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Epidemiology
| Question | Answer |
|---|---|
| What is epidemiology? | “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” |
| exposures | “Determinants”: causes, risk factors or preventive factors that influence the ocurrence of disease or other outcomes |
| study population | • All epidemiological studies refer and to a specific study population • Defined by identifiable characteristics of time, place and person, e.g. age, occupation, etc |
| Sources of epidemiological data for study | • Population census • Vital statistics • Births / deaths • Hospital records + primary care records • Public health surveillance • Chronic disease registries • Epidemiologic research • “Big data” |
| Descriptive epidemiology | Describe patterns of disease |
| Analytical epidemiology | Examine associations between diseases and risk factors |
| Experimental epidemiology | Examine the effectiveness of experimental interventions |
| Proportion | A/(A + B) Number of individuals meeting a criterion / total number of people in the population or group |
| Ratio | X/Y comparing two unrelated but similar quantities (same units) |
| Rate | A/t or A/((A + B) ∗ t) Count or proportion of new cases per unit time. Often used with person-time as denominator |
| Risk | P Probability of an event occurring (essentially a proportion: cases / people at risk) |
| Odds | P/(1 − P) An alternative expression of probability. Probability of occurrence / probability of non-occurrence |
| Hazard | The instantaneous probability of an event happening at time t, given that it has not already happened. Used in survival analysis |
| Incidence | Counts new cases of the disease (or outcome) • Cumulative incidence • Incidence rate |
| Prevalence | Counts existing cases of the disease (or outcome) • Point prevalence • Period prevalence • Prevalence = Incidence rate × duration of disease |
| Attack Rate (AR, %) | Number of cases during outbreak/Population at risk it is a proportion |
| Mortality rate | Number of deaths per population per unit time • Crude (all-cause) vs cause-specific mortality • Usually annual, per 100,000 or 1,000 population (at mid-year) • Synonym: mortality |
| Case Fatality Rate | Proportion of deaths among people with a certain disease (and over a period of time) • NOT a rate! Denominator = ill persons |
| Malaria, Influenza | ↑ incidence and mortality rates, despite ↓ CFR (≈0.5% malaria, influenza usually lower) |
| Ebola | Thankfully very rare and thus ↓ mortality rate, despite ↑↑ CFR (>80%) |
| Direct age standardization (or: Direct age adjustment) | Mortality is affected by the age structure of the population • It involves calculating age-specific rates and applying them to age strata of a common population. |
| Standardized Mortality Ratios (SMRs) | • Observed number of deaths in a group, divided by expected number of deaths if they had the age-specific mortality rates of the general population • Frequently used to compare the mortality of occupational groups to that of the general population. A |
| Risk Difference (RD) | RD = Risk of disease in exposed − Risk of disease in unexposed • Difference between two Risks of disease (exposed vs unexposed) |
| Risk Ratio, or Relative Risk (RR) | RR = Risk of disease in exposed / Risk of disease in unexposed • A ratio of two Risks of disease (exposed vs unexposed) |
| Odds Ratio | • A ratio of two Odds of disease (exposed vs unexposed), or, equivalently, a ratio of two Odds of exposure (persons with the outcome vs persons without the outcome) |
| Rate Ratio | • A ratio of two Rates of disease (exposed vs unexposed) |
| Analytical study | Analytical study designs examine associations between exposures and outcomes |
| Experimental study | Experimental study designs examine the associations between an intervention that we actively expose people to, and an outcome |
| Cross-sectional studies | • They establish the prevalence of disease or other factors (exposures) in the community • Can be used to study the association of outcomes and possible exposures in the population they are undertaken at a single point in time. |
| Cross-sectional studies | We can both measure a “snapshot” of the prevalence of disease, and compare between subgroups using Odds Ratios or Risk Ratios • Quickest and easiest to conduct, good to generate hypotheses – but limited due to lack of temporality |
| Cohort studies | • Participants selected, split between exposed and unexposed, and followed-up over a period of time • Risk or Rate of disease is measured and compared across the two groups • Expressed with a Risk Ratio (Relative Risk) or Rate Ratio |
| Cohort studies | • Participants selected, split between exposed and unexposed, and followed-up over a period of time • Risk or Rate of disease is measured and compared across the two groups • Expressed with a Risk Ratio (Relative Risk) or Rate Ratio |
| Cohort studies | • Particularly suitable for environmental or occupational exposures • Can examine multiple outcomes of the same exposure • Establishes temporality between exposure and outcome • Expensive and time-consuming |
