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1 : Basics of Epidemiology and its application Dr. Mahesh. V Postgraduate Dept of community medicine KIMS,Hubli
2 : Historical context Originates from Hippocrates’ observation more than 2000 years But nineteenth century marked the begining of epidemiology. The finding by John Snow that the risk of cholera in London was related to the drinking of water supplied by a particular company(southwark company) provides a well-known example. Comparing rates of disease in subgroups of the human population became common practice in the late nineteenth and early twentieth centuries.
3 : This approach was to be useful way of linking environmental conditions or agents to specific diseases. In the second half of the twentieth century, these methods were applied to chronic noncommunicable diseases such as heart disease and cancer, especially in middleand high-income countries.
4 : EPIDEMIOLOGY IS BOTH THE BASIC SCIENCE OF PUBLIC HEALTH AND ITS MOST FUNDAMENTAL PRACTICE MAXCY
5 : RIGHT HAND OF COMMUNITY MEDICINE COMMUNITY MEDICINE EPIDEMIOLOGY BIOSTATISTICS
6 : EPIDEMILOGY PROVIDES INTELLIGENCE FOR HEALTH ACTION J. N. MORRIS INTELLIGENCE MEANS INFORMATION REGARDING THE DETERMINANTS OF HEALTH & DISEASE AND THEIR OCCURRENCE & MAGNITUDE IN POPULATIONS FOR TAKING HEALTH ACTION
7 : Definition 1. That branch of medical science which treats of epidemics (Parkin, 1873) 2. The science of the mass phenomena of infectious diseases (Frost, 1927) 3. The study of disease, any disease, as a mass phenomenon (Greenwood, 1934) 4. The study of the distribution and determinants of disease frequency in man (MacMahon, 1960)
8 : Epidemiology(epi=upon,demos=population) Epidemiology has been defined by John M. Last in 1988 as "The study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems".
9 : Aims of epidemiology. To describe the distribution and magnitude of health and disease problems in human populations. To identify etiological factors( risk factors) in the pathogenesis of diseases. To provide the data essential to the planning, implementation and evaluation of services for the prevention, control and treatment of disease and to the setting up of priorities among those services.
10 : Ultimate aim of Epidemiology To eliminate or reduce the health problems or its consequences. To promote the health and well being of society as a whole.
11 : Main Components of epidemiology Disease frequency: rates, ratios & proportions. Distribution of disease: with relation to time, place and person) Determinant of disease: agent, host and environment.
12 : Basic measurements in epidemiology Measurements of mortality. Measurements of morbidity. Measurements of disability. Measurements of natality. Measurements of the presence, absence or distribution of the characteristics or attributes of the disease. Measurements of the presence, absence or distribution of the environmental and other factors suspected of causing the disease. Measurements of the medical needs, health care facilities, utilization of health services and other factors suspected of causing the disease. Measurements of demographic variables.
13 : Basic requirements for measurement are Validity Reliability Accuracy Sensititvity Specificity Screening
14 : Tools of measurement Rates Ratios Proportions
15 : Tools of measurements Rate: A rate measures the occurrence of some particular event ( development of disease or the occurrence of death) in a population during given time period. Rate = no of deaths in one year * 1000 mid year population Consists : Numerator, denominator, time factor and multiplier e.g.. CBR, CDR.
16 : The various categories of rates are: 1) Crude rates: These are the actual observed rates such as the birth and death rates. Crude rates are also known as unstandardized rates. 2) Specific rates: These are the actual observed rates due to specific causes (e.g.. tuberculosis); or occurring in specific groups (e.g., age-sex groups) or during specific time periods (e.g., annual, monthly or weekly rates). 3) Standardized rates: These are obtained by direct or indirect method of standardization or adjustment, e.g.,age and sex standardized rates.
17 : Ratio: It expresses a relation between two random quantities. X:Y or X Y E.g.. Sex ratio, child-woman ratio, doctor- population ratio.
18 : Proportion: A proportion is a ratio which indicates the relation in magnitude of a part of the whole. The numerator is always included in denominator. The proportion is usually expressed in percentage.
19 : Measurements of mortality Crude death rates: “ the number of deaths ( from all causes) per 1000 estimated mid year population in one year, in a given place”. CDR = No. of deaths during the year * 1000 Mid year population. Limitation of CDR is exposed when we compare age-specific death rates b/w two populations. Major disadvantage of CDR is: They lack comparability for communities populations that differ by age, sex, race etc
20 : Specific death rate: SDR= Death due to specific cause * 1000 Mid-yr population Useful when planning to find out etiology May be a) cause or disease specific e.g. TB, Cancer etc. b) Related to specific groups- age specific, sex specific etc. Advantages: It helps us to identify particular groups or groups at risk for preventive action. They permit comparisions b/w different causes with in same population. Disadvantages: mainly used in developed countries where they have civil registration system.
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22 : Case fatality rate: = Total no. of deaths due to particular disease * 100 Total no. of cases due to the same disease It represents the killing power of a disease Ratio of death to cases Time interval is not specified Useful in acute infectious diseases e.g. cholera, measles It is closely related to virulence of organism.
23 : =“No of deaths due to a particular cause or in a specific age group per 100 or 1000 deaths”. a) Proportional mortality of a specific disease = no. of deaths from the specific disease in a year * 100 total deaths from all causes in that year b) Under 5 proportionate mortality rate = no of deaths under 5 yrs of age in a given year * 100 total no of deaths during the same period Proportional mortality rate (ratio)
24 : Proportional mortality rates are usually used for broad disease group and for specific disease of major public health importance e.g., cancer, CHD It is used when population data is not available Depends upon only two variables, which differ. So it cannot be used for comparison b/w population groups or different time periods.
25 : Survival rate: = Total no. of patients alive over a period *100 Total no. of patients diagnosed or treated It is the population of survivors in a group studied and followed over a period e.g. for 5 yr period Helps in describing prognosis in certain disease Can be used as a yard stick for the assessment of standards of therapy.
26 : Adjusted or standardized rates It’s major advantage is able to compare death rates of two populations with different age- composition. This is because rates are only comparable if the populations upon which they are based are comparable. It removes the confounding effect of different age structures and yields a single standardized or adjusted rate by which we can compare mortality directly
27 : Two methods of standarization Direct standarization Indirect standarization
28 : Direct standarization First a “ standard population” is selected (nos in each group are known) Secondly age specific rates are applied to standard population whose crude death rate is intended to be adjusted or standardized
29 : Indirect standarization Standardized Mortality Ratio (SMR) It is the simplest and most useful form of indirect standardization. Concept is that the regions with higher mortality also have the higher morbidity, and should therefore receive proportionately higher funding to combat illhealth. Standard mortality ratio is a ratio (usually expressed as a percentage) = observed deaths/ expected deaths * 100 Applications of SMR: SMR compares the mortality in a study group (e.g.. an occupational group) with the mortality that the occupational group would have had if they had experienced national mortality rates.
30 : If SMR is greater than 100, then the occupation would appear to carry a greater mortality risk than that of the whole population. If SMR is less than 100, then the occupation risks of mortality would seem to be proporiionately less than ihat for the whole population. The SMR is better than direct standarization because it permits adjustment for age and other factors.
31 : Measurements of morbidity Morbidity is defined as “ any departure, subjective or objective, from a state of physiological well-being”. Morbidity rates/ratios measured by 1) Frequency of disease: incidence and prevalence. 2) Duration of illness: days, months and years 3) Severity of illness: case fatality rates.
