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INTRODUCTION TO EPIDEMIOLOGY

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INTRODUCTION TO EPIDEMIOLOGY

INTRODUCTION TO EPIDEMIOLOGY

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  • 1. DR. MAHESWARI JAIKUMAR
  • 2. “That branch of medical science which treats epidemics" (Parkin.1873)
  • 3. “The study of disease, any disease, as a mass phenomenon.” (Greenwood.1934)
  • 4. “The study of the distribution & determinants of disease frequency in man”(Mac Mohan,1960)
  • 5.  “The study of the distribution & determinants of health related states or events in specified populations and the application of this study to control of health problems”.
  • 6. DISEASE FREQUENCY. DISTRIBUTION OF DISEASE. DETERMINANTS OF DISEASE.
  • 7.  Refers to the measurement of health related event in the form of rates & ratios.  E.g.. Prevalence rate, Incidence rates, Death rate etc.  These rates are essential for comparing the disease frequency in different populations or sub groups of the same population
  • 8.  Such comparison yield valuable information on disease etiology.  This is a vital step in the development of strategies for prevention of control of health problems.
  • 9.  The basic tenet of epidemiology is that the distribution of disease occurs in patterns in a community.  An important function is to study the pattern of the distribution in various subgroups
  • 10.  Thus epidemiology examines whether there has been an increase or decrease over time span.  An important outcome of this step is formulation of etiological hypothesis
  • 11.  This aspect of epidemiology is known as “analytical epidemiology”.  Analytical strategies help in developing scientifically sound health programmes, interventions & policies.
  • 12.  To describe the distribution & magnitude of health & disease problems in human populations.  To identify etiological factors (Risk Factors)in the pathogenesis of disease
  • 13.  To provide the data essential to the planning, implementation & evaluation of services for the prevention, control & treatment of disease & to the setting up of priorities among those services.
  • 14.  To eliminate or reduce the health problem or it’s consequences.  To promote the health & well being of society as a whole.
  • 15. Asking questions.  Making comparison.
  • 16. QUESTIONS RELATED TO HEALTH EVENTS. QUESTIONS RELATED TO HEALTH ACTION.
  • 17.  What is the event? ( The problem).  What is the magnitude?  Where did it happen ?  When did it happen?  Who are affected?  Why did it happen?
  • 18.  What can be done to reduce this problem and its consequences?  How can it be prevented in future?  What action should be taken by the community? By whom these activities be carried out?
  • 19.  What resources are required? How are the activities to be organized?  What difficulties might arise, & how might they be overcome?
  • 20. The basic approach in epidemiology is to make comparison & draw inferences.  This may be comparison of two or more groups.     The first consideration before making . comparison is to the “comparability”. Matching or randomization helps in ensuring comparability.
  • 21.  Measurements of mortality.  Measurements of morbidity.  Measurements of disability.  Measurements of natality.
  • 22.  Measurement of the presence, absence or distribution of the characteristic or attributes of the disease.  Measurement of medical needs, health care facilities, utilization of health services & other related events.
  • 23.  Measurement of the presence, absence or distribution of the environmental & other factors suspected of the environmental & other factors suspected of causing the disease.  Measurement of demographic variables.
  • 24.  The epidemiologist usually expresses disease magnitude as a RATE, RATIO OR PROPORTION.
  • 25.  A rate measures the occurrence of some particular event in a population during a given time period. DEATH RATE = Number of deaths in a year *1000  MID YEAR POPULATION
  • 26.  A RATE COMPRISES THE FOLLOWING ELEMENTS.  Numerator,  Denominator,  Time Specification ,  And a Multiplier
  • 27.  CRUDE RATES : OR UNSTANDARDIZED RATES. Eg : Birth rates, Death rates.  SPECIFIC RATES : Actual observed rates due to specific causes during specific time periods.Eg: Tuberculosis – Annual, monthly rates. STANDARDIZED RATES : These are obtained by direct or indirect method of standardization.Eg: Age & Sex standardized rate. 
  • 28.     It expresses a relation in size between two random quantities. The numerator is not a part of the denominator. Ratio is the result of dividing one quantity by another. RATIO = x : y or x y
  • 29.  E.g. : The number of children with scabies at a certain time : The number of children with malnutrition at a certain time
  • 30.  A Proportion is a ratio which indicates the relation in magnitude of a part of the whole.  The numerator is always included in the denominator.
  • 31.  A proportion is usually expressed in percentage.  E.g. The number of children with scabies at a certain time *100 The total number of children in the village at the same time
  • 32.  Crude Death Rates.  Specific Death Rates.  Case Fatality Rates.  Proportional Mortality Rates.  Survival Rates.  Adjusted or Standardized Rates.
  • 33. Incidence. Prevalence.
  • 34.  The number of new cases occurring in a defined population during a specified period of time.
  • 35.  INCIDENCE =  Number of new cases of specific disease during a given period  Population at risk during that time *1000
  • 36. Only to new cases.  During a given period (one year).  In a specified population or “population at risk”, unless other denominators are chosen.  It can refer to new spells or episodes of disease arising.  Incidence measures the rate at which new cases are occurring in a population. 
