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Epidemiology It is the study of the distribution and determinants of health related states or events in specific populations and the application of this study to control health problems. Assumptions in Epidemiology Studies 1. Diseases are NOT randomly distributed in populations. 2. Diseases have specific causes that can be identified, prevented, and treated. Functions of Epidemiology To discover the agent, host, and environmental factors which affect health, in order to provide the scientific basis for the prevention of disease and injury and the promotion of health. Functions of Epidemiology To determine the relative importance of causes of illness, disability, and death, in order to establish priorities for research and action. Functions of Epidemiology To identify those sections of the population which have the greatest risk from specific causes of ill health, in order that the indicated action may be directed appropriately. Functions of Epidemiology To evaluate the effectiveness of health programs and services in improving the health of the population. Objectives of Epidemiology To identify the etiology (cause) of a disease and the risk factors associated with the disease. Objectives of Epidemiology To determine the extent of disease found in the community. What is the burden of disease? Objectives of Epidemiology To study the natural history and prognosis of the disease. Objectives of Epidemiology To evaluate both existing and new preventative and therapeutic measures and modes of health care delivery. Objectives of Epidemiology To provide the foundation for developing public policy and regulatory decisions relating to epidemiologic problems. Issues in Epidemiology Where there is a link between factor and health outcome - does this mean the factor is the cause of disease? Issues in Epidemiology Is there an association, does the amount of disease vary according to the amount of exposure to the factor? Issues in Epidemiology Based on the observation of such an association, what practical steps should individuals and public health departments take? Issues in Epidemiology Do the findings from an epidemiologic study merit panic or measured response? Issues in Epidemiology How applicable are the findings to settings other than the one in which the research was conducted? Epidemiological Approach Observation. Epidemiological Approach Definition of disease process. Epidemiological Approach Descriptive epidemiology. Epidemiological Approach Analytical Epidemiology. Epidemiological Approach Experimental Epidemiology. Surveillance Ongoing and systematic collection, analysis and interpretation of health related data. Primary prevention Prevention or cessation of risk factor exposure (active or passive). Secondary prevention Intent to reduce progress of disease, screenings for 'high risk' subjects - detection. Involves people who already have a disease. Tertiary prevention Reduces limitation of disability from disease. Population-based approach/public health approach Applied to whole population, dietary modification, must be inexpensive and non-invasive. High-risk approach (clinically based) Expensive or invasive (ie. colonscopy for those with family history, cholesterol screening for children from high risk families). Hippocrates 400 BC - Found that disease is associated with physical environment. Francis Bacon Inductive logic, Law of Mortality --> law of epidemics. Royal Society of London 1662 - John Graunt published a comparative study of mortality and morbidity in human populations. Referred to as the Columbus of Statistics. Quantified patterns of disease. James Lind 1747 - etiology and treatment of scurvy, use of comparison group. Morbidity Rate High incidence of disease among sailors. Diet Impact Diet among sailors at sea hard on digestion. Experimental Trial Conducted using a comparison group. Edward Jenner 1768 - use of observational data. Pierre Charles-Alexandre Louis Comparison of groups of individuals, emphasized use of statistical methods in medicine. William Farr In charge of medical statistics in the Office of the Registrar General for England (1839), set up a system for routine compilation of the numbers and causes of deaths. John Snow Investigated cholera from 1849-1854, known as the 'Father of Epidemiology'. Bacteriological Revolution Described the 'Point-contact spread' of infection. Salk Vaccine 1954 - largest formal human experiment. US Surgeon General's Advisory Committee on Smoking and Health Established in 1964. Microcomputer Technologies 1970's - evolution allowed new multivariate statistical methods to develop. Molecular Biology Techniques 1990s - application of techniques in molecular biology to large populations. Three Stages of Modern Epidemiology Sanitary statistics, Infectious disease epidemiology, Chronic disease epidemiology. Sanitary Statistics Focus on poisoning by soil, air, water. Infectious Disease Epidemiology Based on germ theory (single agent, specific disease). Chronic Disease Epidemiology Since WWII, utilizes a 'black box' approach focusing on risk factors. Successes in Epidemiology and Public Health Includes cholera, smallpox, Legionnaire's Disease, Infant Mortality/life expectancy, Toxic Shock Syndrome, smoking/tobacco (lung cancer), CHD - Coronary Heart Disease. Vector Any insect or living carrier that transports infectious agent from infected individual or its waste to a susceptible individual or its food. Vehicle Contaminated inanimate object that transmits the disease (e.g., doorknob). Teenage Smoking Example Host = teenagers; agent = cigarettes; vector/vehicle = advertising; environment = social setting. Stages of Disease Includes Stage of susceptibility, Subclinical disease, Clinical disease. Clinical Infection Presence of signs and symptoms. Nonclinical