32 : Importance of morbidity data To know extent and nature of the disease load in community and help in forming priorities. Provide more comprehensive and accurate and clinically relevant information on patient characterisitcs- essential for basic research. Starting point of etiological studies and plays crucial role in disease population. Needed for monitoring and evaluation of disease control activities.
33 : Incidence “ No of new cases occuring in a defined population during a specified period of time”. = no of new cases of specific disease during a given time period * 1000 population at risk during that period It refers Only to new cases During a given period In a specified population or population at risk New spells or episodes of disease in a given population in the given duration Usually restricted to acute conditions
34 : Special incidence rates Attack rate (case rate), Secondary attack rate, Hospital admission rate, etc. a. Attack rate : An attack rate is an incidence rate (usually expressed as a per cent), used only when the population is exposed to risk for a limited period of time such as during an epidemic. It reflects the extent of the epidemic. Attack rate is given by the formula: Number of new cases of a specified disease during a specified time interval x 100 Total population at risk during the same interval
35 : Secondary attack rate SAR= No of exposed persons developing disease with in the range of the incubation * 100 total no exposed/ “susceptible” contact Primary case is excluded from both numerator and denominator. Limitation: Useful only for disease with short incubation period Not possible to identify susceptible cases
36 : Uses of incidence rate To control disease, and For research into aetiology and pathogenesis, distribution of diseases, and efficacy of preventive and therapeutic measures .
37 : Cumulative incidence Cumulative incidence is a simpler measure of the occurrence of a disease or health status. Unlike incidence, it measures the denominator only at the beginning of a study. The cumulative incidence can be calculated as follows: CI= Number of people who get a disease during a specified period X 1000 Number of people free of the disease in the population at risk at the beginning of the period
38 : In a statistical sense, the cumulative incidence is the probability that individuals in the population get the disease during the specified period. The period can be of any length but is usually several years, or even the whole lifetime. The cumulative incidence rate therefore is similar to the “risk of death” concept used in life-table calculations. The simplicity of cumulative incidence rates makes them useful when communicating health information to the general public.
39 : PREVALENCE The term "disease prevalence" refers specifically to all current cases (old and new) existing at a given point in time, or over a period of time in a given population. Prevalence is a ratio but expressed as a rate Two types Point prevalence Period prevalence
40 : Point prevalence: No of all current cases (old + new) at one point of time in a defined population = no of all current cases(old+new) of a specified disease existing at a given point in time Estimated population at the same point in time Period prevalence = no of existing cases (old+ new) of a specified disease during a given period of time interval * 100 estimated mid- interval population at risk
41 : Prevalence = Incidence x duration. (if population is stable and incidence and duration are unchanging) Incidence = P/D Duration= P/I Longer the duration: greater is the prevalence rate e.g. TB Acute disease: short duration and rapid recovery. So prevalence is less than incidence. Relationship between prevalence and incidence
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44 : Uses of prevalence Estimating magnitude of health/ disease problems in the community Identify potential risk populations Useful for adminstrative and planning purposes
45 : Epidemiological methods
46 : Study Designs Case report Case series Descriptive Epidemiology Descriptive RCT Before-After study Cross-sectional study Case-Crossover study Case-Control study Cohort study Analytic Ecologic study
47 : Study Design Sequence Case reports Case series Descriptive epidemiology Analytic epidemiology Clinical trials Animal study Lab study Cohort Case- control Cross- sectional Hypothesis formation Hypothesis testing
48 : Descriptive Studies Case-control Studies Cohort Studies Develop hypothesis Investigate it’s relationship to outcomes Define it’s meaning with exposures Clinical trials Test link experimentally Increasing Knowledge of Disease/Exposure
49 : Case Reports Detailed presentation of a single case or handful of cases Generally report a new or unique finding e.g. previous undescribed disease e.g. unexpected link between diseases e.g. unexpected new therapeutic effect e.g. adverse events
50 : Case Series Compilation of multiple case reports Assesses prevalent disease Cases may be identified from a single or multiple sources Generally report on new/unique condition May be only realistic design for rare disorders Cases are not compared to a control group Descriptive statistics Usually no statistical testing
51 : Case Series Advantages Time efficient, less resource intensive Uses available clinical data Recognizes new diseases Rapid hypothesis generation Basis for analytic study Can launch a case-control study
52 : Case Series Limitations Cases may not be representative No comparison group or underlying population represented Open to systematic errors
53 : Case Report Case Series Descriptive Epidemiology Study One case of unusual injury finding Multiple cases of injury finding Population-based cases with denominator
54 : Descriptive epidemiology. First phase in epidemiological studies. Describes distribution of disease with relation to time, place and person. Unit of study is population. Helps in formulation of hypotheses. E.g.. EBV with Burkitt’s lymphoma, Kuru a slow virus disease.
55 : Procedures in descriptive studies. Defining the population to be studied. Defining the disease under study. Describing the disease by time, place and person. Measurement of disease. Comparing with known indices. Formulation of hypothesis.
56 : 1. Defining the population: Population is defined in terms of number and composition (age, sex, occupation etc). Defined population may be Whole population or Representative sample (selected age, sex groups etc) Must be large enough Must be stable(i.e. with out migration) Community participation Should not be different from other communities in the region Health facility close to provide easy access to patients e.g., Frimingham Heart study in US
57 : 2. Defining the disease under study. Definition epidemiologist clinician Precise and Valid May not be precise Operational definition: a definition by which the disease or condition can be identified and measured in the defined population with a degree of accuracy Once definition is established it must be used throughout the study
58 : Time Distribution Short term fluctuations (hrs, days, weeks) Periodic fluctuations Long term or Secular trends 3. Describing disease by time, place and person
59 : a) Short-term fluctuations The best known short-term fluctuation is an epidemic. Epidemic is defined as "the occurrence in a community or region of cases of an illness or other health-related events clearly in excess of normal expectancy”. Types of epidemics: 3 major types Common-source epidemics Single exposure or point source epidemics Continous or multiple exposure epidemics Propagated epidemics Person to person Arthropod vector Animal reservior Slow (modern epidemics)
60 : Common source epidemics A. common source, single exposure epidemics - also known as “point source” epidemics - exposure to the agent is brief and simultaneous - cases develop with in one incubation period Features : Rises and fall rapidly No secondary waves Explosive All cases in one incubation points It usually occurs due to environmental contamination like air, water, food, soil by chemicals or pollutants e.g., Bhopal gas tragedy in India, Minamata disease in Japan
61 : B) common source, continous or repeated exposures Exposure from same source is prolonged- continous, repeated or intermittent. e.g. Gonnorhea out break vaccine (poliomyelitis) Variation: common source epidemic and then continue as a propogated epidemic e.g. water borne cholera
62 : B) Propogated epidemics Mostly infectious in origin Results from person to person transmission, Curve usually shows a gradual rise and tails off over a longer period of time Spread depends upon herd immunity, contact and secondary attack rate Transmission continues until susceptible are depleted or susceptible individuals are no longer exposed to infected persons or vectors.
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64 : B) Periodic fluctuations (months and years) 1) Seasonal: Rainy- malaria, filariasis. Winter- RS infections. Summer- Diarrhea. NCD – sumstroke , Hay fever, Snakebite 2) Cyclical trend: diseases occur in cycles, for a short periods(days,wks, months or yrs). e.g.. measles every 2-3 yrs, mumps every 5-7 yrs, influenza 7-10yrs This occurs due to naturally occuring variations in Herd Immunity Non infectious – accidents at wk ends
65 : c. Secular trends or long term trends Changes occur over long period of time (usually > 10yrs). It could be increasing or decreasing, real or apparent, communicable diseases or non-communicable disease. e.g.. 1) Real downward trend: Plague and cholera. 2) Real upward trend: DM, CHD.