  • 37. The incidence rates are health status indicator. It is useful for taking action.  To control disease.  For research into etiology.  For research into pathogenesis, distribution of disease & efficacy of preventive & therapeutic measures.  Provides useful insights into the effectiveness of the health services provided. 
  • 38.  Prevalence refers to ALL CURRENT cases (Old & New) existing at a given point of time, or over a period of time in a given population.  It is actually a ratio
  • 39.  POINT PREVALENCE.  PERIOD PREVALENCE.
  • 40.  Point Prevalence is defined as the number of all current cases (old & new) of a disease at one point of time, in relation to a defined population.
  • 41.   PP = Number of all current cases (old & new) of a specified disease existing at a given point in time.
  • 42.  It measures the frequency of all current cases ( old & new ) existing during a defined period of time. (Annual prevalence).  It includes cases arising before but extending into or through to the year as well those cases arising during the year.
  • 43.   Number of existing cases (old & new) of a specified disease during a given period of time interval Estimated mid interval population at risk X 100
  • 44. Case 1 Case 2 Case 4 Case 3 Case 5 Case 7  Jan 1 Case 6 Case 8 Dec 31 Incidence : case 3,4,5 & 8. Point prevalence Jan 1 : 1,2 & 7. Point prevalence Dec 31 : 1,3,5 & 8. Period prevalence (Jan – Dec) 1,2,3,4,5,7 & 8
  • 45. Prevalence depends upon : 1. Incidence. 2. Duration of illness.  FORMULA : P = I * D  I = INCIDENCE  D= MEAN DURATION  Therefore : I = P/D  D= P/I   
  • 46. Descriptive studies are usually the first phase of an epidemiological investigation.  These studies are concerned with observing the distribution of disease or health – related characteristics in human populations.  Such studies basically ask the questions. 
  • 47.  When is the disease occurring?  Where is it occurring?  Who is getting the disease?
  • 48. Defining the population to be studied.  Defining the disease to be studied.  Describing the disease by --- TIME, PLACE & PERSON.  Measurement of disease.  Comparing with known indices.  Formulation of an aetiological hypothesis 
  • 49.  Descriptive studies are investigations of populations.  Therefore the first step is to define the “population base” in terms of total number, & also by composition in terms of age , sex, occupation, cultural characteristics & similar other information.
  • 50. The “defined population” can be the whole population in a geographic area or a representative taken from it.  The defined population should be large enough so that the specific rates are meaningful.  The community chosen should be stable & not migratory. 
  • 51. The epidemiologist looks for an operational definition.  Operational definition spells out the criteria by which the disease can be measured.  Once operational definition is established, it should be maintained through the study. 
  • 52.  Disease is described by person, place & time distribution.
  • 53. TIME PLACE Year, Season Climatic zones PERSON Age, Birth order Month, Week Country, region Sex, Family size Day, Hour of Urban/ rural / onset Local community Marital State, Height, Weight Duration Occupation, Social status, Education, Blood pressure, Blood cholesterol, Personal Towns, Cities, Institutions
  • 54.  The pattern of a disease may be described by the time of occurrence.  Whether it shows periodic increase?  Whether it follows a consistent trend?  Epidemiologists have identified three kinds of time trends or fluctuations in disease occurrence.
  • 55.  SHORT TERM FLUCTUATIONS.  PERIODIC FLUCTUATION.  LONG – TERM or SECULAR TRENDS
  • 56.  The best known short term fluctuation in the occurrence of disease is an epidemic.  Epidemic is defined as : the occurrence in a community or region of cases of an illness or other related events clearly in excess of normal expectancy”
  • 57.  A. Common Source Epidemics.  B. Propagated Epidemics.  C. Slow (or) Modern Epidemics.
  • 58.  Single Exposure or “POINT SOUIRCE” epidemics.  Continuous or “MULTIPLE EXPOSURE EPIDEMICS”
  • 59.  A graph of the time distribution of epidemic cases is called the “EPIDEMIC CURVE” An epidemic curve may suggest,  1. Time relationship with exposure to a suspected source.  2. A Cyclical or Seasonal pattern suggestive of a particular infection 
  • 60. EXPOSURE NUMBER OF CASES TIME
  • 61.   These are also known as “point Source” epidemics. The exposure to the disease agent is brief & essentially simultaneous, the resultant cases all develop within one incubation period of the disease. They are of two types :  1. Common Source Single Exposure Epidemics.  2. Common Source Continuous or Repeated exposure. 
  • 62.  The exposure to the disease agent is brief & essentially simultaneous, the result cases all develop within one incubation period of the disease.  E.g., An epidemic of food poisoning
  • 63. EXPOSURE NUMBER OF CASES TIME
  • 64.  Common Source Single Exposure Epidemic curve usually has one peak.  One point of interest is the “median incubation period”.  It is the time required for 50 per cent of the cases to occur following exposure.
  • 65.  The epidemic curve rises & falls rapidly , with no secondary waves.  The epidemics tends to be explosive.  There is clustering of cases over a narrow interval of time.  All the cases develop within one incubation period of disease.
  • 66. Common source epidemics are frequently, but not always due to exposure to an infectious agent.  They can result from contamination of the environment (air, water, food, soil) by industrial chemicals or pollutants, E.g., Bhopal gas tragedy in India & Minamata disease in Japan resulting from consumption of fish containing high concentration of methyl mercury 
  • 67.  If the epidemic continues over more than one incubation period, there is either a continuous or multiple exposure to a common source, or a propagated spread.