Infection Includes preclinical, subclinical, persistent, latent. Preclinical Not yet apparent, but will progress. Subclinical An infectious state with no clinical symptoms, usually diagnosed by serological response or culture. Persistent (Chronic) Infection A chronic infection with continued low-grade survival and multiplication of the agent. Latent Infection/Disease An infection with no active multiplication of the agent; only the genetic message is present. Carrier Status Individual that has the organism but is not infected, capable of transmitting. Horizontal Transfer Transmission within a population, between a source and vulnerable person. Vertical Transfer Transmission from mother to baby, of a genetic or infectious nature. Single Exposure One time contact, all infected at the same time, single epidemic peak. Multiple Exposure More than one contact (e.g., TB). Continuous Exposure Constant and always present (e.g., cholera). Case Single person, individual with illness. Disease Cluster Several cases of disease in a certain area. Epidemic Disease excess of expected, differs by type of disease. Endemic Habitual presence of disease within an area. pandemic worldwide epidemic (Ex. 1919 Flu, obesity, HIV, chronic diseases) incubation period time we are first exposed until first symptoms, helps determine the cause of disease because diseases have different incubations periods Calculate incubation period -Collect patient data - case finding -For example, determine that 100 people who ate egg salad at a potluck lunch got sick -We find these people and ask them: -What time did you eat the egg salad? -What time did you feel the first symptoms? -Difference is incubation period -Calculate difference for each person and plot histogram epidemic curve distribution of the times of onset for cases occurring during an outbreak -Tells about mode of transmission, occurrence of an epidemic, time and source of exposure, mode of transmission, causative agent single source, single exposure rapid rise in cases, cases are limited to those who share the exposure, secondary cases are rare index first case in a family or other group to come to the attention of the investigator person to person contact -Epidemic curve shows an epidemic that grows as it spreads -Propagated outbreak -Cases occur over >1 incubation period -Expect to see successive peaks reflecting increasing number of cases in each generation -Few actually show classic pattern immunity the capacity of a person when exposed to an infectious agent to remain free of infection or clinical illness herd immunity the resistance of a group to attack by a disease because a majority of individuals are immune; thus lessening the likelihood that a susceptible person will come in contact with a patient with the disease -Is it necessary to vaccinate everyone? -Not necessary to achieve 100% immunization, immune large percentage and the rest will be immune. Optimal when populations are constantly mixing together. attack rate Type of incidence measure -Number of people at risk for a disease who develop the disease compared to the total number of people who are at risk for the disease attack rate formula = # of people AT RISK who develop illness / Total # of people AT RISK incidence rate formula (# new cases of disease occurring in population during specified time / Total population at risk of developing disease during that time) X per 1000 people secondary attack rate the attack rate in susceptible people who have been exposed to a primary case. secondary attack rate formula = # of people exposed to a primary case who develop illness / Total # people susceptible after first wave cross tabulation method for examining the influence of multiple variables in combination Outbreaks - Epidemics -The occurrence of disease in excess of what is expected -Unexpected - immediate response may be demanded -Fieldwork needed -Limited investigation because timely intervention needed -Use surveillance system to determine what is expected -Is disease endemic? -Is disease process known? Steps in Investigation of Disease Outbreak -Determine if outbreak exists -Distribution of cases -Look for combination of relevant variables -Develop hypothesis -Test hypothesis -Implement control and prevention efforts -Communicate findings case definition criteria that must be met for the patient to qualify as having the disease (based on clinical symptoms or test results) positive declaration (research hypothesis): the infant mortality rate is higher in one region than another negative declaration (null hypothesis): there is no difference between the infant mortality rates of 2 regions. implicit question is there an association between infant mortality and geographic region of residence? Develop and Test Hypothesis Based on knowledge of cases and disease formulate hypothesis; Using data collected test hypothesis (use measures of risk) Control Measures Control outbreak; Prevent future outbreak; Timing important and difficult; Challenge to balance responsibility to prevent further disease with 'political' considerations Communicate Findings Report to state and local health agencies, CDC; Inform others - businesses, manufacturers, etc. (ex. Tylenol); Need to share information with public must be assessed (ex. anthrax) Food Borne Disease Outbreak 2 or more people get sick from a common food count number of cases, number of deaths ratio divide one quantity by another, no specified relationship between numerator and denominator. Example; 1000 motorcycle fatalities 950 are men, 50 women 950/50= 19:1 male to female. proportion numerator is part of the denominator, may be expressed as percentage. Example; number of fetal deaths over the total number of births. rates A ratio with a distinct relationship between numerator and denominator and a measure of time is an intrinsic