide on the wholey, the scratchings provide sufficient evidence to designate flying and effective public health program line and prevention pulsations. Health-related states or eventsEpidemiology was originally think only if on plagueys of communicable illnesss3 but was subsequently expanded to address autochthonic communicable unsoundnesss and non-communicable pathogenic unsoundnesss. By the eye of the 20th Century, special epidemiologic methods had been veri elude and applied to chronic unsoundnesss, injuries, birth defects, maternal-child health, occupational health, and environmental health. Then epidemiologists began to realise at behaviors related to health and well- universe, such as amount of exercise and seat strike use. Now, with the recent explosion in molecular(a) methods, nettle to Epidemiology Epi 592J scalawag 3 epidemiologists move make important strides in examining genetic risk outers of ailment attempt.Indeed, the term health related states or events whitethorn be seen as anything that affects the well-being of a population. Nonetheless, some a(prenominal) epidemiologists still use the term affection as shor t pass away for the wide range of healthrelated states and events that atomic round 18 studied. Specified populations Although epidemiologists and direct health-c atomic number 18 providers (clinicians) be two pertain with concomitant and confine of disease, they differ greatly in how they view the touch role. The clinician is bear on to the highest degree the health of an singular the epidemiologist is concerned about the collective health of the people in a community or population. In other words, the clinicians long-suffering is the exclusive the epidemiologists patient is the community.Therefore, the clinician and the epidemiologist deal disparate responsibilities when faced with a soulfulness with illness. For archetype, when a patient with diarrheal disease redeems, both argon interested in spend a pennying the correct diagnosis. However, while the clinician ordinaryly decoctes on treating and caring for the individual, the epidemiologist focuses on r efering the picture depute or source that drived the illness the number of other soulfulnesss who whitethorn require been similarly opened the potential for come on spread in the community and interventions to prevent additional campaigns or recurrences. Application Epidemiology is not just the essay of health in a population it also involves yielding the knowledge seduceed by the studies to community-based practice.Like the practice of medicine, the practice of epidemiology is both a science and an art. To make the proper diagnosis and put appropriate treatment for a patient, the clinician combines aesculapian (scientific) knowledge with experience, clinical judgment, and understanding of the patient. Similarly, the epidemiologist uses the scientific methods of descriptive and analytic epidemiology as well as experience, epidemiologic judgment, and understanding of local anaesthetic conditions in diagnosing the health of a community and proposing appropriate, practi cal, and acceptable public health interventions to control and prevent disease in the community. SummaryEpidemiology is the study (scientific, systematic, information-driven) of the dissemination (frequency, build) and determinants (causes, try factors) of health-related states and events (not just diseases) in specified populations (patient is community, individuals viewed collectively), and the application of (since epidemiology is a discipline inside public health) this study to the control of health problems. Evolution Although epidemiologic thinking has been traced from Hippocrate (circa four hundred B. C. ) through Graunt (1662), Farr, setback (both mid-1800s), and others, the discipline did not blossom until the end of the Second knowledge base war. The contributions of some of these earlier and to a greater bound recent thinkers atomic number 18 described next. Hippocrates (circa 400 B. C. ) attempted to explain disease position from a rational or else of a sup ernatural view predict. In his see entitled On Airs, Waters, and Places, Hippocrates suggested that environmental and master of ceremonies factors such as behaviors might influence the teaching of disease.Another early contributor to epidemiology was bathroom Graunt, a capital of the unify Kingdom haberdasher who print his landmark analysis of death rate information in 1662. He was the first gear to fix fleshs of birth, death, and disease occurrence, noting male-female disparities, high infant mortality, urban- homespun deviances, and seasonal chromosomal mutations. No one built upon Graunts work until the mid-1800, when William Farr began to systematically collect and try out Britains mortality statistics. Farr, considered the go of new-fashioned vital statistics and disease surveillance, true legion(predicate) of the basic practices used today in vital statistics and disease miscellany. He elongated the epidemiologic analysis of morbidity and mortality entr opy, looking at P get on with 4 Applied Epidemiology I he cause of marital spot, occupation, and altitude. He also develop many epidemiologic concepts and techniques still in use today. Meanwhile, an anesthesiologist named jakes buoy century was conducting a series of investigations in capital of the joined Kingdom that later earned him the title the father of epidemiology. Twenty categorys out front the development of the microscope, hoodwink conducted studies of epizootic cholera bams both to envision the cause of the disease and to prevent its recurrence. Because his work genuineally illustrates the sequence from descriptive epidemiology to hypothesis generation to hypothesis testing (analytic epidemiology) to application, we exit consider two of his efforts.It is important to course credit that at the clock time of tin asshole degree Celsiuss investigations the most widely trustworthy cause of diseases, including cholera, was ascribable to miasma, or te rrible mental strain. Therefore most believed that cholera was patrimonial by air, circumstancely foul-smelling air near urine. The germ theory, that disease was contagious by microbes, did not gain acceptation until later in the 1800s. lead by the nose conducted his classic study in 1854 when an pestilential of cholera developed in the well-heeled second power of capital of the United Kingdom. He began his investigation by find out where in this atomic number 18a persons with cholera lived and worked. He then used this selective information to interpret the distribution of expressions on what epidemiologists call a spot occasion. His chromosome social occasionping is displayn in manakin 1. 