66 : Importance of time trends Can know diseases which are increasing or decreasing Can frame effective measures to control diseases Formulate etiological hypothesis Provide guidelines to health administrator in matters of prevention or control of disease
67 : To study the geographical variations of disease Factors influencing geographical variations are culture, standards of living, external environment and genetic factors. 1) International: a) Malaria, Leprosy in hot and humid climate. E.g.. Africa and South America. b) Bancroftian Filariasis in Africa and South America. c) Malayan Filariasis in SEAR. 2) National: 1) Trachoma in hot and dry. E.g.. Punjab, and Rajasthan. 2) Leprosy: Hot and humid. E.g.. TN, Orissa, W. Bengal. 3) Endemic Goiter: Sub- Himalayan belt. 4) Polio myelitis: UP and Bihar. Place distributions/ Geographical comparisons
68 : 3) Local: Studied with the help of spot maps in a given area. E.g.. a) John Snow study on cholera in London. b) Endemic flurosis in Nalgonda, Kolar. 4) Urban- Rural: e.g.. - Tetanus, OP poisoning common in rural area. - Road traffic accidents, drug abuse in urban areas. Descriptive epidemiology allows to find out these variations and helps to frame guidelines for prevention and control of diseases
69 : Migration studies Migration studies provides a unique opportunity to evaluate the role of the possible genetic and environmental factors in the occurrence of disease in a population. E.g. A and B are two regions In order to know the influence of environmental factors on disease . Ideally, samples of population in area 'A' should be sent to area "B", and vice versa to study change in incidence of disease. As this is not practically possible so migration studies becomes important to study the changes in disease pattern.
70 : Migration studies are done in two ways: Comparision of disease and death rates for migrants with their population Comparision of migrants with local population of host country e.g. coronary heart disease was more in japanese staying in US
71 : PERSON 1) Age. 2) Sex. 3) Occupation. 4) Marriage. 5) Residence. 6) Socio-Cultural environment. 7) Socio-Economic background. 8) Stress 9) Migration
72 : 4) Measurement of disease: in terms of mortality morbidity and disability. Incidence and prevalence etc. 5) Comparing with known indices- comparision b/w different populations and subgroups of same population
73 : 6) Formulation of a hypothesis. Hypothesis must be specific for the following The population Specific cause considered Expected outcome- the disease Dose – response relationship Time- response relationship e.g., smoking of 30-40 cigars per day causes Lung cancer in 10% of smokers after 20yrs of exposure
74 : Uses of descriptive epidemiology Provide data regarding the magnitude of the disease load and types of disease problems in the community in terms of morbidity and mortality rates and ratios. Provide clues to disease etiology, and help in the formulation of an etiological hypothesis. Provide background data for planning, organizing and evaluating preventive and curative services. They contribute to research by describing variations in disease occurrence by time, place and person.
75 : ANALYTICAL EPIDEMIOLOGY The word ‘analysis’ means detailed examination of or study of. It is the second major type of epidemiological study. It is concerned with study of individual within population. Object is not to formulate just to test the hypothesis. It comprises the following studies: Ecological studies Cross sectional study Case control study Cohort study
76 : Ecological study Ecological (or correlational) studies are useful for generating hypotheses. unit of analysis - groups of people. E.g., a relationship was found between average sales of an anti-asthma drug and the occurrence of an unusually high number of asthma deaths in different provinces of New Zealand. Such an observation would need to be tested by controlling for all the potential confounders to exclude the possibility that other characteristics – such as disease severity in the different populations – did not account for the relationship.
77 : Ecological studies done by two ways Time series- one population at different time Time period- many papulation at a single point of time Time series may reduce some of the socioeconomic confounding that is a potential problem in ecological studies. If the time period in a time series is very short, as it is in daily time series studies, confounding is virtually zero as the people in the study serve as their own controls.
78 : Time series study
79 : Advantages and Disadvantages Simple to conduct and attractive, but difficult to interpret. Ecological studies usually rely on data collected for other purposes; data on different exposures and on socioeconomic factors may not be available. Since the unit of analysis is a group, the link between exposure and effect at the individual level can not be made. Ecological studies is that data can be used from populations with widely differing characteristics or extracted from different data sources.
80 : Ecological fallacy An ecological fallacy or bias results if inappropriate conclusions are drawn on the basis of ecological data. The bias occurs because the association observed between variables at the group level does not necessarily represent the association that exists at the individual level. E.g., Clearly many factors other than the presence of a skilled birth attendant impact on the outcome of a delivery.
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82 : Cross sectional study(prevalence study) Cross-sectional studies Cross-sectional studies measure the prevalence of disease and thus are often called prevalence studies. In a cross-sectional study the measurements of exposure and effect are made at the same time.
83 : Cross-sectional studies are relatively easy and inexpensive to conduct Useful for investigating exposures that are fixed characteristics of individuals(chronic disease). In sudden outbreaks of disease, a cross-sectional study to measure several exposures can be the most convenient first step in investigating the cause.
84 : Data from cross-sectional studies are helpful in assessing the health care needs of populations. Data from repeated cross-sectional surveys using independent random samples with standardized definitions and survey methods provide useful indications of trends
85 : WHO Global InfoBase: an online tool The WHO Global InfoBase (http://infobase.who.int) is a data warehouse that collects, stores and displays information on chronic diseases and their risk factors (overweight/ obesity, blood pressure, cholesterol, alcohol, tobacco use, fruit/vegetable intake, physical inactivity, diabetes) for 186 countries. The InfoBase was initiated in 2002 to improve the access of health professionals and researchers to country-reported chronic disease risk factor data. It has the advantage of providing traceable sources and full survey methodology. The following options are available online: • compare countries using WHO estimates for certain risk factors • make country profiles showing the most recent most nationally-representative data • use a survey search tool for all country data on particular risk factors
86 : CASE CONTROL STUDY A case control study is an enquiry in which group of individuals are selected in terms of whether they do (cases) or do not (controls) have the diseases of which etiology is to be studied and groups are then compared with respect to existing or past characteristics judged to be of possible relevance to the etiology of disease. More accurately called case-comparison group. Its distinct characteristics are: a. Both exposure and out come (disease) have occurred before start of study. b. Study proceeds back wards from effect to cause. c. It uses control or comparison group to support or refute an inference. Ex: Between congenital malformation and rubella during pregnancy. Viral infection & Bell’s palsy X ray & blood cancer
87 : Cause to Effect
88 : Cases vs controls
89 : Objectives of Case Control Study: Estimation of risk of exposure to various factors associated with diverse phenomena. To identify the modifiable causal factors. c. Evolving risk intervention strategies for prevention and control of public health problems.
90 : Basic steps in case control study A. Selection of cases and controls B .Matching C. Measurement of exposure D. Analysis and Interpretation
91 : Selection of cases and controls Selection of cases:- a. Definition of case: -Diagnostic criteria: -Eligibility criteria: Sources of cases: It includes: 1. All the persons with disease seen at particular medical care facility or group of facilities in a specified period of time. 2.All the persons with disease found in a more general population, such as that of city or country population at a point or in a period of time.
