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Midterm Study Guide

by: Crysta Meekins

Midterm Study Guide 310

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Crysta Meekins

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Disease Detectives: Epidemiology in Action
Study Guide
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This 7 page Study Guide was uploaded by Crysta Meekins on Sunday October 16, 2016. The Study Guide belongs to 310 at University of Kentucky taught by Dr.WIlson in Fall 2016. Since its upload, it has received 9 views. For similar materials see Disease Detectives: Epidemiology in Action in Public Health at University of Kentucky.

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Date Created: 10/16/16
CPH 310 Review  Communicable Diseases (Lecture 3) - Communicable disease: an illness due to a specific infectious agent or its toxic products that arises through transmission of that agent or its products from an infected person, animal, or reservoir to a susceptible host. - Infection: the entry and multiplication of an infectious agent within, or intruding into, the body - Infestation: the presence of an agent on the surface of the body o Lice, scabies - Contamination: the presence of an infectious agent on articles of apparel or soiled articles - Zoonosis: a disease that can be naturally transmitted between animal (vertebrae) hosts and human o Influenza strains, rabies - Emerging pathogen: an agent or infectious disease whose incidence is increasing following its appearance in a new host population o Ebola - Susceptibility of a host to disease factors: o Genetics o Nutrition o Prior exposure o Vaccination o Presence of other diseases o Age - Direct transmission o Person to person contact Touching Kissing Sex Airborne, short-distance-via droplets from coughing or sneezing Transplacental - Indirect transmission o Vehicles/fomites (contaminated inanimate objects) Food Water Toys Surgical tools, syringes o Vector (transmission through another animal) Mammals Arthropods - Airborne, long distance-when microbes are aerosolized and remain suspended in air for long periods of time - Infectivity: the ability of an agent to invade and multiply in a host - Pathogenicity: the ability to produce disease, given infection - Virulence: severity of the disease caused by the agent - Incubation period: the time it takes from exposure until the infectious agent begins producing disease symptoms - Herd immunity: prevalence of immunity among others, which makes it more difficult for disease to spread throughout the population - Convalescent carrier: infectious, but recovering from illness - Incubatory carrier: infectious, but in early, pre-clinical stage of disease - Endemic: usual level of disease in the population of a defined area - Epidemic: an unusually high level of a disease in a defined area - Pandemic: an unusually high level of a disease globally, or over a very wide area - Epi Curves are useful for describing: o Magnitude o Outliers o Temporal trend o Incubation period Chronic Diseases (Lecture 4) - Acute: diseases with a sudden onset, sharp rise, and short course - Chronic: diseases marked by long duration or frequent recurrence - Chronic illness is characterized by: o Uncertain etiology o Multiple risk factors o Long latency periods o Prolonged course o Non-contagious agent o Incurability o Functional impairment - Leading cause of death and disability in US - 70% of all deaths in the US - Big 3: heart disease, cancer, diabetes - Epidemiologic Transition o 1 era in public health: the communicable diseases nd o 2 era: chronic disease erath Began in the mid-20 century, particularly among the industrialized nations o First occurred among the affluent in developed countries o Death rate falls o Birth rate initially stays the same, then later falls - Prevention Types o Primordial: social, economic, or environmental factors Reduce air pollution, support active transportation, higher taxes for cigarettes o Primary: intervene before disease develops Improving diet, quitting smoking, exercise, vaccinations o Secondary: intervene early in the course of the disease (usually via screening) Colonoscopy, mammogram, pap smear o Tertiary: prevent disability Statins, daily aspirin, insulin Measuring Disease I & II (Lectures 5-6) - Incidence o Measures the new occurrence of a disease in a population o RISK of disease in a population - Prevalence o Measures the current existence of disease in a population o Prevalence= Incidence X Duration of disease o BURDEN of disease in a population - Death Rates o Case fatality # deaths from a disease/# diagnosed with disease Disease severity o Disease specific # deaths due to a specific disease/total population o Age-specific # deaths in a specific age group/population in same age group o Crude mortality # deaths/ total population o Proportionate Mortality Proportion of deaths due to a specific cause Always a percent - Age Standardization o Necessary when comparing rates of disease across populations with different age distributions o Age-adjusted rates Multiply age specific rates from each population by population counts for the same age groups in a reference population o Standardized mortality ratios (deaths observed/deaths expected)* 100 <100 means lower mortality >100 means higher mortality  Study Designs (Lectures 7-10) - Hierarchy of Evidence o Systematic Review ***Top o Experimental o Cohort o Case-control o Cross-sectional o Case report/case series o Ecological (population) **Bottom - Types of Studies o Ecological  A study in which the units of analysis are populations or