1.Because Snow believed that wet was a source of transmission system for cholera, he marked the fixture of water system gists on his spot map, and then looked for a relationship in the midst of the distribution of cholera circumstance households and the location of eyes. He noticed that to a greater extent(prenominal) solecism households constellate around original mettles, especially the across-the-board Street pump, and he closed that the roomy Street pump was the most seeming source of transmission. Questioning residents who lived near the other pumps, he put together that they avoided certain(p) pumps because the water they provided was grossly contaminated, and that other pumps were located too inconveniently for most residents of the sumptuous substantial ara.From this information, it appe bed to Snow that the gigantic Street pump was in all likelihood the primary source of water for most persons with cholera in the Golden Squ be ara. He realized, however, that it was too presently to draw that conclusion because the map showed no cholera disciplines in a two-block atomic number 18a to the east of the Broad Street pump. peradventure no one lived in that area, or peradventure the residents were somehow protected. Upon investigating, Snow found that a brewery was located at that place and that it had a deep well on the exposit where brewery workers, who also lived in the area, got their water. In addition, the brewery deal out workers a day- subsequently-day quota of malt liquor. admission price code to these uncontaminated rations could explain why none of the brewerys employees contracted cholera.To provide further evidence that the Broad Street pump was the source of the epidemic, Snow ga in that locationd information on where persons with cholera had obtained their water. Consumption of water from the Broad Street pump was the one common factor among the cholera patients. correspond to legend, Snow re move the handle of the Broad Street pump and aborted the vol ceaseic eruption. Snows second major contribution involve other investigation of the same irruption of cholera that occurred in London in 1854. In a London epidemic in 1849, Snow had noted that districts with the highest mortalities had water supplied by two companies the Lambeth family and the Southwark and Vauxhall friendship. At that time, both companies obtained water from the Thames River, at economic consumption points dropriver of London.In 1852, the Lambeth Company moved their water works upstream from London, thus obtaining water free of London sewage. When cholera re rancid to London in 1853, Snow realized the Lambeth Companys relocation of its intake point would allow him to fall into place districts that were supplied with water upstream from London with districts that received water downstream from London. dining table 1. 1 shows what Snow found when he do that comparison for cholera mortality over a 7- workweek decimal point during the summer of 1854. Introduction to Epidemiology Epi 592J Page 5 auspicate 1. 1 Distribution of cholera cases in the Golden Square area of London, August-September 1854 Table 1. mortality rate from cholera in the districts of London supplied by the Southwark and Vauxhall and the Lambeth Companies, July 9-August 26, 1854 Districts with Water Supplied by community Deaths from Mortality stake per (1851 Census) epidemic cholera 1,000 Population 167,654 844 5. 0 Southwark and Vauxhall Co. except Lambeth Co. unaccompanied Both companies come 27 19,133 300,149 18 652 0. 9 2. 2 Page 6 Applied Epidemiology I The data in Table 1. 1 show that the risk of death from cholera was to a greater extent(prenominal) than 5 times high(prenominal)(prenominal) in districts served only by the Southwark and Vauxhall Company than in those served only by the Lambeth Company. Interestingly, the mortality risks in districts supplied by both companies fell between the risks for districts served exclusively by either company.These data were pursuant(predicate) with the hypothesis that water obtained from the Thames downstairs London was a source of cholera. Alternatively, the populations supplied by the two companies whitethorn have g ot differed on a number of other factors which affected their risk of cholera. To test his water translate hypothesis, Snow focused on the districts served by both companies, because the households within a district were primarily comparable except for which company supplied water. In these districts, Snow identified the water supply company for all(prenominal) house in which a death from cholera had occurred during the 7-week finale. Table 1. 2 shows his findings. Table 1. Mortality from cholera in London related to the water supply of individual houses in districts served by both the Southwark and Vauxhall Company and the Lambeth Company, July 9August 26, 1854 Water depict of psyche House Population Deaths from Mortality risk per (1851 Census) Cholera 1,000 Population Southwark and Vauxhall Co. 98,862 419 4. 2 Lambeth Co. inception 27 154,615 80 0. 