92 : SELECTION OF CONTROLS: Controls must be free from disease under study. They must be as similar as to the cases, except for the absence of the disease under study. SOURCES OF CONTROLS: a. Hospital controls b. Relatives c. Neighbourhood controls d. General population
93 : Matching: Definition: It is defined as process by which we select controls in such a way that they are similar to cases with regard to certain pertinent selected variables which are known to influence the outcome of disease and which, if not adequately matched for comparability, could distort or confound result the results. Eg: Age in study of breast cancer Role of alcohol as etiology of colon cancer TYPES: a. Group matching b. Pair matching
94 : Measurement of exposure This may be obtained by interview, by questionnaires or by studying past records of cases such as hospital record or employment record. Bias or systematic error should be ruled out.
95 : Analysis Is final step to find out A. Exposure rates among cases and controls to suspected factor. B. Estimation of disease risk associated with exposure(odds ratio). Exposure Rates:
96 : Exposure rates: Cases=a/(a+c)=33/35=94.2 percent Controls=b/(b+d)=55/82=67percent p<0.001 Odds ratio: It is a measure of strength of the association between risk factor and out come. Disease Yes No Exposed a b Non exposed c d Odds ratio= ad/bc =33x27/55x2=8.1
97 : Estimation of relative risk : Estimation of disease risk associated with exposure is obtained by an index known as ‘Relative Risk’ which is defined as Relative Risk= incidence among exposed incidence among non exposed =a/(a+b) c/(c+d)
98 : Examples of case- control study Adenocarcinoma of vagina Oral contraceptives and thromboembolic disease Thalidomide tragedy
99 : Advantages Relatively easy to carry out Rapid and inexpensive (compared with cohort studies) Require comparatively few subjects Particularly suitable to investigate rare diseases or diseases about which little is known. But a disease which is rare in the general population(e.g. leukemia in adolescents) may not be rare in special exposure group (e.g. prenatal x rays) No risk to subjects Allows the study of several different etiological factors (e.g. : smoking, physical activity and personality characteristics in myocardial infarction) Risk factors can be identified . Rational prevention and control programmes can be established No attrition problems, because case control studies do not require follow up of individuals into the future Ethical problems minimal
100 : Disadvantages Problems of bias. e.g., Relies on memory or past records, the accuracy of which may be uncertain; validation of information obtained is difficult or sometimes impossible Selection of an appropriate control group may be difficult We cannot measure incidence, and can only estimate the relative risk. Do not distinguish between causes and associated factors Not suited to the evaluation of therapy or prophylaxis of disease. Another major concern is the representativeness of cases and controls.
101 : COHORT STUDY(Incidence study) It is also called longitudinal or incidence or forward looking study. A Cohort is defined as group of people who share a common characteristic or experience within a defined time period . Distinguishing factors : a. Cohort are identified prior to appearance of disease under investigation. b. Study groups, so defined are observed over a period of time to determine frequency of disease. c. Study proceeds forward from cause to effect.
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103 : OBJECTIVES OF COHORT STUDY Estimating directly risk of exposure to various factors associated with disease phenomena. Exploring natural history of disease in entirety and identifying additional pathological events to complete natural history. Identifying appropriate outcome events in natural history of disease for appropriate intervention for limitations. Identify modifiable risk factors.
104 : TYPES OF COHORT STUDY PROSPECTIVE STUDY RETROSPECTIVE STUDY COMBINATION OF PROSPECTIVE STUDY RETROSPECTIVE STUDY
105 : Prospective or current study It is one in which outcome has not yet occurred at the time of investigation begins. Ex: Does exposure to x(smoking) correlates with outcome y(lung cancer)
106 : Retrospective or historical study It is one in which outcome have all occurred before the start of investigation. Investigation goes back in time , sometimes 10 to 30yr to select his study groups from existing records of past employed medical or other records and traces them forward through time from past date fixed on records.
107 : Combination of prospective and retrospective study/Nested cohort study Cohort is defined from past records and is assessed of date for outcome. Same cohort is followed up prospectively into future for further assessment of outcome.
108 : Nested case-control study of gastric cancer To determine if infection with Helicobacter pylori was associated with gastric cancer, investigators used a cohort of 128 992 people that had been established in the mid-1960s. By 1991, 186 people in the original cohort had developed gastric cancer. The investigators then did a nested case-control study by selecting the 186 people with gastric cancer as cases and another 186 cancer-free individuals from the same cohort as controls. H. pylori infection status was determined retrospectively from serum samples that had been stored since the 1960s. 84% of people with gastric cancer –and only 61% of the controls – had been infected previously with H. pylori, suggesting a positive association between H. pylori infection and gastric cancer risk.18
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110 : Elements of cohort study I.Selection of study subjects: a. General population b. Special group c. Exposed groups
111 : Obtaining data on exposure a. Cohort Members : Through interviews b. Review of records: certain kind of information can be obtained only from records ex; x-ray dose, type of surgery etc c. Medical examination or special tests. d. Environment surveys.
112 : Selection of comparison groups a. Internal comparison: within group. b. External comparison: with other group c. Comparison with general population.
113 : Follow up A. Periodic medical examination of each member B. Reviewing physician and hospital records C. Routine surveillance of death records D. Mailed questionnaires, telephone calls, home visits etc
114 : Analysis Data analyzed in terms of a. Incidence rates of outcome among exposed and non exposed. b. Estimation of risk A. INCIDENCE RATE: ex:
115 : Incidence Rates Among smokers=70/7000= 10per 1000 Among non smokers=3/3000=1per 1000 B. Estimation of risk: a. RELATIVE RISK : RR= Incidence Of disease(or death) among exposed Incidence of disease( or death) among non exposed ex: RR of lung cancer=10/1=10. implies smokers are 10 times greater risk of lung cancer than non smokers.
116 : Attributable risk: AR=Incidence of disease rate among exposed – incidence of disease rate among non exposed __________________________________ Incidence rate among exposed =10-1 X100=90percent 10_____________ Implies 90percent of lung cancer in smokers is due to smoking.
117 : PAR It is the incidence of the disease (or death) in the total population minus the incidence of disease (or death) among those who were not exposed to the suspected causal factor . It simply provides an estimate of the amount by which the disease could be reduced in that population if the suspected factor was eliminated or modified.
118 : Population attributable risk In our example one might expect that 86 per cent of deaths from lung cancer could be avoided if the risk factor of ciqarettes were eliminated.
119 : Examples of cohort study Smoking and lung cancer The framingham heart study Oral contraceptives and health
120 : Advantages Incidence can be calculated Several possible outcomes related to exposure can be studied simultaneously. Cohort studies provide a direct estimate of relative risk Dose response ratios can also be calculated Since comparison groups are formed before disease develops, certain forms of bias can be minimized like misclassification of individuals into exposed and unexposed groups
121 : Disadvantages Involve a larger number of people. Unsuitable for investigating uncommon diseases or diseases with low incidence in the population. Takes long time to complete the study. Administrative problems like loss of funding , experienced staff , extensive record keeping are inevitable. Attrition of cohort group-due to migration , dropout , loss of interest and death. Difficulties in selection of comparison groups. Changes in standard methods and diagnostic criteria during study. Expensive Study can alter behavior of cohort study group. E.g.: smoking and exercise Ethical problems. Studies only limited factors in the disease causation neglecting others.
122 : Difference between case control and cohort study
123 : Bias
124 : 124 Definition of bias Any systematic error in an epidemiological study that results in an incorrect estimate of the association between exposure and disease Systematic variation of measurements from the true value (Last J.)