part of the denominator. Example; number of colds per 1000 elementary school students during a one month period. disease incidence # of NEW cases of a disease occurring during a specified period of time in a population at risk for the disease cumulative incidence the incidence calculated when all persons within the denominator are considered to be at risk for the disease for the same period of time. incidence rate/incidence density denominator consists of the sum of different times each individual was at risk -- expressed as person-time (cases per person-years) prevalence the number of EXISTING CASES of a disease or health condition in a population at some designated time. Point Prevalence number ill at a point in time divided by the total number in group at a point in time. Period Prevalence number ill during a time period divided by the average population during a time period. Cumulative/Lifetime prevalence prevalence of a disease during the lifetime of an individual. incidence/prevalence issues Numerators: defining who has the disease; Problems with recording data/ hospital data; Denominators- undercounting of minority groups Surveillance the ongoing systematic collection, analysis and interpretation of outcome-specific health data, closely integrate with the timely dissemination of these data to those responsible for preventing and controlling disease or injury. passive surveillance relies upon reporting of cases by health care professionals at their discretion. Routine reporting. Prone to error. Inexpensive. active surveillance depends on periodic solicitation of case reports from health care providers or facilities. Generally more accurate and complete but requires more effort and is expensive. Sentinel Surveillance Relies on reports of cases of disease whose occurrence suggests that the quality of preventive or therapeutic medical care needs improvement. Serves as warning to health officials. Inexpensive. Lacks specificity regarding cause of disease and risk factors. SEER Program National Cancer Act 1971 established the National Cancer Program under which the Surveillance, Epidemiology, and End Results Program was developed. SEER collects cancer data throughout the US. Uses of Surveillance Information - Immediate Epidemics, emerging health problems, changes in health practices, changes in antibiotic resistance. Uses of Surveillance Information - Annual Estimating magnitude of health problem, assessing control activities, setting research priorities, testing hypotheses, etc. Uses of Surveillance Information - Archival Describing natural history of diseases, facilitating epidemiologic and lab research, setting research priorities, documenting distribution and spread. Mortality The number of deaths occurring during a period of time within a specified population. Mid-point populations often used in calculating rates. Crude Rates Presented for entire population, summary measures, actual # of events over a given time period. The proportion of population that dies during a time period. Specific Mortality Rate The number of deaths during a set period divided by the mid-point population limited to a specific disease, population group or combination. Case-Fatality Rate The number of persons who die from a disease within a certain period of time divided by the total number of people who have the disease. Proportionate Mortality The percent of deaths attributable to a specific cause of death (not a rate, can be specific to demographic in conjunction to disease). Years of Potential Life Lost (YPLL) A measurement of time lost due to mortality. 16/18 years old through 65 years old are considered 'productive' years. Calculated at 65 minus age at death. Why Look at Mortality Data? Provides clues to changes in patterns of disease occurrence. Mortality can be reflection of incidence when case-fatality rate is high, duration of disease is short. Sources of Mortality Data Death certificates, mortality reports/surveillance. Problems with Mortality Data Classification of cause of death, underlying vs. contributory cause, accuracy of causes of death, population data. Adjustment of Rates Makes comparison of morbidity or mortality rates between two groups more accurate (indirect or direct). Direct Age Adjustment Used if age-specific death rates in a population known and suitable standard population is available. Requires application of observed rates of disease in a population to some standard population to derive an expected number of mortality. Indirect Adjustment Does not require knowledge of actual age-specific incidence or mortality rates among each group. Comparison of one population group's rates against a standard population's rates using the first group's base population. Direct Adjustment Equalize differences in population distribution by applying an outside, standardized population to the rates of the groups to be compared. Direct vs. Indirect Adjustment Indirect adjustment compares a study population to a standard. Can be used in any situation where a standard has been determined. Small random error Standard rates are determined from very large samples. Screening Application of a test to people who are as yet asymptomatic for purpose of classifying them with respect to their likelihood of having a particular disease. Risks and costs must be weighed against benefit. Not diagnosing illness. Diagnostic and/or screening tests Tests designed to separate persons without disease from individuals with disease based on biological variable. Ex: Diabetes (blood sugar). Factors in a screening test Disease Related Factors: diseases often include a sub-clinical period, early treatment provides benefits to patients. Test Related Factors: valid and reliable test is available, test is inexpensive, easy to use, minimally intrusive. Feasibility: willingness of the population