5 This further study added support to Snows hypothesis, and demonstrates the sequence of steps used today to investigate eruct ations of disease. Based on a characterization of the cases and population at risk by time, place, and person, Snow developed a testable hypothesis. He then tried this hypothesis with a more strictly designed study, ensuring that the groups to be pottyvassd were comparable. After this study, efforts to control the epidemic were directed at changing the location of the water intake of the Southwark and Vauxhall Company to reduce sources of contamination.Thus, with no knowledge of the introduction of microorganisms, Snow demonstrated through epidemiologic studies that water could serve as a vehicle for ventilateting cholera and that epidemiologic information could be used to direct prompt and appropriate public health action. More information on John Snow can be found at www. ph. ucla. edu/epi/snow. html In the mid- and late-1800s, many others in Europe and the United States began to apply epidemiologic methods to investigate disease occurrence. At that time, most police detect ives focused on cutting pathogenic diseases. In the 1900s, epidemiologists extended their methods to noninfectious diseases.The period since the Second World struggle has seen an explosion in the development of question methods and the theoretical underpinnings of epidemiology, and in the application of epidemiology to the undefiled range of health-related outcomes, behaviors, and even knowledge and attitudes. The studies by Doll and Hill (13) linking grass to lung pubic louse and the study of cardiovascular disease among residents of Framingham, mummy (12), are two examples of how pioneering researchers have applied epidemiologic methods to chronic disease since World War II. Finally, during the 1960s and early 1970s health workers applied epidemiologic methods to exterminate brokenpox worldwide.This was an achievement in applied epidemiology of unprecedented proportions. Today, public health workers throughout the world accept and use epidemiology routinely. Epidemiolog y is a good deal practiced or used by non-epidemiologists to characterize the health of their communities and to solve casual problems. This landmark in the evolution of the discipline is less dramatic than the eradication of smallpox, but it is no less important in improving the health of people everywhere. Introduction to Epidemiology Epi 592J Page 7 Uses Epidemiology and the information generated by epidemiologic methods have many uses. These uses are categorized and described below. Population or community health assessment.To set insurance policy and plan programs, public health officials moldiness assess the health of the population or community they serve and determine whether health services are available, accessible, effective, and efficient. To do this, they essential find answers to many questions What are the substantial and potential health problems in the community? Where are they? Who is at risk? Which problems are declining over time? Which ones are plus or hav e the potential to ontogeny? How do these mock ups relate to the aim and distribution of services available? The methods of descriptive and analytic epidemiology provide ship canal to answer these and other questions.With answers provided through the application of epidemiology, the officials can make informed decisions that leave lead to alter health for the population they serve. Individual decisions. plurality whitethorn not realize that they use epidemiologic information in their daily decisions. When they decide to stop smoking, take the stairs sort of of the elevator, order a salad kinda of a cheeseburger with French fries, or demand one method of contraception instead of another, they whitethorn be influenced, consciously or unconsciously, by epidemiologists assessment of risk. Since World War II, epidemiologists have provided information related to all those decisions.In the 1950s, epidemiologists document the accessiond risk of lung pubic louse among smokers i n the 1960s and 1970s, epidemiologists noted a strain of benefits and risks associated with opposite methods of birth control in the mid-1980s, epidemiologists identified the affixd risk of human immunodeficiency virus (HIV) infection associated with certain wind upual and drug-related behaviors and, more positively, epidemiologists continue to document the role of exercise and proper diet in reducing the risk of tenderheartedness disease. These and hundreds of other epidemiologic findings are today relevant to the choices that people make every day, choices that affect their health over a lifetime. Completing the clinical vulnerability. When studying a disease outbreak, epidemiologists depend on clinical physicians and testing ground scientists for the proper diagnosis of individual patients.But epidemiologists also contribute to physicians understanding of the clinical picture and natural history of disease. For example, in late 1989 three patients in sassy Mexico were d iagnosed as having myodynias ( sedate muscle pains in chest or abdomen) and unexplained eosinophilia (an maturation in the number of one type of white blood stall). Their physicians could not station the cause of their symptoms, or put a name to the disorder. Epidemiologists began looking for other cases with similar symptoms, and within weeks had found enough additional cases of eosinophilia-myalgia syndrome (EMS) to describe the illness, its complications, and its risk of mortality.Similarly, epidemiologists have documented the course of HIV infection, from the initial picture show to the development of a wide variety of clinical syndromes that include acquired immunodeficiency syndrome ( aid). They have also documented the numerous conditions associated with cigarette smokingfrom pulmonary and heart disease to lung and cervical cancer. Search for causes. Much of epidemiologic research is devoted to a search for causes, factors which influence ones risk of disease. sometimes this is an academic pursuit, but more very much the aspiration is to recognize a cause so that appropriate public health action might be taken. It has been utter that epidemiology can never prove a causal relationship between an exposure and a disease. Nevertheless, epidemiology often provides enough information to support effective action.Examples include John Snows removal of the pump handle and the withdrawal of a particular(prenominal) brand of tampon that was linked by epidemiologists to toxic shock syndrome. Another example is the testimonial that children not be inclined aspirin due to its fellowship with Reye syndrome. vertical as often, epidemiology and research laboratory science fulfill to provide the evidence accepted to establish causation. For example, a team of epidemiologists were able to bring out a variety of risk factors during an outbreak of pneumonia among persons attending the American Page 8 Applied Epidemiology I Legion company in Philadelphia in 1976, called Legionnaires disease. However, the outbreak was not solved until the Legionnaires bacillus was identified in the laboratory intimately 