| Cohort studies | • Open vs closed cohorts Closed cohort Fixed membership; may lose persons to follow-up, but all recruited together (e.g. a birth cohort) Open cohort Members can enter or leave at any time (e.g. a cancer registry) |
| Cohort studies | (+) • Can calculate absolute incidence, absolute risk difference, attributable risk • Can examine rare exposures • Less vulnerable to bias (especially if prospective) (-) • Exposure can change over time |
| 95% Confidence Interval (95% CI): | You can construct such an interval by adding and substracting 1.96 Standard Errors from the sample estimate (point estimate) |
| p-values: | The probability of seeing a result equally or more extreme, given this sample size, assuming the “null hypothesis” is true |
| Null hypothesis | There is NO true association/difference |
| Alternative hypothesis | There is a true association/difference |
| conditional probability fallacy: | Would you agree that the p-value is also the probability of the null hypothesis being correct? |
| Cross-sectional studies: | • Outcomes & exposures measured at a single point in time • Establish the prevalence of disease, plus study associations • Not possible to assess temporality • Quick and easy; appropriate for ↑prevalent / chronic diseases |
| Cohort studies: | • Participants selected, split exposed vs unexposed, and followed-up & should be at risk of the outcome • Risk/Rate of disease is measured and compared across the two groups with a Risk Ratio (Relative Risk) or Rate Ratio • Prospective or Retrospective |
| Ecological studies | -The study units are not individuals, but entire populations -The study units are not individuals, but entire populations -Correlate population characteristics with population outcomes |
| Ecological fallacy: | group associations might not be the same as individual associations |
| Ecological studies (+) & (-) | (+) • Quick, low-cost – use information that is already available • Very useful to generate hypotheses for further study (-) • Limited exposure information, limited control of confounding • Ecological fallacy • Cannot establish causality |
| Case-control studies: | We take all available cases from our source population, and compare them in terms of (past) exposure to an appropriately selected control group |
| rare disease assumption: | The Odds Ratio (OR) is an approximate estimator of the Relative Risk (RR), if the outcome is rare. |
| Why not just compare risk, odds or rate of disease, or maybe just mean time-to-event, between exposed and unexposed? | 1. Censoring: when follow-up is completed, but the patient may remain at risk (thus the true time-to-even, is unknown) 2. Irregular baseline hazard: the hazard of getting the outcome is not the same throughout the entire time of follow-up |
| hazard: | Recall that hazard is the instantaneous risk of something happening to you at time t + 1, provided that you’ve survived until time t |
| Right censoring: | = follow-up terminated before the event occurs (thus we have only a “lower limit” for the time-to-event) |
| Kaplan-Meier (K-M) curves | -Estimates the survival function -compare two K-M curves using the logrank test, which tells us if average survival is equal or not -If our exposure is numeric, or have multiple covariates to adjust for, we can use Cox proportional hazards regression |
| Bias | • Difference between observed and actual (population) value due to any reason except sampling • Cannot be corrected in the statistical analysis phase |
| Confounding | • A “special case” of bias • Can (partly) be corrected for in the analysis |
| Hierarchy of evidence | 1. Randomized controlled trials 2. cohort studies 2. case-control studies |
| Selection bias | • Arises from the way the sample is selected −→ not representative of the source population • (alternatively) Probability of selection not equal throughout the population = non-random sample |
| Information bias | • Arises due to systematic errors in the way exposures or outcomes are measured −→ misclassification |
| participation bias | results of studies become non-representative because the participants disproportionately possess certain traits which affect the outcome. |
| volunteer bias or self-selection bias | • Volunteers often have different characteristics than the general population • “Self-selecting” controls |
| exclusion bias | Collective term covering the various potential biases that can result from the post-randomization exclusion of patients from a trial and subsequent analyses. This may also be referred to as attrition bias. |
| survival bias or Neyman bias, incidence-prevalence bias | occurs when studying the relationship between an exposure and an outcome using prevalence of the outcome instead of incidence in cases where prevalence is a biased estimator of incidence. |
| healthy worker effect | a bias that is typically characterized by lower relative mortality and morbidity rates from all causes combined and from selected causes in an occupational cohort, possibly masking an increased risk of the disease under study |