groups, rather than individuals  Geography based  Temporal trend  Strengths  Good for hypothesis generation  Especially good for rare diseases  Good for evaluation of population-wide changes or differences, perhaps related to policies, law  Inexpensive and quick, since they are relying on existing data  Weaknesses  Ecological fallacy: inappropriate conclusions regarding relationships at the individual level, based on observations at the group level  Group-level data are not always good evidence of a casual link at the individual level  Atomistic fallacy: the opposite, where group level relationships are erroneously based on observations at the individual level  Very difficult to control for confounding  Exposure and disease unknown at individual level o Cross-Sectional  Examines the relationship between diseases and exposures as they exist at one particular point in time  Strengths  Can often be completed with existing data, so relatively quick, inexpensive  Can adjust for effects of other variables  Exposure usually current, easier for subjects to recall  Weaknesses  Cannot establish temporal relationship  Prevalent cases are not necessarily representative of incident cases  Selection bias: some people are more likely to participate based on their exposure or disease status o Case-Control  Observational, analytic epidemiologic investigation in which subjects are selected on the basis of whether they do (cases) or do not (controls) have a particular disease  Retrospective  Controls  Patients at clinics/hospitals  Population  Friends/spouses/relatives o Cohort  Subsets of a defined population cane identified who are… exposed or not exposed, or exposed in different degrees  Starts with people free of disease  Prospective, longitudinal, and follow-up studies  Strengths  Good for rare exposures  Can evaluate multiple effects of exposure  Clear temporal relationship  Weaknesses  Loss to follow-up  Costly  Requires very large sample  General comparison groups  Internal comparison (exposed vs. unexposed members of same cohort)  External comparison (members of cohort vs. unexposed cohort from another study)  General population (members of cohort vs. general population) o Experimental  Assign treatments/interventions in an attempt to change disease exposures or outcomes and/or to determine causality Biostatistics (Lectures 11-12) - Descriptive: summarize a sample selected from a population - Inferential: make inferences about population parameters based on sample statistics o Asking questions about a population based on a sample - Estimation: what is the average value in the population, based on a sample? - Hypothesis Testing: is the average value in the population above a certain value? Is it different than the corresponding values in another population? - Normal distribution o Mean=median=mode o “Gaussian” o Used as model for continuous data o Described by mean and standard deviation - P-value o Probability that the observed result (from test statistic) would occur, assuming the null hypothesis is true o A p-value of 0.05 represents a 5% chance that the conclusion is incorrect - Categorical data o Ordinal: order is important o Nominal: unordered categories (race, state, occupation, color) o Binary: two categories - Continuous data o Represents measurable quantities, not restricted to specified values. Can have an infinite number of selected values between two numbers (range) - Summary of statistical tests Research Types of Data Key Words Statistical Question Test Does the frequency / rate / c (chi- distribution of 2 categorical Proportion, squared) a(n) exposure variables rate, frequency / disease test differ among groups? Was there a change in 1 categorical mean values (before/after), Change, mean Paired after (matched treatment / 1 continuous values pair) t-test education / variable intervention? Are the mean Student’s 1 categorical, 1 values of two continuous Mean values, (independe groups variable two groups nt sample) different? t-test Is there a difference in mean values 1 categorical, 1 Mean values, between continuous three or more ANOVA variable groups groups (three or more)? Is there a linear 2 continuous Linear, two Simple  relationship regression / Correl between two variables variables correlation ation variables? vs. Causation (Lecture 13) - Correlation: statistical dependence between two or more events, characteristics or ther variables - Causation: the act of causing something - Bradford Hill Criteria o Strength The stronger the relationship between independent and dependent variables, the less likely it is due to an extraneous variable or chance o Consistency Multiple observations of association by different people under different circumstances increase the belief the association is real o Specificity An outcome is predicted by one primary factor adds credibility to a causal claim o Temporality (time relationship) The cause needs to precede the outcome o Biological gradient There should be a direct relationship between the degree of risk and probability of outcome o Plausibility Rational, theoretical basis for association between the risk factor and disease o Coherence The association does not conflict with other knowledge about the risk and disease o Experiment Research based on experiments makes the casual inference more believable o Analogy Using a commonly accepted association in one area to another similar area - Sufficient cause: a complete causal mechanism that inevitably produces disease - Necessary cause: a required component cause for disease to occur - component cause


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