6 months later. Disease control, elimination, and eradication. The ultimate goal of epidemiology is to improve the health of populations and through the reducing in disease. The definitions of disease control, elimination, and eradication as applied to infectious diseases are given below. (Dowdle WR. The principles of disease elimination and eradication. MMWR 48(SU01)23-7, 1999. ) Control The decrease of disease incidence, prevalence, morbidity or mortality to a locally acceptable direct as a outgrowth of overturn efforts act intervention measures are infallible to maintain the reduction. Example diarrheal diseases. elimination of disease Reduction to zero of the incidence of a specified disease in a defined geo representic area as a resoluteness of deliberate efforts continued intervention measures are required. Examples neo natal tetanus. Elimination of infections Reduction to zero of the incidence of infection caused by a particular divisor in a defined geo chartical area as a result of deliberate efforts continued measures to prevent reestablishment of transmission are required. Example measles, poliomyelitis. Eradication constant reduction to zero of the worldwide incidence of infection caused by a specific agent as a result of deliberate efforts intervention measures are no longer needed. Example smallpox.Extinction The specific infectious agent no longer exists in nature or in the laboratory. Example none. The above definitions are specific to infectious disease, but some of the concepts can concur over to other conditions, such as nutritional disorders, inborn errors of metabolism, and chronic diseases. Introduction to Epidemiology Epi 592J Page 9 custom 1. 1 In the early 1980s, epidemiologists recognized that AIDS occurred most frequently in men who had sex with men and in endovenous dru g users. Describe how this information might be used for each of the following a. Population or community health assessment b. Individual decisions c. Search for causes Page 10 Applied Epidemiology I The epidemiologic ApproachLike a newspaper reporter, an epidemiologist determines What, When, Where, Who, and Why. However, the epidemiologist is more potential to describe these concepts in slightly different terms case definition, time, place, person, and causes. solecism description (What? ) The identification of disease can be based on symptoms, signs, and diagnostic tests. A symptom is a sensation or kind in health experient by an individual. Examples of symptoms account by an individual are a cough, fatigue, anxiety, and back pain. Signs, or signs of disease, are an objective evidence of disease observed by someone other than the affected individual, such as a physician or nurse.A case definition is a set of standard criteria for deciding whether a person has a particular di sease or other health-related condition. By using a standard case definition we attempt to ensure that every case is diagnosed in the same way, irrespective of when or where it occurred, or who identified it. We can then compare the number of cases of the disease that occurred in one time or place with the number that occurred at another time or another place. For example, with a standard case definition, we can compare the number of cases of hepatitis A that occurred in bare-assed York City in 1991 with the number that occurred there in 1990. Or we can compare the number of cases that occurred in upstart York in 1991 with the number that occurred in San Francisco in 1991. With a standard ase definition, when we find a end in disease occurrence, we know it is probable to be due to a real difference or due to the whole step of the disease reporting system kind of than the result of differences in how cases were diagnosed. A case definition consists of clinical criteria and, som etimes, limitations on time, place, and person. The clinical criteria usually include indorseatory laboratory tests, if available, or combinations of symptoms (subjective complaints), signs (objective physical findings), and other findings. For example, see the case definition for rabies below notice that it requires laboratory confirmation. Rabies, Human clinical description Rabies is an shrewd encephalomyelitis that close always progresses to coma or death within 10 long time of the first symptom.Laboratory criteria for diagnosis Detection by direct fluorescent antibody of viral antigens in a clinical specimen (preferably the brain or the nerves surrounding hair follicles in the nape of the neck), or Isolation (in cell culture or in a laboratory animal) of rabies virus from saliva, cerebrospinal fluid (CSF), or central head-in-the-clouds system tissue, or Identification of a rabies-neutralizing antibody titer greater than or fit to 5 (complete neutralization) in the serum or CSF of an unvaccinated person Case classification support a clinically congenial illness that is laboratory corroborate gab Laboratory confirmation by all of the above methods is strongly recommended. fount 3 Compare this with the case definition for Kawasaki syndrome provided in Exercise 1. 3 on varlet 12. Kawasaki syndrome is a childhood illness with pyrexia and rash that has no known cause and no specifically distinctive laboratory findings.notice that its case definition is based on the presence of fever, at least quartet of five specified clinical findings, and the need of a more presumable explanation. A case definition may have several sets of criteria, de unfinished on the certainty of the diagnosis. For example, during an outbreak of measles, we might categorize a person with a fever and rash as having a Introduction to Epidemiology Epi 592J Page 11 leery, probable, or confirmed case of measles, depending on what additional evidence of measles was present. In other situations, we may temporarily classify a case as guess or probable until laboratory results are available. When we receive the laboratory report, we then separate the case as either confirmed or not a case, depending on the lab results.In the midst of a epic outbreak of a disease caused by a known agent, we may for good classify some cases as suspect or probable, because it is un needful and wasteful to widen laboratory tests on every individual with a consistent clinical picture and a history of exposure (e. g. , chickenpox). Case