| prevarication bias | occurs when a study subject over- or under-estimates outcome because of knowledge of the kind of treatment they had received. |
| interviewer bias | where the expectations or opinions of the person conducting an interview interfere with their objectivity, either negatively or positively, clouding their judgment of the person being interviewed |
| recall bias | Recall bias is a systematic error that occurs when participants do not remember previous events or experiences accurately or omit details |
| How to control for confounding? | 1. Restriction 2. Matching 3. Stratification 4. Multiple regression models, especially logistic regression 5. Randomization |
| Directed Acyclic Graphs – DAG | A way to organize our analysis. (Which are the potential confounder that we need to adjust for?) |
| Internal validity | lack of bias |
| External validity | is the study generalizable to different settings? |
| surrogate outcomes | an outcome that can be observed sooner, at lower cost, or less invasively than the true outcome, and that, enables valid inferences about the effect of intervention on the true outcome |
| multiple subgroup analyses | Findings from multiple subgroup analyses may be misleading. Subgroup analyses are observational by nature and are not based on randomized comparisons |
| Efficacy | Whether an intervention works under ideal(e.g. experimental) conditions. Usually higher |
| Effectiveness | Whether an intervention works in “real world” conditions. Usually lower |
| Sensitivity | is the proportion of diseased participants that are correctly classified as true positives |
| Specificity | is the proportion of non-diseased participants that are correctly classified as true negatives |
| Receiver Operating Characteristic curve (ROC curve) | is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. |
| Infectious diseases | are caused by microscopic germs (such as bacteria or viruses) that get into the body and cause problems |
| Contagious or communicable diseases | are infectious diseases that spread from person to person |
| Infectious agents | are diverse living agents (viruses, bacteria, fungi, parasites) which can replicate in their hosts and cause diseases |
| Infectivity | is the ability of a pathogen to establish an infection. More specifically, infectivity is a pathogen's capacity for horizontal transmission that is, how frequently it spreads among hosts that are not in a parent-child relationship |
| Pathogenicity | refers to the ability of an organism to cause disease. It is estimated as the proportion of infected individuals who developed symptoms |
| Virulence | is a measure of the severity of the disease it causes (i.e. the degree of pathogenicity within a group or species) |
| Immunogenicity | is the ability to induce a humoral and/or cell-mediated immune responses within the host |
| Direct contact of spread of disease; | • Person-to-person contact • Droplet spread |
| Indirect contact of spread of disease: | • Vector-borne • Airborne transmission, contaminated objects, food and drinking water, animal-to-person contact, environmental reservoirs |
| Person-to-person contact: | Transmission occurs when an infected person touches or exchanges body fluids with someone else |
| Droplet spread | The spray of droplets during coughing and sneezing can spread an infectious disease. You can even infect another person through droplets created when you speak. |
| Vector-borne disease | Some zoonotic infectious agents are transmitted by insects, especially those that suck blood. These include mosquitos, fleas, and ticks |
| Animal-to-person contact | Some infectious diseases can be transmitted from an animal to a person. This can happen when an infected animal bites or scratches you or when you handle animal waste |
| Food and drinking water | Infectious diseases can be transmitted via contaminated food and water. E. coli is often transmitted through improperly handled produce or undercooked meat |
| Contaminated objects | Some organisms can live on objects for a short time.. Transmission occurs when you touch your mouth, nose, or eyes before thoroughly washing your hands |
| Airborne transmission | Some infectious agents can travel long distances and remain suspended in the air for an extended period of time. You can catch a disease like measles by entering a room after someone with measles has departed |
| Incubation period | The time period between the occurrence of infection and the onset of disease symptoms |
| Latent period | The period of time between the occurrence of infection and the onset of infectiousness (when the infected individual becomes infectious). Individuals in this stage of the disease are said to be infected but not infectious |
| Immunity | Immunity refers to an individual's resistance to infection or re-infection by a causative pathogen. There are various types of immunity |
| Infectious | Individuals who are infected and can transmit a pathogen |
| Recovered | Recovery refers to a transitional stage from the infectious state to another non-infectious state |
