Surveillance and Epidemiological Investigation (22 questions) Flashcards

Question

Attributable risk percent

Answer 1

gives the proportion of cases attributable (and avoidable) to this exposure in relation to all cases. calculate in order to figure out diseases that could be prevented by eliminating exposure in the entire study population (relative risk - 1) / relative risk

Answer 2

the power of the study. Power is affected by size of the effect and the size of study/sample size

Answer 3

birds, esp domestic poultry (chicken, turkeys, geese, ducks)

Answer 4

causation is essential concept in epidemiology. The web of causation refers to the interrelationship of multiple factors that contribute to the occurrence of disease indirect and direct causes of disease may form a complex network of events that determines the level of disease in a community

Answer 5

will increase the PPV (positive predictive value) and decrease the NPV (neg predictive value)

Answer 6

Difference in rate of a condition between an exposed pop and unexposed AR= IE - IU IE (Incidence of exposed) = # exposed who get disease / total # exposed IU (unexposed) = # unexposed with get disease / total # unexposed

Answer 7

probability of having a particular risk factor if a condition/disease is present divided by the probability of having the condition/disease is not present ad / bc 2x2 table: A| B ----- C| D

Answer 8

The alternative hypothesis (reject null and accept alternative hypothesis) Rationale: The p value is the probability of obtaining the observed sample results (or a more extreme result) when the null hypothesis is actually true. If the p value is small (≤ the significance level), it suggests that the observed data is inconsistent with the assumption that the null hypothesis is true, and thus that hypothesis must be rejected and the alternative hypothesis accepted as true.

Answer 9

Used in cohort studies % Risk of outcome in group WITH exposure/ risk of outcome of group WITHOUT exposure Incidence proportion= cases/ exposed or unexposed. Use this to calculate % of With and without exposure

Answer 10

rejecting the null hypothesis when it is true p value = probability of type 1 error A Type I error occurs when one rejects the null hypothesis (H0) when it is true. This is also called a false-positive result (as we incorrectly conclude that the research hypothesis is true when in fact it is not). The p value or calculated probability is the estimated probability of rejecting the null hypothesis of a study question when that hypothesis is true.

Answer 11

failing to reject a false null hypothesis

Answer 12

BSI and # device days Need device days, NOT # central line The number of patients who had bloodstream infections identified and the number of device days for the time period X/Y x K #BSI/device days x K

Answer 13

occur within 30 days-only skin or subcutaneous tissue. In addition, **one of the following must be met:** *Purulent drainage, *Organisms isolated from an aseptically obtained culture of fluid or tissue And patient has at least **one** of the following: °° Purulent drainage from the superficial incision °° Organisms isolated from an aseptically obtained culture of fluid or tissue from the superficial incision °° Superficial incision that is deliberately opened by a surgeon, attending physician, or other designee* And patient **one signs or symptoms**: pain or tenderness, localized swelling, redness, or heat. A culture negative finding does not meet this criterion. °° Diagnosis of superficial incisional SSI by the surgeon or attending physician or other designee

Answer 14

-To evaluate the effect of a variable on outcomes -To calculate an odds ratio or relative risk - If each cell of the table is greater than 5 Chi-square tests (χ2) can be used to test the association between two classifications of a set of counts or frequencies (discrete data). This data are commonly displayed as a contingency table or 2 x 2 table where rows represent one variable and columns represent the other. The null hypothesis is that there is no association between the two variables. Row and column totals (marginal totals) are used to predict what count would be expected for each cell if the null hypothesis were true. A test statistic is calculated from the observed and expected frequencies. The larger the test statistic (for given degrees of freedom) the more likely there is to be a statistically significant association between the two variables. Chi-square tests are used for medium to large samples (see Figure 4-1). The Fisher’s exact test is used in place of the χ2 when the sample size number is less than 20 or any one cell in the table is less than 5. Figure 4-1. Formula for chi-square χ2 = (0-E)2 / E Where: O = observed frequency E = expected frequency

Answer 15

Fisher’s exact Rationale: Fisher’s exact test is a statistical significance test used in the analysis of contingency tables. Although in practice it is employed when sample sizes are small, it is valid for all sample sizes.

Answer 16

Standard deviation

Answer 17

* State the research question * Specify the null and alternative hypotheses * Calculate test statistic * Compute probability of test statistic or rejection region * State conclusions Analysis and dealing with outliers is an important component of statistical analysis. Sometimes careful analysis of outliers, their removal, or weighting down can change the conclusions considerably. Outliers should be investigated to determine the optimal method of analysis.