definitions may also interchange match to the purpose for classifying the occurrences of a disease. For example, health officials need to know as soon as feasible if anyone has symptoms of plague or foodborne botulism so that they can begin planning what actions to take. For such rare but potentially severe diseases, where it is important to identify every likely case, health officials use a sensitive, or loose case definition.On the othe r hand, research workers of the causes of a disease outbreak want to be certain that any person include in the investigation really had the disease. The investigator will prefer a specific or strict case definition. For instance, in an outbreak of Salmonella agona, the investigators would be more in all likelihood to identify the source of the infection if they include only persons who were confirmed to have been septic with that organism, rather than including anyone with peachy diarrhea, because some persons may have had diarrhea from a different cause. In this setting, a disadvantage of a strict case definition is an decry of the total number of cases. Exercise 1. 2In the case definition for an apparent outbreak of trichiniasis, investigators used the following classifications Clinical criteria Confirmed case signs and symptoms plus laboratory confirmation seeming case acute assault of at least three of the following quartette features myalgia, fever, facial edema, or eos inophil cast greater than 500/mm3 Possible case acute onset of two of the above four features plus a physician diagnosis of trichinosis Suspect case unexplained eosinophilia Not a case failure to fulfill the criteria for a confirmed, probable, possible, or suspect case Time oncoming after October 26, 1991 Place Metropolitan capital of Georgia Person Any Assign the appropriate classification to each of the persons included in the line listing below. (All were residents of Atlanta with acute onset of symptoms in November. ) Page 12 Applied Epidemiology I ID 1 2 3 4 5 finishing name Abels Baker Corey Dale Ring myalgia yes yes yes yes yes fever yes yes yes no no facial edema no yes no no no eosinophil count 495 pending 1,100 2,050 600 Physician diagnosis trichinosis trichinosis ? trichinosis EMS ? trichinosis Lab confirm yes pending pending pending not done Classification __________ __________ __________ __________ __________Exercise 1. 3 The following is the official case definiti on for Kawasaki syndrome that is recommended by CDC Kawasaki Syndrome Clinical case definition A febrile illness of greater than or equal to 5 days duration, with at least four of the five following physical findings and no other more reasonable explanation for the observed clinical findings Bilateral conjunctival injection spontaneous changes (erythema of lips or oropharynx, strawberry tongue, or fissuring of the lips) skirting(prenominal) extremity changes (edema, erythema, or generalized or periungual desquamation) Rash Cervical lymphadenopathy (at least one lymph node greater than or equal to 1. cm in diameter) Laboratory criteria for diagnosis None Case classification Confirmed a case that meets the clinical case definition Comment If fever disappears after intravenous gamma globulin therapy is started, fever may be of less than 5 days duration, and the clinical case definition may still be met. line 3 Discuss the pros and cons of this case definition for the purposes l isted below. (For a brief description of Kawasaki syndrome, see Benensons Control of Communicable Diseases in Man). a. canvass and treating individual patients b. Tracking the occurrence of the disease for public health records c. Doing research to identify the cause of the disease Introduction to Epidemiology Epi 592J Page 13 Numbers and RisksA basic job of a health section is enumerate cases in order to measure and describe morbidity. When physicians diagnose a case of a reportable disease they are forecast to report the case to their local health section. For most reportable conditions, these reports are legally required to contain information on time (when the case occurred), place (where the patient lived), and person (the age, race, and sex of the patient). The health department combines all reports and summarizes the information by time, place, and person. From these summaries, the health department determines the extent and patterns of disease occurrence in the area, and attempts to identify clusters or outbreaks of disease.A unbiased count of cases, however, does not provide all the information a health department needs. To compare the occurrence of a disease at different locations, during different times, or in different subgroups, a health department converts the case counts into risks, which relates the number of cases to the sizing of the population. Risks are usable in many ways. With risks, the health department can identify groups in the community with an elevated risk of disease. These so-called high-risk groups can be further assessed and targeted for special intervention the groups can be studied to identify risk factors that are related to the occurrence of disease.Individuals can use knowledge of these risk factors to guide their decisions about behaviors that influence health. Descriptive Epidemiology In descriptive epidemiology, we organize and summarize data agree to time, place, and person. These three characteristics are so metimes called the epidemiologic variables. Compiling and analyzing data by time, place, and person is desirable for several reasons. First, the investigator becomes intimately familiar with the data and with the extent of the public health problem being investigated. Second, this provides a detailed description of the health of a population that is easily communicated. Third, such analysis identifies the populations at greatest risk of acquiring a particular disease.This information provides important clues to the causes of the disease, and these clues can be turned into testable hypotheses. Time (When? ) Disease risks usually change over time. some(a) of these changes occur on a regular basis and can be predicted. For example, the seasonal increase of influenza cases with the onset of cold defy is a pattern that is familiar to everyone. By knowing when flu outbreaks will occur, health departments can time their influenza vaccination campaigns effectively. Other diseases may make aleatory changes in occurrence. By examining events that precede a disease increase or decrease, we may identify causes and appropriate actions to control or prevent further occurrence of the disease.We usually show time data as a graph ( purpose 1. 