| Endemic | is the habitual presence of a disease within a given geographic area |
| Epidemic | is the occurrence in a community or region of cases of an illness of similar nature and derived from a common source clearly in excess of expectancy |
| Pandemic | refers to a worldwide epidemic |
| Incubation period | is the interval from the receipt of the infection to the time of onset of clinical symptoms |
| epidemic curve | gives a graphical display of the numbers of incident cases in an outbreak or epidemic, plotted over time |
| Surveillance | provides decision-makers with guidance for developing and implementing the best strategies for programs for disease prevention and control |
| susceptibles | The class of individuals who are healthy but can contract the disease. |
| Basic reproduction number R0 | , is defined as the average number of secondary cases caused by a single infectious individual in a totally susceptible population |
| R0 measures.... | the transmissibility of an infectious agent When, R0 < 1 the infection will fade out in the long run, but if R0 > 1 the infection will lead to an epidemic |
| Generation time (Tg) | is the mean time interval between infection of one person and infection of the people that individual infects |
| The effective reproductive number (R) | equals the average number of secondary cases per infectious case in a population made up of both susceptible and nonsusceptible hosts |
| herd immunity | The resistance to the spread of a contagious disease within a population that results if a sufficiently high proportion of individuals are immune to the disease, especially through vaccination |
| Systematic literature | review articles are considered original work because they are conducted using rigorous methodological approaches |
| Meta-Analysis (MA) | The statistical synthesis of the data from separate but similar studies, leading to a quantitative summary of the pooled results |
| Database Bias | No single database is likely to contain all published studies on a given subject. |
| Publication Bias | selective publication of articles that show positive treatment of effects and statistical significance |
| Randomized Controlled Trials (RCT): | – RCT are considered to be more rigorous than observational studies |
| Heterogeneity | The variability among studies in a systematic review |
| Publication bias | is a type of bias that occurs in published academic research |
| funnel plot | is a graph designed to check for the existence of publication bias |
| genetic epidemiology | Identification of genetic markers related to diseases |
| Molecular epidemiology | is a branch of epidemiology developed by merging molecular biology into epidemiological research |
| Phylogeny | the history of the evolution of a species or group, especially in reference to lines of descent and relationships among broad groups of organisms |
| Genetic association studies | assess the overrepresentation of specific gene variants in persons expressing the phenotype trait of interest |
| genome wide association studies (GWASs) | A genome-wide association study (abbreviated GWAS) is a research approach used to identify genomic variants that are statistically associated with a risk for a disease or a particular trait. |
| Exposure misclassification: | It is in part related to the challenge of assessing exposure during critical windows of exposure |
| Susceptibility: | The effects of specific exposures on phenotypic traits depend on susceptibility of individuals, which is in part genetically determined. Gene–environment interactions, require very large sample sizes. |
| Sample size: | it requires large and long-running cohorts to accumulate sufficient incident diagnoses that allow studying exposure effects in a prospective manner |
| Low exposures and relative risks: | The current focus of chronic disease and environmental epidemiology is on low levels of exposures each associated with a small relative risk increase |
| exposome | defined as the totality of exposures to which a human organism is exposed from the time of conception to death |
| PM/ particulate matter | the term for a mixture of solid particles and liquid droplets found in the air |
| environmental epidemiology | We study the association of an exposure and an (health) outcome |
| Exposure assessment | – Population-wide – Multi-exposures – Measurement error – Unknown exposure period of most health relevance |
| Outcomes definition | • Small relative risks in the presence of many confounders/mediators • Causality issues • Many underlying biological mechanics driven by oxidative stress |
| Acute effects | are those occurring within minutes, hours or few days |
| Chronic effects | may occur after years of exposure to relatively low levels |
| Induction period | is the time between exposure and initiation of disease |
| Latent period | is the time period between initiation of disease and clinical manifestation of disease or diagnosis |
| Biomarkers | A biomarker is a variable measuring a substance or mechanism in biological material |
Created by:
elenatz
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