to submit to screening, treatment is available if disease is detected. Example: Hypertension Serious, risk of death increases with higher levels of blood pressure, early treatment reduces risk. Validity The ability of a test to accurately indicate which individuals in a population have a disease and which do not. Sensitivity The ability of a test to correctly identify those who have the disease. Specificity The ability of a test to correctly identify individuals who do NOT have the disease. Gold Standard External source of truth regarding the disease status of each individual. Defines the presence of disease. The best diagnostic assessment available. May be another test. Two by Two for a screening test A = True Positives (TP) - have disease and have a positive test. B = False Positives (FP) - no disease but have positive test. C = False Negatives (FN) - have disease but have negative test. D = True Negatives (TN) - no disease and have negative test. Sensitivity = (A) / (A+C) OR (True Positives) / ((True Positives) + (False Negatives)). Specificity = (D) / (B+D) OR (True Negatives) / ((False Positives) + (True Negatives)). Trade-offs Determining a cut-off level where a test result is considered positive or negative is needed. Depends on nature of disease. Sometimes you decide cutoff. Choosing cut-offs Ask yourself: What is the consequence of an undetected case? What is the consequence of calling a disease-free person a positive? At what level does risk increase (i.e. at what point should someone receive treatment?). Series testing Sequential testing, we have two screening tests, someone is defined as having disease if they test positive on BOTH, if someone tests negative on EITHER test they are considered to not be diseased. Parallel testing Two screening tests. Someone is defined as having disease if they test positive on EITHER test. Someone has to test negative on BOTH tests before they are considered to be free of the disease. Positive Predictive Value The likelihood that someone with a positive test result really has disease. Can be determined by using a gold standard as comparison. Negative Predictive Value The likelihood that someone with a negative test result really does NOT have disease. Can be determined by using a gold standard as comparison. Predictive Values Highly affected by disease prevalence and specificity and lesser so by sensitivity. The PPV in one population will not be the same as in another population. PPV decreases with decreased prevalence and specificity and increases when prevalence and/or specificity is high. NPV decreases when prevalence increases and/or specificity is low and vice versa. Reliability The measure of whether a test gives the same results after repeat testing. overall percent agreement measure of the total agreed upon number of observations between two tests/observers out of the total number of observations. paired percent agreement measure of the agreement between two tests/observers divided by the total number of pairs where at least one of the two tests/observers indicate that a positive result has occurred. kappa statistic evaluates how much better than random chance is the agreement between two tests/observers. Observed agreement is equal to overall percent agreement. Normally a value between 0 and 1. expected agreement determined by adding together the number of positive test results that we expect the observers to agree upon by chance along and the number of negative test results that we expect to be agreed upon on chance alone. preclinical phase anytime after disease onset while there are no outward signs and symptoms. clinical phase any time after disease onset where signs and symptoms are present. case-fatality rate the number of persons who die from a disease within a certain period of time divided by the total number of people who have the disease (%) - best used when disease is short term, not chronic. 5 year survival the percentage of people alive 5 years after diagnosis/initiation of treatment. observed survival person-years assumes that person-years are equivalent. For example, the experience of 1 person observed for 10 years is the same as 10 people observed for 1 year each. life tables a way of using the actual observed survival over time to measure prognosis. Survival rates/percentages can be determined for specific time intervals or aggregate periods (resulting in cumulative survival probabilities). Median Survival Time the length of time until exactly half of the study group has died. Not affected by outliers. Relative Survival compares the survival of a group to the survival we would expect in the group if they did not have the disease. Greater in older age groups. Kaplan-Meier life table approach uses intervals to group events. Kaplan and Meier developed a method that does not use intervals but calculates the survival probability each time an event occurs. "Withdrawn" people remove them completely from being at risk, count them completely as being at risk, count them for being at risk part of the interval. birth certificates calculate birth rates, birth conditions, studies of environmental influences on congenital malformation. reportable disease statistics usually infectious and communicable diseases. disease registries centralized database for collection of information about a disease. morbidity data surveys collect data on health status of a population. hospital and clinic records inpatient and outpatient data. Special Clinics/Hospitals Advantages: specialized information on disease. Physician Practices Advantages: valuable supplemental information, verify self-report against medical records, source of exposure data. School Health Programs physical exams, immunization history, cognitive and other tests. Census Data valuable source of information - social, economic characteristics.