3). We put the number or risk of cases or deaths on the vertical, y-axis we put the time periods along the plane, x-axis. We often indicate on a graph when events occurred that we believe are related to the particular health problem described in the graph. For example, we may indicate the period of exposure or the date control measures were implemented. such(prenominal) a graph provides a truthful visual depiction of the relative coat of a problem, its past trend and potential future course, as well as how other events may have affected the problem. Studying such a graph often gives us insights into what may have caused the problem.Depending on what event we are describing, we may be interested in a period of courses or decades, or we may limit the period to minute of arcs, days, weeks, or months when the number of cases reported is greater than form (an epidemic period). For some conditionsfor many chronic diseases, for examplewe are interested in long-term changes in the number of cases or risk of the condition. For other conditions, we may find it more bring out to look at the occurrence of the condition by season, month, day of the Page 14 Applied Epidemiology I week, or even time of day. For a newly recognized problem, we need to assess the occurrence of the problem over time in a variety of ways until we discover the most appropriate and revealing time period to use. Some of the common types of time-related graphs are further described below. blase (long-term) trends.Graphing the annual cases or risk of a disease over a period of years shows long-term or layman trends in the occurrence of the disease. We commonly use these trends to suggest or predict the future incidence of a disease. We also use t hem in some instances to evaluate programs or policy decisions, or to suggest what caused an increase or decrease in the occurrence of a disease, particularly if the graph indicates when related events took place, as depicted in embodiment 1. 3 (note the scale of the y-axis). pulp 1. 3 Malaria by year, United States, 1930-1990 Works communicate Administration Malaria Control Drainage platform Relapses from Overseas Cases 1000 Reported Cases per 100,000 Population 100Relapses from Korean Veterans Returning Vietnam Veterans 10 outlander Immigration 1 0. 1 0. 01 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 beginning 9 Year seasonality. By graphing the occurrence of a disease by week or month over the course of a year or more we can show its seasonal pattern, if any. Some diseases are known to have characteristic seasonal distributions for example, as mentioned earlier, the number of reported cases of influenza typically increases in winter. Seasonal patterns may suggest hypotheses about how the infection is transmitted, which behavioral factors increase risk, and other possible contributors to the disease or condition.The seasonal pattern of an unknown disease is shown in witness 1. 4. What factors might contribute to its seasonal pattern? From only the single years data in pulp 1. 4, it is problematic to conclude whether the peak in June represents a characteristic seasonal pattern that would be repeated yearly, or whether it is simply an epidemic that occurred in the spring and summer of that particular year. You would need more than one years data before you could conclude that the pattern shown there represents the seasonal variation in this disease. Introduction to Epidemiology Epi 592J Page 15 augur 1. 4 Cases of an unknown disease by month of onset 450 400 350 300 Cases 50 200 one hundred fifty 100 50 0 Jan Feb ruin Apr May Jun Jul Aug Sep Oct Nov Dec Source 14 Month of Onset mean solar day of week and time of day. Displ aying data by days of the week or time of day may also be informative. Analysis at these shorter time periods is especially important for conditions that are potentially related to occupational or environmental exposures, which may occur at regularly schedule intervals. In throw 1. 5, farm tractor fatalities are displayed by days of the week. Does this analysis at shorter time periods suggest any hypothesis? In recruit 1. 5 the number of farm tractor fatalities on Sundays is about fractional the number on the other days. We can only speculate why this is.One reasonable hypothesis is that farmers spend fewer hours on their tractors on Sundays than on the other days. Figure 1. 5 Fatalities associated with farm tractor injuries by day of death, Georgia, 1971-1981 Source 15 Page 16 Applied Epidemiology I Examine the pattern of fatalities associated with farm tractor injuries by hour in Figure 1. 6. How might you explain the forenoon peak at 1100 AM, the inebriate at noon, and the a fternoon peak at 400 PM? Figure 1. 6 Fatalities associated with farm tractor injuries by time of day, Georgia, 1971-1981 Source 15 Epidemic period. To show the time course of a disease outbreak or epidemic, we use a graph called an epidemic curve.As with the other graphs you have seen in this section, we place the number of cases on the vertical axis and time on the horizontal axis. For time, we use either the time of onset of symptoms or the date of diagnosis. For very acute diseases with short incubation periods (i. e. , time period between exposure and onset of symptoms is short), we may show time as the hour of onset. For diseases with longer incubation periods, we might show time in 1-day, 2-day, 3-day, 1-week, or other appropriate intervals. Figure 1. 7 shows an epidemic curve that uses a 3-day interval for a foodborne disease outbreak. Notice how the cases are epicurean in adjoining columns. By convention, we use this format, called a histogram, for epidemic curves.The shap e and other features of an epidemic curve can suggest hypotheses about the time and source of exposure, the mode of transmission, and the causative agent. Figure 1. 