125 : 125 Types of bias Selection bias Information bias Confounding
126 : Selection Bias Systematic error resulting from participant selection procedures or factors influencing participation Occurs in all types of study, i.e. observational and experimental Cannot be corrected analytically, i.e. must be prevented
127 : 127 Selection bias Sampling bias Ascertainment bias Surveillance Referral, admission Diagnostic Participation bias Self-selection (volunteerism) Non-response, refusal Healthy worker effect, survival
128 : 128 Minimising selection bias Clear definition of study population Explicit case and control definitions Cases and controls from same population
129 : 129 Information bias Systematic error in the measurement of information on exposure or outcome Differences in accuracy of exposure data between cases and controls of outcome data between different exposure groups Study subjects are classified in the wrong category
130 : Types of Information Bias Interviewer bias Recall bias Reporting bias Publication bias Follow up bias
131 : 131 Mothers of children with malformations will remember past exposures better than mothers with healthy children Recall bias Cases remember exposure differently than controls
132 : 132 Investigator may probe listeriosis cases about consumption of soft cheese Interviewer bias Investigator asks cases and controls differently about exposure
133 : 133 Biased follow-up Unexposed are less likely diagnosed for disease than exposed Example Cohort study to investigate risk factors for mesothelioma Difficult histological diagnosis Histologist more likely to diagnose specimen as mesothelioma if asbestos exposure known
134 : Berkisonian bias A special example of bias is Berkesonian bias, termed after Dr. Joseph Berkson who recognized this problem. The bias arises because of the different rates of admission to hospitals for people with different diseases (i.e.,hospital cases and controls)
135 : 135 Bias in prospective cohort studies Loss to follow up The major source of bias in cohort studies Assume that all do / do not develop outcome? Ascertainment and interviewer bias Some concern: Knowing exposure may influence how outcome determined Non-response, refusals Little concern: Bias arises only if related to both exposure and outcome Recall bias No problem: Exposure determined at time of enrolment
136 : 136 Bias in retrospective cohort & case-control studies Ascertainment bias, participation bias, interviewer bias Exposure and disease have already occurred ? differential selection / interviewing of compared groups possible Recall bias Cases (or ill) may remember exposures differently than controls (or healthy)
137 : Confounding Bias due to confounding factors. confounding factors: associated with both exposure and out come Differs from selection and information bias because it can be evaluated and controlled to some extent in the analysis phase of the study. It can be removed by matching cases and controls.
138 : Bias can be reduced by Single blinding Double blinding Triple blinding Ideal one is triple blinding but most commonly used is double blinding
139 :
140 :
141 : EXPERIMENTAL EPIDEMIOLOGY
142 : DEFINITION It is the study involving some action,intervention or manipulation & observing & comparing the outcome of experiment in both groups. Aims & objectives 1.To provide scientific proof of aetiological factors which may permit the modification or control of those diseases. 2.To provide a method of measuring the effectiveness of health services for prevention, control and treatment of diseases.
143 : Experimental Studies can be done in : 1) Animals 2) Human Beings
144 : ANIMAL STUDIES They play a important role in men's quest for knowledge about himself & his environment. USES: Experimental reproduction of human disease. Testing the efficacy of drugs and vaccines Completing the natural history of disease
145 : ADVANTAGES: Animals can be bred in labs. Animals can be manipulated easily by examiner The animals multiply rapidly & help to carry out his experiments Cost effective DISADVANTAGES: All human diseases cant be produced in animals. Findings of experiment cant be applicable to human beings.
146 : USES: To study occurrence of diseases in human & effectiveness of one method over other method. ADVANTAGES Gives precise knowledge of disease in humans. Gives correct idea of preventive & therapeutic measures. DISADVANTAGES Ethical and logistic problems. Unnecessary exposure of humans to the hazards of causative agents HUMAN EXPERIMENTS:
147 : Experimental studies
148 : Randomized control trial It is an epidemiologic experiment made to use scientific technique to evaluate methods of prevention & treatment.
149 : Flow chart of RCT
150 : Steps of RCT Drawing a protocol Selecting the reference and study group Randomization Manipulation and intervention Follow up Assessment
151 : STEPS IN RCT: 1.Drawing up a protocol: They are written guidelines, helps to minimize bias and errors in study. It includes question to be answered, criteria for selection of study, size of sample, procedure for allocation of subjects, treatment to be applied etc. Pilot studies or preliminary test runs.
152 : 2.Selecting reference & study population: Reference population is population to which the findings of the trail if found successful are expected to be applicable. Study population is the actual population that participates in study. 3.Randomization: It is the heart of RCT. It is a statistical procedure by which the participants are allocated into groups called study and control groups. It attempts to eliminate bias and allow for comparability by matching. 4. Manipulation: Done by deliberate application or withdrawal or reduction of suspected casual factor.
153 : 5.Follow up: It is examination of experimental & control group subjects at defined intervals of time. 6.Assessment: It is the final step of the outcome of trial in terms of positive & negative results. Bias may arise due to subject variation, observer bias and blinding. Blinding is done to get valid result & to prevent bias. It has 3 types. 1.single blind trial 2.double blind trial 3.triple blind trial.
154 : 1.Concurrent parallel study design 2.Cross over type of study design. Some study designs:
155 : Concurrent and Cross over study
156 : TYPES OF RCT: 1.Clinical trials: It is concerned with evaluating therapeutic agents mainly drugs. The main disadvantage is it takes long time for the process. Eg-- Hypertension detection & follow up program on 10500 subjects assigned randomly into 2 groups. 1.Stepped care: Anti-HTN therapy. 2.Refferred care: Subjects are referred to primary care, physician treated as usual. Stepped care Referred care Mortality 9:100 9.7:100 Final BP 84 89
157 : Round shaped- Aspirin Elongated capsules- Beta- carotene or Placebo
158 : 2.Preventive trial or Field trials: They are the trials of primary preventive measures done to prevent or eliminate disease on experimental basis. Eg.Trials of vaccines & chemo-prophylactic agents. It should be in clear statement about benefit to the community, risk involved, cost to the health services in terms of money, men & material.
159 : Example for vaccine trial
160 : 3.Risk factor trials: A type of preventive trial of risk factors in which the investigator intervenes to interrupt the usual sequence in the development of disease for those who are having risk factors for developing the disease. eg.Major risk factors for CHD are elevated blood cholestrol,smoking & hypertension. 4.Cessation experiments: In this type of study an attempt is made to evaluate the termination of a habit which is considered to be casually related to disease. eg.cigratte smoking & lung cancer one group smokes & other group give up smoking ,demonstration of decrease in incidence of cancer.
161 : 5.Trial of aetiological agents 6.Evaluation of health services
162 : Examples- 1.Uncontrolled trials: These are trials with no comparison(controls) eg.pap test, there is epidemiological evidence from these trials that pap test for Ca cervix is effective in reducing mortality. 2.Before & after comparison studies: i.Without control.eg.James Lind studies in preventing scurvy ii.With control.Eg.Seat Belt Legislation inVictoria, Australia. Non Randomized control trial
163 : 3) Natural experiments: studies are done on natural groups e.g., migrants religious or social groups atomic bombing of Japan etc John snow discovery of cholera is a water-borne disease is a natural infection.
164 : Association and causation When the disease is multifactorial (e.g., coronary heart disease) numerous factors or variables become implicated in the web of causation, and the notion of "cause“ becomes confused. The more associations. the more investigations to disentangle the web of causation. The epidemiologist whose primary interest is to establish a "cause and effect" relationship has to sift the husk from the grain. He proceeds from demonstration of statistical association to demonstration that the association is causal.
165 : Exposure OR Genetic Background OR Combination of Both Disease or Other Outcome ? Causation ? Association Suppose we determine that an exposure is associated with disease. How do we know if the observed association reflects a causal relationship?