  • 68.  Some times the exposure from the same source may be prolonged – continuous or repeated or intermittent – not necessarily at the same time or place.  A prostitute may be a common source on gonorrhea outbreak, but since she will infect her clients over a period of time there may be no explosive rise in the number of cases.
  • 69. A well of contaminated water or a nationally distributed brand of vaccine or food could result in similar outbreaks.  The outbreak continued beyond the range of one incubation period.(1976 – Legionnaire’s disease)  There was no evidence of secondary cases among persons who had contact with ill persons. 
  • 70.  Water borne cholera is a familiar example, the epidemic reaches a sharp peak, but tails off gradually over a longer period of time.
  • 71.    A propagated epidemic is most often of infectious origin & results from person to person transmission of an infectious agent. The epidemic usually shows a gradual rise & tails off over a much longer time. Transmission continues until the number of susceptibles is depleted or susceptible individuals are no longer exposed to infected persons or intermediary vectors.
  • 72.  The speed of spread depends upon herd immunity, opportunities for contact & secondary attack rate.  Propagated epidemics are more likely to occur where there is a regular supply of new susceptible individuals lowering herd immunity.
  • 73. INITIAL EPIDEMIC HEIGHT OF EPIDEMIC TERMINATION OF EPIDEMIC
  • 74.  Two types of periodic fluctuation may be described.  1. SEASONAL TREND.  2. CYCLIC TREND.
  • 75. Seasonal trend is a well known trend in many communicable disease measles, varicella, malaria.  Measles is usually at its height in early spring.  Bacterial gastrointestinal infections are prominent in summer months because of warm weather & rapid multiplication of flies. 
  • 76. Some disease occur in cycles spread over short periods of time which may be days, weeks, months or years..  E.g., Rubella occurred every 6-9 years.  This is due to naturally occurring variations in herd immunity.  A build up of susceptible is again required in the herd before there can be another attack. 
  • 77.  Influenza pandemics are known to occur at intervals of 7-10 years due to antigenic variations.
  • 78.    The term “secular trends” implies changes in the occurrence of disease over a long period or time, generally several years or decades. Secular trend implies a consistent tendency to change in a particular direction or a definite movement in one direction. E.g., Coronary heart disease, lung cancer have shown consistent upward trend in the developed countries during the past 50 years.
  • 79.  Study of the geography of the disease (geographical pathology)is one of the important dimensions of descriptive epidemiology.  With the geographical pathology we gain perspective on the fascinating differences in disease patterns between two geographical areas.
  • 80.  The relative importance of genes versus environment; changes with migration; the possible role if diet & other etiological factors.  Geographical diseases have profoundly influenced our understanding of disease, its nature, its detriments & its relation to subsequent pathology.
  • 81. The geographic variation in disease occurrence has been one of the stimulants to national & international studies.  The world is not a uniform unit.  Cultures, standard of living & external environments vary greatly. The use of migrant studies is one way to distinguishing genetic & environmental factors. 
  • 82.      Geographic patterns provide an important source of clues about the causes of the disease. The geographic variations may be classified as : 1. International variations. 2. National variations. 3. Rural – Urban differences. 4. Local distributions
  • 83.  There is a marked international differences in the occurrence of various disease. This variations have stimulated epidemiologists to search for cause – effect relationships between the environmental factors & disease.  The aim is to identify factors which are crucial in the cause & prevention of disease
  • 84.  E.g., Cancer of the oral cavity & uterine cervix are exceedingly common in India as compared to industrialized countries.  There is marked difference between the incidence of each cancer in different parts of the world. It is common in Japan, but unusual in USA.
  • 85.  Variations in disease occurrence also exist within countries or national boundaries.  Distribution of lathyrism, endemic goitre, flurosis, leprosy, malaria, nutritional deficiency diseases have all shown variations in their distribution in India, with some part of the country more affected than the others.
  • 86.  Rural Urban variations are well known.  Chronic bonchitis, lung cancer, cardio vascular diseses, mental illness & drug dependence are usually more frequent in in urban areas than in rural areas.
  • 87.    On the other hand, skin & zoonotic diseases & soil transmitted helminths may be more frequent in rural areas than in urban areas. Death rates especially maternal mortality rates are higher for rural than urban areas. These variations may be due to variations in population density, social class, deficiencies in health services, levels of sanitation, education & environmental factors.
  • 88.  The epidemiologists seek to define groups which are at higher risk for a particular diseases, and provides guidelines to the health administrator for their prevention & control.
  • 89. Inner & outer city variations are common.  These variations are best studied with the aid of “spot maps” or “shaded maps”.  These maps show at a glance areas of high or low frequency, the boundaries & patterns of disease distribution. 
  • 90.    If the map shows “clustering” of cases , it may suggest a common source of infection or a common risk factor shared by all cases. E.g., John Snow’s cholera epidemic. Geographic differences in disease occurrence is an important dimension of a descriptive study. These differences are determined by the agent, host & environmental factors.