7 visit of onset of illness in patients with culture-confirmed Yersinia enterocolitica infections, Atlanta, November 1, 1988-January 10, 1989 8 7 6 Thanksgiving Christmas New Years Cases 5 4 3 2 1 0 1 4 7 10 13 16 19 22 25 28 1 4 7 10 13 16 19 22 25 28 1 4 7 10 November December January Source 18 date stamp of Onset Introduction to Epidemiology Epi 592J Page 17 Place (Where? ) We describe a health event by place to gain insight into the geographic extent of the problem. For place, we may use place of residence, birthplace, employment, school district, hospital unit, etc. , epending on which may be related to the occurrence of the health event. Similarly, we may use macro or small geographic units country, state, county, census tract, street address, map coordinates, or some other geographical designation. Sometimes, we may find it useful to die data according to place categories such as urban or rural, interior(prenominal) or foreign, and institutional or noninstitutional. Not all analyses by place will be equally informative. For example, sample the data shown in Table 1. 3. Where were the malaria cases diagnosed? What place does the table break the data down by? Would it have been more or less useful to crush the data according to the state of residence of the cases?We believe that it provides more useful information to show the data in Table 1. 3 by where the infection was acquired than it would have to show where the case-patients lived. By analyzing the malaria cases by place of acquisition, we can see where most of the malaria cases acquired their disease. Table 1. 3 Malaria cases by distribution of Plasmodium species and area of acquisition, United States, 1989 Species Area of Acquisition Vivax Falciparum Other agree Africa 52 382 64 498 Asia 207 44 29 280 Central America & Caribbe an 107 14 9 130 North America 131 3 13 147 (United States) (5) (0) (0) (5) South America 10 1 2 13 Oceania 19 2 5 26 unidentified 6 2 0 8 Total 532 448 122 1,102 Source 6By analyzing data by place, we can also get an idea of where the agent that causes a disease commonly lives and multiplies, what may carry or transmit it, and how it spreads. When we find that the occurrence of a disease is associated with a place, we can infer that factors that increase the risk of the disease are present either in the persons living there (host factors) or in the environment, or both. For example, diseases that are passed from one person to another tend to spread more rapidly in urban areas than in rural ones, mainly because the greater crowding in urban areas provides more opportunities for capable people to come into contact with someone who is septic.On the other hand, diseases that are passed from animals to humans often occur in greater numbers in rural and suburban areas because people in those areas are more likely to come into contact with disease-carrying animals, ticks, and the like. For example, perhaps Lyme disease has become more common because people have moved to wooded areas where they come into contact with infected deer ticks. Although we can show data by place in a tableas Table 1. 3 doesit is often better to show it pictorially in a map. On a map, we can use different shadings, color, or line patterns to indicate how a disease or health event has different numbers or risks of occurrence in different areas, as in Figure 1. 8. Page 18 Applied Epidemiology I Figure 1. 8 AIDS cases per 100,000 population, United States, July 1991-June 1992 Source 4For a rare disease or outbreak, we often find it useful to prepare a spot map, like Snows map of the Golden Square of London (Figure 1. 1), in which we mark with a dot or an X the relation of each case to a place that is potentially relevant to the health event being investigatedsuch as where each case lived or worked. We may also label other sites on a spot map, such as where we believe cases may have been exposed, to show the orientation of cases within the area mapped. Figure 1. 9 is a spot map for an outbreak of epidemic parotitis that occurred among employees of the Chicago futures throws. Study the location of each case in relation to other cases and to the traffic pits. The four numbered areas delineated with heavy lines are the transaction pits.Does the location of cases on the spot map lead you to any hypothesis about the source of infection? Figure 1. 9 Mumps cases in trading pits of exchange A, Chicago, Illinois, August 18-December 25, 1987 1 3 2 4 Key Pit areas are numbered and delineated by heavy lines. Individual trading pits within pit areas are outlined by light lines. affected person (N= 43) Desk areas Source CDC, unpublished data, 1988 Introduction to Epidemiology Epi 592J Page 19 You probably observed that the cases occurred primarily among those working in tradin g pits 3 and 4. This clustering of illness within trading pits provides indirect evidence that the mumps was transmitted person-to person. Person (Who? ) In descriptive epidemiology, when we organize or analyze data by person there are several person categories available to us. We may use inherent characteristics of people (for example, age, race, sex), their acquired characteristics (immune or marital location), their activities (occupation, leisure activities, use of medications/ baccy/drugs), or the conditions under which they live (socioeconomic status, access to medical care). These categories usually determine, to a large degree, who is at greatest risk of experiencing certain undesirable health conditions, such as becoming infected with a particular disease organism. We may show person-related characteristics in either tables or graphs.In analyzing data by person, we often must try a number of different categories before we find which are the most useful and enlightening. g row and sex are most captious we almost always analyze data according to these. Depending on the health event we are studying, we may or may not break the data down by other attributes. Often we analyze data by more than one characteristic simultaneously for example, we may look at age and sex simultaneously to see if the sexes differ in how they develop a condition that increases with agesuch as with heart disease. Age. Age is probably the single most important person attribute, because almost every health-related event or state varies with age.A number of factors that also vary with age are behind this association susceptibility, opportunity for exposure, latency or incubation period of the disease, and physiologic response (which affects, among other things, disease development). When we analyze data by age, we try to use age groups that are narrow enough to detect any agerelated patterns that may be present in the data. In an initial breakdown by age, we commonly use 5-year age intervals 0 to 4 years, 5 to 9, 10 to 14, and so on. Larger intervals, such as 0 to 19 years, 20 to 39, etc. , may conceal variations related to age which we need to know to identify the true ages at greatest risk.Sometimes, even 5-year age groups can hide important differences, especially in children less than five years of age. precede time to examine Figure 1. 