166 : First step in determining causation: Understanding disease etiology Experimental studies In vitro systems Animal studies in controlled environments Allows for control of precise dose control of environmental conditions loss to follow up kept to a minimum Problems with extrapolating data to human populations human diseases with no good animal models Clinical pathologies
167 : Second step in determining causation: Conducting Studies in Human Populations Here’s where Epidemiology is important…. Epidemiology capitalizes on “natural” or “unplanned” experiments. We take advantage of groups who have been exposed for non-study purposes. All of the study designs are important here and provide different evidence for or against a causal hypothesis.
168 : Two step process to carry out studies and evaluate evidence 1. Determine if an association is present Ecologic studies: studies of group characteristics Cross-sectional studies: studies at one particular time Case-control or cohort studies: studies of individual characteristics. 2. If an association is demonstrated, determine whether the observed association is likely to be a causal one using pre-determined criteria.
169 : Surgeon Alton Ochsner observed that almost all lung cancer patients were smokers Ecologic study of per capita smoking and lung cancer incidence Case-control study of lung cancer patients versus those without lung cancer
170 : Understanding Causality Types of Association causal noncausal Types of Causal relationships direct indirect Types of causal factors sufficient necessary
171 : 3 categories of association Spurious association Indirect association Direct association or causal association One to one causal association Multifactorial association
172 : Two Types of Association: Real and Spurious A real association is present if the probability of occurrence of an event or the quantity of a variable depends upon the occurrence of one or more other events, characteristics or variables. Spurious associations refer to non-causal associations due to chance, bias, failure to control for extraneous variables (confounding), etc.
173 : Interpreting Associations - Causal and Non-Causal Causal Non-Causal (due to confounding) Characteristic Under Study Characteristic Under Study Disease Factor X Disease
174 : The relationship between coffee consumption and pancreatic cancer In 1981, MacMahon et al. reported results from a case-control study of cancer of the pancreas. There was an apparent dose response relationship between coffee consumption and cancer of the pancreas, particularly in women. Was the disease caused by coffee consumption or by some factor closely related to coffee consumption?
175 : The relationship between coffee consumption and pancreatic cancer Smoking is closely associated with both pancreatic cancer and coffee consumption. There were many issues with control selection and measurement of exposure levels in cases and controls. Subsequent studies were unable to reproduce the result.
176 : Interpreting Associations - Causal and Non-Causal Causal Non-Causal (due to confounding) Coffee Consumption Coffee Consumption Pancreatic Cancer Smoking Pancreatic Cancer Spurious Association Real Association Real Association
177 : Why is it important to distinguish between causal and non-causal associations? Causal relationships are used to make public health decisions and design interventions. In our example, if smoking was indeed causal, it would be irresponsible to target coffee drinking as an intervention. Very important to consider all confounders.
178 : Types of Causal Relationships: Direct vs Indirect Factor Factor 1 Disease Factor 2 Factor 3 Factor 4 Disease Direct Indirect
179 : Types of Causal Relationships: Direct vs Indirect ?F508 Polymorphism High cholesterol Cystic Fibrosis Artery thickening Hemostatic factors Myocardial infarction Direct Indirect
180 : Four types of causal factors Necessary and sufficient Without factor, disease does not develop Example: HIV Necessary but not sufficient Multiple factors, including main factor, required Example: Development of tuberculosis requires M. tuberculosis and other factors, such as immunosuppression, to cause disease Bacteria still necessary, but not sufficient to cause the disease
181 : Four types of causal factors Sufficient but not necessary Factor can produce disease, but not necessary Example: Both radiation exposure and exposure to benzene are sufficient to cause leukemia, but neither are necessary if the other present. Neither sufficient nor necessary Complex models of disease etiology Example: High fat diet and heart disease, hypertension, diabetes, certain kinds of cancer
182 : Nine guidelines for judging whether an association is causal Temporal relationship Strength of association Dose response relationship Replication of the findings Biologic plausibility Consideration of alternate explanations Cessation of exposure Specificity of the association Consistency with other knowledge
183 : Temporal Relationship Exposure to the factor must have occurred before the disease developed. Easiest to establish in a cohort study Length of interval between exposure and disease very important If the disease develops in a period of time too soon after exposure, the causal relationship is called into question.
184 : Asbestos Latent period of 10 - 20 yrs Lung Cancer Asbestos Latent period of 3 yrs Lung Cancer In this case, the latent period is not long enough for lung cancer to develop if caused by exposure. Well - established temporal relationship Asbetos and Lung Cancer New Study
185 : Strength of Association The larger the relative risk or odds ratio, the higher the likelihood that the relationship is causal. However, care must be taken to examine confidence intervals and sample size. For example, if the confidence interval is wide (e.g., 1.8 - 22.6), an OR of 12.0 is less strong because we are less confident of the strength of the odds ratio.
186 : Dose-Response Relationship With increasing dose, there is increasing risk of disease. This is not considered necessary for a causal relationship, but does provide additional evidence that a causal relationship exists.
187 : Replication of the Findings If there is a true causal relationship between exposure and disease, the expectation is that we would see the association consistently in other (NOT necessarily all) subgroups of the population.
188 : Biologic plausibility Consistency of epidemiologic plausibility with existing biologic knowledge. Requires knowledge of the biologic etiology of disease
189 : Consideration of alternate explanations Consider the example of coffee consumption, smoking and pancreatic cancer. Did the investigators consider the associations between smoking, coffee consumption and pancreatic cancer? If the investigators did not consider possible confounders and effect modifiers, the association is less likely to be causal. Requires a knowledge of the literature and known risk factors for the disease
190 : Cessation of exposure Upon elimination or reduction of exposure to the factor, the risk of disease declines. HOWEVER, in certain cases, the damage may be irreversible. Example: Emphysema is not reversed with the cessation of smoking, but its progression is reduced.
191 : Specificity of the Association The weakest of the criteria (should probably be eliminated) Specific exposure is associated with only one disease. This is used by tobacco companies to argue that smoking is not causal in lung cancer. Smoking is associated with many diseases. If anything, may provide support for a causal relationship, but does not negate if not present.
192 : Consistency with other knowledge If a relationship is causal, the findings should be consistent with other data. If lung cancer incidence increased as cigarette use was on the decline, we would have to be able to explain how this was consistent with a causal relationship (How?!?)
193 : Associations are observed Causation is inferred It is important to remember that these criteria provide evidence for causal relationships. All of the evidence must be considered and the criteria weighed against each other to infer the causal relationship.
194 : Morris’ seven uses of epidemiology Trend study Community diagnosis Health services evaluation To know the individual risks and chances Syndrome identification Completing the clinical picture Searching for causes / risk factors for establishing causal relationship
195 : TREND STUDY STUDYING THE PAST HISTORY FOR RISE AND FALL STUDYING ITS CHANGING BEHAVIOUR MAKING FUTURE PREDICTIONS GIVING EARLY WARNINGS OR FEED -BACK
196 : SOCIAL ANATOMY SOCIAL PATHOLOGY SOCIAL PHYSIOLOGY QUANTIFICATION QUALITATIVE ESTIMATION COMMUNITY DIAGNOSIS
197 : COMMUNITY DIAGNOSIS Social anatomy: race, age and sex composition, socio economic status, population at risk, resources avalaible. Social physiology: positive &negative lifestyles, occupation, health services awareness and uilization, nutritional polices, labour. Social pathology: morbidity, mortality, disability, alcholism, smoking, crime & voilence, risk prone behaviour.