  • 91.  Large scale migration of human population from one country to another provides a unique opportunity to evaluate the role of the possible genetic & environmental factors in the occurrence of disease in a population. Migration studies can be carried out in two ways :  1. Comparison of disease & death rates for migrants with those of their kin who have stayed at home.
  • 92.  2. Comparison of migrants with local population of the host country provides information on genetically different groups living in a similar environment.
  • 93.  In descriptive studies disease is further characterized by defining the persons who develop the disease by age, sex, occupation, marital status, habits, social class & other host factors.  These host factors help us to understand the natural history of disease.
  • 94. Age is strongly related to disease than other host factors.  Certain factors are more frequent in certain age groups than others.  E.g., Measles in childhood, cancer in middle age & atherosclerosis in old age.  Many chronic degenerative diseases show an increasing in the prevalence with advancing age. 
  • 95. Some times there may be two separate peaks instead of one in the age incidence curve of a disease as in the case of Hodgkin’s disease, leukaemia & female breast cancer.  This phenomenon is known as bio modality.  This suggests that two set of causal factors might be operative. 
  • 96. incidence 7 6 5 4 3 2 1 0 0 10 20 30 40 50 60 70 80
  • 97.  Gender is another host characteristics which is often studied in relation disease using indices such as sex – ratio, sex specific morbidity & mortality rates.  It has been found that certain chronic diseases such as diabetes, hyperthyroidism & obesity are strikingly more common in women than in men & lung cancer & CHD are less frequent in women
  • 98.  Variations in disease frequency between sexes have been ascribed to 1. biological differences including sex linked genetic inheritance & 2. cultural & behavioral differences between sexes (smoking, alcohol, automobile use).
  • 99.  Differences in disease occurrence have been noted between population subgroups of different racial & ethnic origin.  These include tuberculosis, essential hypertension, coronary heart disease, cancer, & sickle cell anemia.
  • 100.  Studies related to marital status reveal that mortality rates were always lower for married males & females than for the unmarried, of the same age & sex.  Marital status can be a risk factor for some disease & conditions.
  • 101.  The observation that cancer cervix is rare in nuns led to the hypothesis regarding marital status & cancer cervix.  Further studies led to the suggestions that cancer cervix may be associated with multiple sexual contacts & promiscuity.
  • 102. It is now recognized that man’s occupation has an important bearing on his health status.  Occupation may alter the habit pattern of an employee e.g., sleep, alcohol, smoking, night shifts, etc.   It is obvious that persons working in a particular occupations are exposed to particular types of risk.
  • 103.  Workers on coal mines are more likely to suffer from silicosis, those in sedentary occupations face the risk of heart disease.
  • 104.  Epidemiological studies have shown that health & illness are not equally distributed in social classes.  Individuals in the upper social classes have long life & better nutritional status than those in the lower social groups.
  • 105.  Certain diseases like CHD, hypertension, diabetes have shown a higher prevalence in upper classes than in lower classes.  Social class differences have also been observed in mental illness & utilization of medical & health care services.
  • 106.  Human behavior is increasingly looked upon as a risk factor in modern day disease such as coronary heart diseases, obesity & accidents.  The behavioral factors which have attracted the greatest attention are cigarette smoking, sedentary life, over eating & drug abuse.  Mass movement of people such as pilgrimages lend themselves to the transmission of infectious diseases
  • 107.  Stress has been shown to affect a variety of variables related to patients response, e.g., susceptibility to disease, exacerbation of symptoms, compliance with medical regimen, etc.
  • 108.    In India diseases like leprosy, filaria & malaria are considered to be rural problems. Because of the movement of people from rural to urban areas these diseases have created a serious problem in urban areas also. Human movement can be classified as 1. short term, long term & permanent, 2. according to age, sex, occupation, 3. internal or external, 4. urban versus rural.
  • 109.  It is mandatory to have a knowledge on the disease load in the community.  This information should be available in terms of mortality, morbidity, disability & incidence & prevalence so on.  Incidence can be obtained from longitudinal studies & prevalence from cross sectional studies. 
  • 110.  Are simplest form of an observational studies.  It is based on a single examination of a cross section of population at one point of time. Cross sectional studies are also known as prevalence studies.   Cross sectional studies are more useful for chronic diseases
  • 111.  Cross sectional diseases provide very little information about the natural history of the disease or about the occurrence of new cases.
  • 112.  In longitudinal studies observations are repeated in the same population over a prolonged period of time by means of follow up examinations.  Cross sectional studies have been likened to a photograph, & longitudinal studies to a cine film
  • 113.      Longitudinal studies are useful : 1. To study the natural history of a disease & its future outcome. 2. For identifying risk factors of a disease. 3. For finding out incidence rates or occurrence of new cases in the community. Longitudinal diseases are more difficult to organize & more time consuming
  • 114.  The essence of epidemiology is to make comparisons & ask questions.  By making comparisons between different populations & sub groups of the same population, it is possible to arrive at clues to disease aetiology.  We can also identify the at risk group
  • 115.  A hypothesis is a supposition, arrived at from observation or reflection.  It can be accepted or rejected using the techniques of analytical epidemiology.
  • 116.  A hypothesis should specify the following :     1. The population. 2. The specific cause being considered. 3. Expected outcome – disease. 4. Time response relationship.