10, for example, before you read ahead. What does the information in this figure suggest health regime should do to reduce the number of cases of whooping cough? Where should health authorities focus their efforts? You probably say that health authorities should focus on immunizing infants against whooping cough during the first year of life. Now, examine Figure 1. 11. This figure shows the same data but they are presented in the usual 5-year intervals. Based on Figure 1. 11 where would you have suggested that health authorities focus their efforts?Would this recommendation have been as effective and efficient in reduci ng cases of whooping cough? You probably said that health authorities should immunize infants and children before the age of 5. That recommendation would be effective, but it would not be efficient. You would be immunizing more children than actually necessary and wasting resources. Sex. In general, males have higher risks of illness and death than females do for a wide range of diseases. For some diseases, this sex-related difference is because of genetic, hormonal, anatomic, or other inherent differences between the sexes. These inherent differences affect their susceptibility or physiologic responses.For example, premenopausal women have a commence risk of heart disease than men of the same age. This difference is attributed to higher estrogen levels in women. On the other hand, the sex-related differences in the occurrence of many diseases theorise differences in opportunity or levels of exposure. For example, Figure 1. 12 shows that hand/wrist disorders occur almost twice as often in females than in males. What are some sex-related differences that would cause a higher level of this disorder in females? Page 20 Applied Epidemiology I Figure 1. 10 Pertussis (whooping cough) incidence by age group, United States, 1989 Source 9 Figure 1. 11 Pertussis (whooping cough) incidence by age group, United States, 1989 Source 9 Figure 1. 2 Prevalence of hand/wrist cumulative trauma disorder by sex, Newspaper Company A, 1990 Source NIOSH, unpublished data, 1991 Introduction to Epidemiology Epi 592J Page 21 You may have attributed the higher level of disorders in females to their higher level of exposure to occupational activities that require repetitive hand/wrist motion such as typing or keyboard entry. With occupationally-related illness, we usually find that sex differences polish the number of workers in those occupations. You may also have attributed the higher level of disorders in females to anatomical differences perhaps womens wrists are more susceptible to hand/wrist disorders. Ethnic and racial groups.In examining epidemiologic data, we are interested in any group of people who have lived together long enough to acquire common characteristics, either biologically or socially. Several terms are commonly used to identify such groups race, nationality, religion, or local reproductive or social groups, such as tribes and other geographically or socially isolated groups. Differences that we observe in racial, ethnic, or other groups may reflect differences in their susceptibility or in their exposure, or they may reflect differences in other factors that bear more directly on the risk of disease, such as socioeconomic status and access to health care. In Figure 1. 13, the risks of self-destruction for five groups of people are displayed. Figure 1. 3 Suicide death rates for persons 15 to 24 years of age according to race/ethnicity, United States, 1988 Source 22 Clearly this graph displays a range of suicide death rates for the five grou ps of people. These data provide charge for prevention programs and for future studies to explain the differences. socioeconomic status. Socioeconomic status is difficult to quantify. It is made up of many variables such as occupation, family income, educational achievement, living conditions, and social standing. The variables that are easiest to measure may not reflect the overall concept. Nevertheless, we commonly use occupation, family income, and educational achievement, while recognizing that these do not measure socioeconomic status precisely.The frequency of many adverse health conditions increases with decreasing socioeconomic status. For example, tuberculosis is more common among persons in lower socioeconomic strata. Infant mortality and time lost from work due to damage are both associated with lower income. These patterns may reflect more prejudicial exposures, lower resistance, and less access to health care. Or they may in part Page 22 Applied Epidemiology I reflec t an interdependent relationship which is unsurmountable to untangledoes low socioeconomic status contribute to disability or does disability contribute to lower socioeconomic status? Some adverse health conditions are more frequent among persons of higher socioeconomic status.These conditions include breast cancer, Kawasaki syndrome, and tennis elbow. Again, differences in exposure account for at least some of the differences in the frequency of these conditions. Exercise 1. 4 The following series of tables (Exercise 1. 4, Tables 1-4) show person information about cases of the unknown disease described in Figure 1. 4 on page 15. pick up again at Figure 1. 4, study the information in the four exercise tables and then describe in words how the disease outbreak is distributed by time and person. Exercise 1. 4, Table 1 relative incidence of the disease by age and sex in 24 villages surveyed for one year Males Females Age Group Population* Cases Risk per Population* Cases Risk per (years) 1,000 1,000