198 : COMMUNITY DIAGNOSIS MUST BE DYANAMIC IN A WORLD OF CHANGE, EPIDEMIOLOGIST HAVE A SPECIAL DUTY TO OBSERVE THE IMPACT “UPON THE PEOPLE” AND THE WAY WE LIVE TO DIAGNOSE WHERE WELL -BEING IS INCREASING AND WHERE LOSING OUT, TO PROBE FOR UNINTENDED CONSEQUENCES , TO IDENTIFY TRENDS AND TO THINK AHEAD.
199 : ONION PRINCIPLE JUST LIKE THE LAYERS OF THE ONION, THE OLD DISEASES WANE AND GIVE PLACE TO NEWONES. INFECTIOUS ONES WILL BE REPLACED BY NON– INFECTIOUS ONES TO BE REPLACED LATERBY PERSONAL AND BEHAVIORAL PROBLEMS. ONE MUST BE AWARE OF THIS PHENOMENON BEFORE DIAGNOSING THE COMMUNITY HEALTH OLD DISEASES
200 : HEALTH SERVICES EVALUATION HEALTH PLANNING FOR APPROPRIATE COST EFFECTIVE COMMUNITY NEED BASED JUDICIAL MIX OF PREVENTIVE, PROMOTIVE, CURATIVE, REHABILITATIVE AND PUBLIC HEALTH SERVICES
201 : SYNDROME IDENTIFICATION LUMPERS & SPLITTERS GROUPING AND DIVIDING THE SYMPTOM- COMPLEXES AND NAMING THEM AS SYNDROMES IS THE STARTING POINT FOR THE STUDY OF NATURAL HISTORY OF ANY DISEASE
202 : SEARCH FOR CAUSES SEVERAL CAUSES? SINGLE DISEASE SINGLE CAUSE ? SEVERAL DISEASES SEARCH FOR CAUSE IN INTERRELATED DISEASES MAY YIELD CLUES FOR NEW CAUSES / RISK FACTORS
203 : COMPLETING THE CLINICAL PICTURE OF DISEASE IN BREADTH HOSPITAL STUDIES HAS TO BE BROADEND WITH SIMULTANEOUS COMMUNITY STUDIES AS THEY POORLY REPRESENT THE HELTH EVENT IN GENERAL POPULATION. MERE DEPENDENCE ON STUDIES CONDUCTED IN HOSPITAL OR ANY HEALTH FACILITY SETTING IS BIASED BECAUSE THEY DO NOT INCLUDE THE PREPATHOGENIC AND FOLLOW-UP PHAGES OF THE DISEASE STUDIED. IN DEPTH GOING TO THE BOTTOM, THE DEEEPER PART OF THE ICEBERGH TO STUDY THE EARLIER PART OF DISEASE, WHICH IS EITHER STOPPABLE OR ATLEAST PREVBENTABLE BY SEARCHING FOR PRECURSORS OF THE DISEASE DISPOITIONS DUE TO DISEASE ASYMPTOMATIC DISEASE SUBCLINICAL CASES LATENT CASES CARRIER STATE
204 : NATURAL HISTORY OF DISEASE
205 : RISK ASSESMENT INDIVIDUAL RISK GENERAL POPUTLATION RISK PROGNOSIS FOR BY PHYSICIAN
206 : SURVILLANCE, EPIDEMIOLOGICAL INVESTIGATIONS COUNT CASES & MEASURE THE POPULATION AFFECTED DETECTS, INVESTIGATES & ANALYZES PROBLEMS DISSEMINATION TO HELATH PLANNERS & PUBLIC EVALUATION HEALTH POLICY HEALTH PROGRAMS RESULTING INFORMATION APPLIED FOR PREVENTION & CONTROL LANGMUIR ON EPIDEMIOLOGICAL PRACTICE
207 : SCOPE AND JURISDICTION STRICTLY SPEAKING, THERE IS NO LIFE SCIENCE, WHERE EPIDEMIOLOGICAL APPROACH AND PRINCIPLES CANNOT BE APPLIED FROM WOMB TO TOMB EPIDEMIOLOGY IS APPLICABLE PREVENTIVE PAEDIATRICS PREVENTIVE GERIATRICS PREVENTIVE CARDIOLOGY CLINICAL EPIDEMIOLOGY
208 : Recent applications of epidemiology Study of communicable diseases. E.g. TB, leprosy. Study of NCDs. E.g. Cancer, IHD. Health related states. E.g. Accidents. Public health. E.g. Utilization rates, vaccination coverage, health needs and demands. Psychological epidemiology social epidemiology Molecular and genetic epidemiology Nutritional epidemiology
209 : Epidemiology of Infectious Diseases
210 : Infectious Disease Epidemiology: Major Differences A case can also be an exposure Subclinical infections influence epidemiology Contact patterns play major role Immunity There is sometimes a need for urgency
211 : What is infectious disease epidemiology? Epidemiology Deals with one population Risk ? case Identifies causes (www)
212 : Two or more populations Humans Infectious agents Helminths, bacteria, fungi, protozoa, viruses, prions Vectors Mosquito (protozoa-malaria), snails (helminths-schistosomiasis) Blackfly (microfilaria-onchocerciasis) – bacteria? Animals Dogs and sheep/goats – Echinococcus Mice and ticks – Borrelia What is infectious disease epidemiology? (www)
213 : A case is a risk factor … Infection in one person can be transmitted to others What is infectious disease epidemiology? (www)
214 : The cause often known An infectious agent is a necessary cause What is infectious disease epidemiology then used for? Identification of causes of new, emerging infections, e.g. HIV, vCJD, SARS Surveillence of infectious disease Identification of source of outbreaks Studies of routes of transmission and natural history of infections Identification of new interventions What is infectious disease epidemiology? (www)
215 : Concepts Specific to Infectious Disease Epidemiology Attack rate, immunity, vector, transmission, carrier, subclinical disease, serial interval, index case, source, exposure, reservoir, incubation period, colonization, generations, susceptible, non-specific immunity, clone, resistance, repeat episodes …
216 : Definitions Infectious diseases Caused by an infectious agent Communicable diseases Transmission – directly or indirectly – from an infected person Transmissible diseases Transmission – through unnatural routes – from an infected person Tetanus Measles vCJD (www) Infectious Disease
217 : Routes of transmission Direct Skin-skin Herpes type 1 Mucous-mucous STI Across placenta toxoplasmosis Through breast milk HIV Sneeze-cough Influenza Indirect Food-borne Salmonella Water-borne Hepatitis A Vector-borne Malaria Air-borne Chickenpox Ting-borne Scarlatina Exposure A relevant contact – depends on the agent Skin, sexual intercourse, water contact, etc (www)
218 : No infection Clinical Sub-clinical Carrier Death Carrier Immunity No immunity Outcome (www) Exposure to Infectious Agents
219 : (www) Timeline for Infection
220 : Cases Index – the first case identified Primary – the case that brings the infection into a population Secondary – infected by a primary case Tertiary – infected by a secondary case (www) Transmission
221 : Disease is the result of forces within a dynamic system consisting of: agent of infection host environment Epidemiologic Triad
222 : Agent Host Environment Age Sex Genotype Behaviour Nutritional status Health status Infectivity Pathogenicity Virulence Immunogenicity Antigenic stability Survival Weather Housing Geography Occupational setting Air quality Food (www) Factors Influencing Disease Transmission
223 : Infectivity (ability to infect) (number infected / number susceptible) x 100 Pathogenicity (ability to cause disease) (number with clinical disease / number infected) x 100 Virulence (ability to cause death) (number of deaths / number with disease) x 100 All are dependent on host factors Epidemiologic Triad-Related Concepts
224 : Predisposition to Infections (Host Factors) Gender Genetics Climate and Weather Nutrition, Stress, Sleep Smoking Stomach Acidity Hygiene
225 :
226 : Horton & Parker: Informed Infection Control Practice (www) Chain of Infection
227 : Iceberg Concept of Infection
228 : Bacteria Viruses Fungi Protoctists / Protozoa Helminths Infectious Agents
229 : A host that carries a pathogen without injury to itself and serves as a source of infection for other host organisms (asymptomatic infective carriers) Reservoirs