  • 117.  Provide data regarding the magnitude of the disease load & types of disease problems in the community in terms of morbidity & mortality rates.  Provide clues to disease aetiology.
  • 118.  Provide background data for planning, organizing & evaluating preventive & curative services.  Contribute to research by describing variations in disease occurrence by time, place & person.
  • 119.  In contrast to the descriptive studies ( the focus is on the population on the whole), the analytical studies focus on individual within the population. Analytical studies comprise of two distinct types of observational studies.  1. Case Control Studies.  2. Cohort studies. 
  • 120. Case control studies Factor(s) present / Absent Individual exposed to particular (s) / individual unexpected to particular factor(s) Cohort studies •Individuals with particular disease --Cases •Individuals without particular disease --Controls PROSPECTIVE COHORT STUDY Presence or absence of a particular disease TIME
  • 121.  Case control studies is often called “retrospective studies”.  This is the first approach to test causal hypothesis.  The case control method has three distinct features.
  • 122.  Both exposure & outcome (disease) have occurred before the start of the study.  The study proceeds backwards from effect to cause.  It uses a control or comparison group to support or refute an inference.
  • 123.  Selection of cases & control.  Matching.  Measurement of exposure.  Analysis & interpretation.
  • 124.      SELECTION OF CASES : Definition of a case is crucial to a case control study. It involves two specifications.1. Diagnostic criteria. 2. Eligibility criteria. DIAGNOSTIC CRITERIA : Specifies the diagnostic criteria & the stage of the disease. ELIGIBILITY CRITERIA : Only newly diagnosed individuals with in specified time are eligible.
  • 125.      The sources may be drawn from, 1. Hospitals. 2.General Population. HOSPITALS : It is convenient to select from hospitals or network of hospitals, admitted during a specified period of time. GENERAL POPULATION : In a population based study all cases within in a defined geographic area are included (entire cases or randomly selected)
  • 126.    The controls must be free from the disease under study. They must be similar to the cases as possible, except for the absence of the disease under study. Selection of an appropriate control group is an important pre requisite, for it is against this we will be making comparisons.
  • 127.  1.Hospital controls.  2.Relatives.  3.Neighbourhood controls.  4.General population.
  • 128. The controls may differ from the cases in a number of factors such as age, gender, occupation, social status, etc.  An important consideration is to ensure comparability between cases & controls.  This involves what is known as “MATCHING” 
  • 129.  Matching is defined is to ensure comparability between cases & controls in such a way that they are similar to cases with regard to certain pertinent selected variables e.g. age, which are known to influence the outcome of the disease, or distort or confound the results.
  • 130.  A confounding factor is defined as one which is associated both with exposure & disease, & is distributed unequally in study & control groups.
  • 131.  This may be obtained by interviews, by questionnaires or by studying past records of cases & controls hospital records, employment records.
  • 132.  The final step is analysis, to find out :  1. Exposure rates among cases & controls to suspected factor.  2.Estimation of disease risk associated with exposure ( odds ratio )
  • 133. Cases (with Ca lung ) Controls (without Ca lung ) Smokers ( < 5 cigarettes a day ) 33 (a) 55 (b) Non smokers 2 (c) 27 (d) 35 (a+c) 82 (b+d) Total
  • 134.  CASES = a a+c = 33 / 35 = 94.2 % CONTROLS = b/(b+d) =55/82 = 67 %
  • 135. The second analytical step is estimation of disease risk associated with exposure.  The estimation of disease risk associated with exposure is obtained by an index known as the “Relative Risk” (RR) or “Risk Ratio”, which is defined as the ratio between the incidence of disease among exposed persons & incidence among non exposed. 
  • 136.  It is given by the formula : Relative Risk = Incidence among exposed  Incidence among non exposed  = a/(a+b)  c/(c+d) 
  • 137.  Odds Ratio (OR) is the measure of the strength of the association between risk factor & outcome.  The odds ratio is the cross product of the entries in table.
  • 138. Disease Yes No Exposed a b Not exposed c d Odds Ratio = ad/bc = 33 x 27 55 x 2 = 8.1 Odds ratio is a key parameter in the analysis of case control studies
  • 139. Relatively easy to carry out.  Rapid & expensive.  Suitable to investigate rare diseases.  No risk to subjects.  Allows the study of several different aetiological factors.  Risk factors can be identified.  No attrition problems.  Ethical problems minimal 
  • 140.       Problems of bias relies on previous records. Selection of an appropriate control group may be difficult. We cannot measure incidence,& can only estimate the relative risk. Do not distinguish between causes & associated factors. Not suited to evaluation of therapies. Representativeness is a major concern in case of both cases & controls.
  • 141.  Cohort study is a type of analytical study.  Cohort study is known by a variety of names: prospective study, longitudinal study, incidence study & forward looking study.
  • 142. When there is a good evidence of an association between exposure & disease.  When exposure is rare, but incidence is high among the exposed.  When attrition of the study population can be minimized.  When ample funds are available. 
  • 143. Disease Yes No Exposed a b Not exposed c d Total a+b c+d
  • 144.  Prospective cohort study.  Retrospective cohort study.  Combined of retrospective & prospective cohort study
  • 145.  The elements of cohort study are :  1.Selection of study subjects.  2.Obtaining data on exposure.  3.Selectionof comparison group.  4.Follow up.  5.Analysis.