Answer 18

Relatively flat Rationale: Two terms are used to describe the shape of a frequency distribution: “skewness” and “kurtosis.” Kurtosis refers to how flat or peaked a curve is (see Figure 4-3): * Leptokurtic is the more peaked curve. (+) positive numbers * Mesokurtic is a typical bell-shaped curve or normal distribution. A value of 0 * Platykurtic is the flatter curve (-) negative numbers.

Answer 19

Confounding variable Rationale: A confounding variable is a variable that has an important confounding effect on the result but is not among the variables being studied. It can suggest a false relationship between variables, or it can hide a relationship that exists.

Answer 20

useful for showing 2 sets of data on a graph, uses connecting lines and data points

Answer 21

Human herpesvirus 8

Answer 22

The positive predictive value of a diagnostic test is lowered Sensitivity and specificity are independent of prevalence of disease. PPV and NPV are disease prevalence dependent. Generally a higher prevalence will increase the PPV and decrease the NPV.

Answer 23

Noroviruses (NoVs) are the most common cause of epidemic gastroenteritis worldwide and the leading cause of foodborne outbreaks in the United States. Severe disease associated with NoV occurs most frequently among older adults, young children, and immunocompromised patients. NoV outbreaks occur year round, but activity increases in the United States duringthe winter months; 80 percent of reported outbreaks occur during Novem ber–April. Most NoV outbreaks are attributed to genotype GII.4, which evolves rapidly over time.

Answer 24

exposed to same source over brief period of time (ex: meal or event)- transmission occurs through a vehicle (same person) rather than person-to- person

Answer 25

*The incidence of disease is higher in those who are exposed to the factor *Evidence that the independent and dependent variables are related *The association has been observed in numerous studies Rationale: The criteria for causality are known as Hill’s criteria and use epidemiological methods to determine whether a factor is causal for a given disease. Hill’s criteria for causation are as follows: 1. Strength of association: The incidence of disease should be higher in those who are exposed to the factor under consideration than in those who are not exposed; that is, the stronger the association between an exposure and a disease, the more likely the exposure is to be causal. For example, lung cancer is common in those who smoke. 2. Consistency: This means that the association should be observed in numerous studies, preferably by different researchers using different research methodologies. 3. Specificity: Refers to an association between one factor and one disease, and this association is more likely to be causal. This criterion also refers to the extent to which the occurrence of one factor can be used to predict the occurrence of another (disease). In reality, such a one-to-one relationship is rare due to the multifactorial causes of most diseases and because, sometimes, the same factor(s) can cause more than one disease. 4. Temporality: This must also be addressed when determining cause of disease. Essentially, exposure to the hypothesized causal factor must precede the onset of disease. 5. Biological gradient: The biological gradient is a dose-response relationship between increased exposure to a factor and increased likelihood of disease. For example, the longer one smokes, the more likely one is to develop lung cancer. If the association demonstrates a biological gradient between the factor (exposure) and effect (disease), the relationship is more likely to be causal. 6. Plausibility: The association in question should also be biologically plausible in light of current knowledge. This criterion may be the most elusive and variable of the nine. Because biological knowledge is ever expanding, lack of biological plausibility does not necessarily disprove a theoretical association. 7. Coherence: There should be coherence between known information about the biological spectrum of the disease and the associated factor, that is, the association should be in accordance with other facts known about the natural history of the disease. 8. Analogy: Associations derived from experiments add considerable weight to evidence supporting causal associations. These experiments can be animal model studies or clinical trials; however, although animal models may be helpful, many diseases do not manifest the same way in animals and humans. 9. Finally, if similar associations have been shown to be causal, by analogy the association is more likely to be causal. Determining causality may also help to determine at which points the natural history of a disease may be interrupted, so that prevention and control efforts are effective. It can also add information on the natural history of a disease.

Answer 26

Koch’s postulates consist of four points: 1. The organism must always be found with the disease, in accordance with the clinical stage observed. 2. The organism must then be grown in pure culture from a diseased host. 3. The same disease must be reproduced when a pure culture of the organism is inoculated into a healthy susceptible host. 4. The organism must then be recovered from the experimentally infected host. A causal association should not be confused with causality, which requires a number of conditions to be met, one of which is the presence of causal associations