230 : Humans {hepatitis} Other Vertebrates {zoonoses} Birds & Bats {histoplasmosis} NOT vectors Reservoirs
231 : Vectors A host that carries a pathogen without injury to itself and spreads the pathogen to susceptible organisms (asymptomatic carriers of pathogens)
232 : Arthropod Vectors Pathogen - Vector Viruses (Arbovirus) - Mosquitoes Bacteria (Yersinia) - Fleas Bacteria (Borrelia) - Ticks Rickettsias (R. prowazeki) - Lice, ticks Protozoa (Plasmodium) - Mosquitoes Protozoa (Trypanozoma) -Tsetse flies Helminths (Onchocerca) - Simulium flies
233 : Ecological Factors in Infections Altered environment {Air conditioning} Changes in food production & handling {intensive husbandry with antibiotic protection; deep-freeze; fast food industry} Climate changes {Global warming} Deforestation Ownership of (exotic) pets Air travel & Exotic journeys / Global movements Increased use of immunosuppressives/ antibiotics
234 : Infectious Disease Process Direct tissue invasion Toxins Persistent or latent infection Altered susceptibility to drugs Immune suppression Immune activation (cytokine storm)
235 : Endemic - Epidemic - Pandemic Endemic Transmission occur, but the number of cases remains constant Epidemic The number of cases increases Pandemic When epidemics occur at several continents – global epidemic R = 1 R > 1 R < 1 (www)
236 : Endemic Epidemic Number of Cases of a Disease Time Endemic vs Epidemic
237 : Levels of Disease Occurrence Sporadic level: occasional cases occurring at irregular intervals Endemic level: persistent occurrence with a low to moderate level Hyperendemic level: persistently high level of occurrence Epidemic or outbreak: occurrence clearly in excess of the expected level for a given time period Pandemic: epidemic spread over several countries or continents, affecting a large number of people (www)
238 : INVESTIGATION OF EPIDEMIC
239 : OBJECTIVES TO DEFINE THE MAGNITUDE OF THE EPIDEMIC OUTBBREAK OR INVOLVEMENT IN TERMS OF TIME , PLACE AND PERSON TO DETERMINE THE PARTICULAR CONDITIONS AND FACTORS RESPONSIBLE FOR THE OCCURRENCE OF THE EPIDEMIC
240 : 3. TO IDENTIFY THE CAUSE, SOURCE OF INFECTION AND MODES OF TRANSMISSION TO DETERMINE MEASURES NECESSARY TO CONTROL THE EPIDEMIC 4. TO MAKE RECOMMENDATIONS TO PREVENT RECURRENCE
241 : STEPS 1. VERIFICATION OF DIAGNOSIS 2. CONFIRMATION OF THE EXISTENCE OF THE EPIDEMIC 3. DIFINING THE POPULATION AT RISK OBTAINING A MAP OF THE AREA COUNTING THE POPULATION
242 : 4. RAPID SEARCH FOR ALL CASES AND THEIR CHARACTERISTICS MEDICAL SURVEY EPIDEMIOLOGICAL CASE SHEET SEARCHING FOR MORE CASES
243 : 5. DATA ANALYSIS TIME PLACE PERSON 6. FORMULATION OF HYPOTHESIS 7. TESTING OF HYPOTHESIS
244 : 7. EVALUATION OF ECOLOGICAL FACTORS 8. FURTHER INVESTIGATION OF POPULATION AT RISK EXPOSURE TO SPECIFIC POTENTIAL VEHICLES WHETHER ILL OR NOT
245 : 9. WRITING THE REPORT BACKGROUND HISTORICAL DATA METHODOLOGY OF INVESTIGATION ANALYSIS OF DATA CONTROL MEASURES
246 : Classical Infectious Diseases Epidemiology Edward Jenner (1749-1823) developed a vaccine against smallpox using cow pox 160 years before virus was identified John Snow (1813-1858) described the association between dirty water and cholera 44 years before vibrio was identified Ignaz Semmelweis (1818-1865) described the association between childbed fever and physician’s unclean hands 32 years before causal agent was discovered
247 : Epidemiology & Clinical Medicine Epidemiology is used in clinical medicine to: describe the natural history of diseases discuss disease causality - proximate: biological mechanisms of disease - distal: social and environmental causes of disease provide disease surveillance - essential for evaluating community health problems - - and setting disease control priorities
248 : Epidemiology & Clinical Medicine Epidemiology is used in clinical medicine to: evaluate diagnostic testing - evaluate usefulness, sensitivity, specificity - to set cutoff points, and develop screening strategies evaluate prognosis - by identifying prognostic factors - through cohort and case control studies
249 : Epidemiology of Chronic Diseases Observational Studies: R Doll & AB Hill. Early case-control study. Smoking and carcinoma of the lung: Preliminary report. [Br. Med. J. 2:739, 1950] Cohort Studies: An approach to longitudinal studies in a community: the Framingham study. 10,000 residents gave baseline information. Follow-up is now 50 years. [Annals New York Academy of Sciences 107:539;1963]
250 : Epidemiology of Chronic Diseases Experimental Studies: Hypertension Detection and Follow-up Program Cooperative Group. 10,500 subjects randomly assigned to two groups: 1. stepped care - antihypertensive therapy increased stepwise to achieve and maintain blood pressure reduction to goal. 2. Referred care - subjects were referred to their primary care physician and treated as usual. mortality stepped care 9.0/100 referred care 9.7/100 final blood pressure 84.1 in stepped care 89.1 in referred care
251 : Classical Nutritional Epidemiology James Lind (1716-1794) conducted an experiment which showed that scurvy could be treated and prevented with limes, lemons, and oranges ascorbic acid was discovered 175 years later Joseph Goldberger (1874-1927) identified that pellagra was not infectious but nutritional in origin and could be prevented by increasing the amount of animal products in the diet and substituting oatmeal for corn grits niacin was discovered 10 years later
252 : Psychiatric epidemiology Epidemiology is used in many psychiatric studies For collection of data (questionnarie) Analysis (statisitcs) Planning and evaluation
253 : Chicago Study : Faris and Dunham (1922-1934) 35,000 admissions to mental hospitals 1st admissions for schizophrenia highest in inner city areas within lowest socioeconomic groups Led to the social drift and social segregation hypotheses And to the social causation and social selection theories
254 : Midtown Manhattan: Rennie and Srole (1954) 1660 adults, structured interview by non psychiatrists Incidence of mental disorder increased with age Low socioeconomic group had 6 times as many symptoms as those in the high groups
255 : Molecular and Genetic epidemiology It is used to study the natural history of genetic disorders To identify the cause /risk factors To find out association b/w different factors To study the distribution To take measures to reduce the genetic disorders
256 : References Park text book of preventive and social medicine 20th edition Baegelhole and Boneta – Basics of epidemiology Oxford text book of public health Barker’s applications of public health Greenberg RS (ed.) Medical Epidemiology Various internet sites
257 : Thank U

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