  • 146.  The subjects of cohort study are selected from general population or select groups within the population.  GENERAL POPULATION: When the exposure or cause of death is fairly frequent in the population, cohorts may be assembled from the general population. If the population is large appropriate sample is taken from the population  
  • 147. SPECIAL GROUPS :  These may be special groups that can readily be studied.(select groups – these may be professional groups; doctors, nurses, lawyers, college alumni, government employees, volunteers, etc.   These groups are usually homogenous population
  • 148.   EXPOSURE GROUPS : If the exposure is rare, an economical procedure is to select a cohort of persons known to have experienced the exposure.
  • 149. Information about exposure may be obtained from :  1.COHORT MEMBERS-personal interviews, mailed questionnaires.  2.REVIEW OF RECORDS  3.MEDICAL EXAMINATION/SPECIAL TESTS.  4.ENVIRONMENTAL SURVEYS 
  • 150.  Information about exposure should be collected in a manner that will allow classification of cohort members: 1. according to whether or not they have been exposed to the suspected factor.  2. according to the level or degree of exposure, in the case of special exposure groups. 
  • 151. Classification of exposure (cigarettes) ½ pack 1/2 – 1 pack 1 -2 pack 2 packs + No of deaths 24 84 90 97 Death rate 95.2 107.8 229.2 264.2
  • 152.  Comparison may be :  1.Internal Comparison.  2.External comparison.  3.Comparison with the general population
  • 153.    INTERNAL COMPARISON : The comparison groups are in built. Single cohorts enter the study & its members may, on the basis of information obtained, be classified into several comparison groups according to the degree or levels of exposure to risk (table - 1)
  • 154.    EXTERNAL COMPARISON : When information on degree of exposure is not available, it is necessary to put up an external control, to evaluate the experience of the exposed group. E.g., smokers with non smokers, cohort of radiologist compared with ophthalmologist.(The study & control cohorts should be similar in demographic & possibly important variables, other than those under study)
  • 155.  COMPARISON WITH GENERAL POPULATION RATES :  If none is available, the mortality experience of the exposed groups is compared with the mortality experience of the general population in the same geographic area.
  • 156.  Follow up is an important aspect of the cohort study. The procedures required comprise : 1. Periodic medical examination of each member of the cohort.  2. Reviewing physician & hospital records.  
  • 157.  Routine surveillance of death records.  Mailed questionnaires, telephone calls, periodic home visits – preferably all three on an annual basis.
  • 158.  The data are analyzed in terms of :  Incidence rates among outcome among exposed & non exposed.  Estimation of risk.
  • 159. Cigarette smoking Cases (with Ca lung ) Controls (without Ca lung ) Total Yes 70 (a) 6930 (b) 7000 (a+b) No 3(c) 2997(d) 3000 (c+d)
  • 160.  Incidence rates :  Among smokers = 70/7000 = 10 / 1000.  Among non smokers = 3/3000 = 3 / 1000.  Statistical Significance = P<0.001
  • 161.   ESTIMATION OF RISK : RELATIVE RISK : RR is the ratio of the incidence of the disease or death among exposed & the incidence among non exposed.   RR = Incidence among exposed Incidence among non exposed.  RR = 10/1=10  (it is the measure of the strength of association between suspected cause & effect
  • 162.  AR is the difference in incidence rates of disease between an exposed group & non exposed group.  AR = Incidence of disease rate among exposed minus incidence of disease rate among non exposed  Incidence rate among exposed
  • 163.    10 -1 * 100 = 90% 10 Attributable risk indicates to what extent the disease under study can be attributed to the exposure.  90% of the lung cancer among smokers was due to their smoking. This suggests the amount of disease that might be eliminated if the factor under study could be controlled or eliminated
  • 164.  Population Attributable Risk is the incidence of the disease in the total population minus the incidence of disease among those who were not exposed to the suspected causal factor
  • 165. Deaths per 100,000 persons - years  = 224 (a) exposed = 10 (b) non exposed Deaths in total population = 74(c)  Individual RR  Population AR   Heavy smokers Non smokers = a/b =224/10 =22.40 =(c-b)/c = 86%
  • 166.      Incidence can be calculated. Several possible outcomes related to exposure can be studied simultaneously. Provide a direct estimate of relative risk. Dose Response ratio can be calculated. Certain form of bias can be minimized as comparison groups are formed before disease develops
  • 167. N CASE CONTROL o STUDY from effect to 1 Proceeds COHORT STUDY Proceeds from cause to effect cause 2 Starts with the disease Starts with people exposed to risk factor or suspected cause 3 Tests whether the suspected cause occurs more frequently in those with the disease than among those without the disease Tests whether disease occurs more frequently in those exposed, than in those not similarly exposed
  • 168. 4 First test to test the hypothesis Reserved for testing of precisely formulated hypothesis 5 Involves fewer number of subjects Involves larger number of subjects 6 Yields relatively quick results Long follow up period
  • 169. 7 Suitable for study of rare diseases Inappropriate when the disease under investigation is rare 8 Generally yields Yields incidence rates, only estimate of RR RR as well as RR 9 Relatively Expensive inexpensive
  • 170.    Experimental studies are directly controlled & carried out under the investigator. Experimental epidemiology is often equated with Randomized Control Trials. Experimental studies involve some action, intervention or manipulation such as deliberate application or withdrawal of the suspected cause.
  • 171.  1. To provide scientific proof of aetiologic or risk factor.  2. To provide a method of measuring the effectiveness & efficiency of health services for the prevention, control & treatment of disease & improve the health of the community
  • 172.  1. Animal studies.  2.Human experiments.
  • 173.  Animal studies have contributed to our knowledge of anatomy, physiology, pathology, microbiology, immunology, genetics, etc.  Classical animal experiments have given us a wide range of knowledge.
  • 174.  Important application of animal experiments are:  1.experimental reproduction of human disease in animals to confirm etiological hypothesis & to study the patho genetic phenomenon or mechanisms.
  • 175.  2.Testing the efficacy or preventive & therapeutic measures such as vaccines, drugs.  3.Completing the natural history of disease.
  • 176.  1.Experimental animals can be bred in laboratories & manipulated easily according to the wishes of the investigator.  2.They multiply rapidly & enable the investigators to carry put certain experiments (genetic experiments) which in human population would take several years..
  • 177.  1. Not all human diseases can be reproduced in animals.  2.All conclusion drawn from animal experiments may not be strictly applicable to human beings. There are difficulties encountered in extrapolating findings from animal experiments in man
  • 178.  1. Human experiments are always needed to investigate disease etiology & to evaluate the preventive & therapeutic measures.  2. Before launching human experiments, the benefits of the experiments have to be made aware of all possible consequences of the experiment.
  • 179.  Experimental studies are of two types :  1.RCT.  2.Non RCT.
  • 180.         The design of a randomized controlled trial is as follows. The basic steps in conducting a RCT include the following: 1.Drawing up a protocol. 2.Selecting reference & experimental populations. 3.Randomization. 4.Manipulation or intervention. 5.Follow up. 6.Assessment of outcome.
  • 181.  1. Select suitable population  2. Select suitable sample  3. Make necessary exclusions  4. RANDOMIZE  Experimental group Control group  6.Manipulation & follow up Not eligible No consent
  • 182.  The protocol :  1. Specifies the aims & objectives of the study.  2. Questions to be answered.  3. Criteria for the selection of the study & control groups.
  • 183.  4. Size of the sample.  5. The procedures for allocation of subjects into the study.  6. Treatments to be applied.
  • 184. 7.When & Where & how to what kinds of patients.  8.Standardization of work procedures.   Once the protocol has been evolved, it should be strictly adhered to throughout the study. Preliminary runs may be made to test the feasibility of the study.
  • 185.  REFERENCE OR TARGET POPULATIONS:  1. It is the population to which the findings of the trial, if found successful, are expected to be applicable.  2. A reference population may be as broad as a general population.
  • 186.  EXPERIMENTAL OR STUDY POPULATION :  1.The study population is derived from the reference population.  2.It is the actual population that participates in the study.  3.Ideally it should be randomly chosen from the reference population.
  • 187.  4. They must give an informed consent.  5. They should be representatives of the population to which they belong.  6. They should be qualified or eligible for the study.  7. Participants must be fully susceptible to the disease under study.
  • 188.  Randomization is a statistical procedure by which the participants are allocated into groups usually called “study” & “control” groups to receive or not to receive an experimental preventive or therapeutic procedure, manoeuvre or intervention.
  • 189.  1.Randomization is the “heart” of a control trial.  2.It will the greatest confidence that the groups are comparable so that “like can be compared with like”.  3.It ensures that the investigator has no control over the allocation of the participants to either study or control group
  • 190.  4.This eliminates selection bias.(Every individual gets an equal chance of being allocated into either group or any of the trial groups).  5. Randomization is best done by using a table of random numbers.
  • 191.  The experimental group is intervened or manipulated, by deliberate application or withdrawal or reduction of the suspected causal factor. (drug, vaccine, dietary component as laid down in the protocol).
  • 192.  The manipulation creates an independent variable whose effect is then determined by measurement of the final outcome, which constitutes the dependent variable (incidence of disease)
  • 193.  1.This implies examination of the experimental & control group subjects art defined intervals of time, in a standard manner. 2.The follow up may be short of for a long time.  3. There could be problems of attrition. 
  • 194. 1.The final step is to assess the result of the intervention.  2.It may be a positive outcome or a negative outcome.   3.The positive or negative result is rigorously compared both with the experimental & control groups.
  • 195. Blinding can be done in three ways.  SINGLE BLIND : The trial is so planed that the participant is not aware whether he belongs to the study or the control group.   DOUBLE BLIND TRIAL : The trial is so planned that neither the doctor nor the participant is aware of the group allocation & the treatment received.
  • 196.  TRIPLE BLIND : This goes one step further. The participant, the investigator & the person analyzing the data are all blind. Ideally the triple blinding should be used.  But, most commonly the double blind is used. 
  • 197.  1. Concurrent parallel study designs.  2. Cross over type of study designs.
  • 198. Random assignment PATIENTS Exposed to specific treatment Compare Outcome Un exposed to specific treatment TIME Random assignment PATIENTS Exposed to specific treatment Un exposed to specific treatment Compare Outcome – Exposed & Un exposed
  • 199.  Comparison are made between two randomly assigned groups, one group exposed to specific treatment, & the other group not exposed. Patients remain in the study group or the control group for the duration of the investigation
  • 200.  In this type of study each patient serves as his own control  The patients are randomly assigned to the control & the study groups.  The study group receives treatment under consideration.  The control group receives a placebo.
  • 201.  Then patients are in each group are taken off their medication or placebo to allow for the possibility of any “carry over” effects.  After this period of medication the two groups are switched.
  • 202.  1.clinical trials.  2.preventive trials.  3.risk factor trials.  4.cessation experiments.  5.trial of etiological agents.  6.evaluation of health services.
  • 203.  Clinical trials have been concerned with evaluation therapeutic agents, mainly drugs.  A clinical trial is a powerful tool that is carried out before any new therapy, procedure or service is introduced.
  • 204.  Preventive trial implies trials of primary prevention measures.  These trials are purported to prevent or eliminate on an experimental basis.  The most frequently occurring trials of vaccines
  • 205. The basic experimental designs are applicable for these trials.  Analysis of a preventive trial must result in a clear statement about:  1.The benefit that the community will derive from the measure.  2. The risks involved.  3. The costs to the health services in terms of man, money, material resources. 
  • 206.  This is a preventive trial in which the investigator intervenes to interrupt the usual sequence in the development of disease for those individuals who have “risk factor”, for developing disease.
  • 207. In this type of study, an attempt is made to evaluate the termination of a habit, (or a removal of the suspected etiological factors),which is associated to the causal of disease.  If such action is followed by a significant in the reduction in the disease, the hypothesis if the cause is greatly strengthened. 
  • 208.  A trial of the etiological agents are under taken & followed up for the development of the effect or the disease.  E.g.,Retrolental fibroplasia as a cause of blindness among pre mature babies.
  • 209.    RCT have been extended to assess the effectiveness & efficiency of health services. Often choices have to be made between alternative policies of health care delivery services. The necessity of choice results from the fact that resources are limited & priorities must be set for the implementation of a large number of activities which could contribute to the welfare of the society.
  • 210.  1.Uncontrolled trials.  2.Natural experiments.  3.Before & after comparisons studies
  • 211. 1.To study the natural history of disease in the population.  2.Community diagnosis.  3.Planning & evaluation.  4.Evaluation of individual’s risks & chances.     5.Syndrome identification. 6.Completing the natural history of the disease. 7.Searching for causes & risk factors.
  • 212.  1. Epidemiology aims at closely studying the diseases load in the community  2. Epidemiology provides a means to study disease profiles & time trends in human population.
  • 213.  3.By a study of these trends, we can make useful projections into the future & identify emerging health problems & their correlates.
  • 214.  4.Epidemiology provides information about the disease fluctuations in the community.
  • 215.  1.Epidemiology helps in diagnosing the health status of the community.  2.It quantifies the health related events in the community in terms of morbidity, mortality, natality , disability & other statistics related to the health events in the population.
  • 216.  3.By quantification of health problems, we lay down priorities in disease control & prevention.  4.Quantification of morbidity & mortality serves as a benchmark for the evaluation of health services. at a later date.
  • 217.  5.Quantification of health problems can be a source of new knowledge about disease distribution, causation & prevention.  6.Community diagnosis has been effectively extended beyond population distributions & profiles of illness to include an understanding of the social, cultural & environmental characteristics of the community.
  • 218.  7.Epidemiology therefore has been described as a “DIAGNOSTIC TOOL”
  • 219.  1.Planning is essential for a rational allocation of the resources.  2.Epidemiologic information about the distribution of health problems over time & place provides the fundamental basis for planning & developing the needed health services.
  • 220.  3.Epidemiology helps in assessing the impact of the health services provided to address people’s problems.  4.The application of epidemiological principles to problems of health care constitutes the “new epidemiology”, E.g. planning facilities for medical care, man power planning.
  • 221.  5.Epidemiology helps in evaluating the health care services outcome.  6.The development of RCT has made it possible to evaluate treatment modalities on a firm scientific basis.
  • 222. 1.One of the important tasks of an epidemiologist is to make a statement about the degree of risk in a population.  2.Study of Relative Risk, Attributable Risk,Population Atributable risk, & other parameters related of the strength between cause & association offer us information on risk status of an individual & community. 
  • 223.  1.Medical syndromes are identified by observing frequently associated findings in individual patients.  2.Epidemiological investigations can be used to define & redefine syndromes.
  • 224.  3.Epidemiological studies have been able to correct misconceptions concerning many disease syndrome.
  • 225.  Epidemiology is concerned with the entire spectrum of disease in a population.  2.The epidemiologist by studying the disease patterns in the community are in a better position to fill the gaps in the natural history of diseases.
  • 226.   3.Epidemiological investigations yield a large amount of data on risk factors in relation to chronic diseases.
  • 227.  1.Epidemiology by relating disease to inter population differences & other attributes of the population tries to identify the caused of the diseases.  2.The concept of “risk factors” give us renewed impetus to epidemiologic research.
  • 228. EPIDEMIOLOGY