There are two principal types of epidemiology, analytic epidemiology and descriptive epidemiology. Descriptive epidemiology describes the amount and distribution of disease, which may suggest possible causes. These causes can then be confirmed or corrected through more advanced methods of research.
Assuming the two brothers lived in the same household, the environment and the agent or infectious organism are the same. The only difference could be between the two brothers themselves and their genetic inheritance.
The epidemiological triangle model of agent-host-environment is very useful especially with single-cause infectious diseases. However, with the multiple factors involved in chronic diseases, the wheel model is more useful in analyzing and identifying the multiple variables.
Identifying risk factors is critical to creating or discovering specific prevention and intervention approaches that reduce chronic disease morbidity and mortality. Because some risk factors cannot be avoided, knowing other risk factors involved allows for more possibilities of preventing the problem.
Although it is a more recently created model, the web of causation model is more useful because it illustrates the complexity of relationships among causable variables. It is not easier to understand and use as it has more variables than the three (agent, host, and environment) in the epidemiological model.
The researchers concluded that ecosocial or contextual conditions strongly enhance sexually transmitted disease risk by increasing sexual risk behaviors and likelihood of exposure to infection.
No conclusions can really be drawn from just knowing a number. Only by converting that count to a rate and then comparing the rate with the previous rate, or with the rate in the broader environment or a similar community nearby, can any conclusions be drawn as to whether there is a problem or intervention needed.
As only new cases were being reported to the health department, the media could only report the ongoing incidence rate, that is, the number of new cases reported each day.
The incidence rate of new cases would be most useful for detecting short-term acute disease changes, as the swine flu duration is usually relatively short.
Rates are calculated by the number of people with the problem over the number exposed to the problem. In this case, 650 persons out of the 1000 at the banquet complained of illness. Although this rate could be presented as an attack rate of 65%, 6.5% is incorrect.
Diabetes would have the higher prevalence rate because it is a long-term chronic condition that typically does not decrease. Although flu might have a higher incidence rate of new cases, because flu is typically of short duration, the prevalence rate would remain low. Flu is contagious, which could increase the incidence rate but not the prevalence rate.
The text states that data on many conditions are not available because surveillance is not widely conducted. In other words, there is no responsibility to report cases of most diseases, including gonorrhea. Further morbidity rates are subject to underreporting. Information is only available related to conditions where care providers are required to report that specific condition or where those affected die and mortality data are available.
Although pregnancy is not specifically addressed, the text stresses that only those susceptible to a particular condition should be considered in the denominator. In the case of pregnancy, only women of childbearing age are susceptible.
Attributable risk is determined by subtracting the rate of disease among nonexposed individuals (such as athletes) from the rate of disease among those exposed (the individuals with a sedentary lifestyle).
A risk factor of less than one means the factor is actually protective, so the inexpensive lotion is helpful in preventing skin sores. A risk factor of more than one means the factor increases risk, so using the expensive lotion increases the probability of getting a skin lesion.
The natural history of disease model explains disease from prepathogenesis through resolution of the disease process.
Screening, because it may result in early diagnosis and treatment, is secondary prevention.
There is no point in doing a screening if there is no treatment or if there is a known risk of social stigma and discrimination if it becomes known that the person has the disease. Discussion and disagreement continue as to whether genetic information should be used in family planning. However, it is extremely useful to the individuals concerned and society if screening can lead to early diagnosis and successful control of the disease process.
Not all positive screening results are confirmed with further diagnostic testing. The positive predictive value of a test (proportion of true positive results relative to all positive test results) is usually known for any screening test. Although one could argue that the test could be wrong, it is more therapeutic—because you want people to attend future screenings—to emphasize that screening is only suggestive than to say the screening test is inaccurate.
The positive predictive value is affected by what proportion of the tested population has the problem. To increase the positive predictive value, screen populations most at risk for the problem.
Effectiveness of Healthy People 2020 depends on the availability of reliable baseline and continuing data to characterize health problems and evaluate goal achievement. Surveillance is crucial.
By definition a cross-sectional study examines relationships between potential causal factors and disease at a specific time.
When a study looks at individuals with a particular condition in comparison with those who do not have the disease, based on their exposures to various life situations, it is a retrospective study; that is, the study requires participants to look back at previous experiences.
Prospective studies monitor a group of individuals to determine if and when disease occurs.
The most advantageous research design, because it obtains more reliable information and can more easily establish a stronger temporal relationship between presumed causal factors and their effects, is a longitudinal cohort prospective study.
Because longitudinal cohort or incidence studies are costly in terms of resources and staff and often lose subjects over time, a retrospective study may be used because it is faster and less demanding of resources.
Experimental design is used to test treatment and prevention strategies. Subjects are randomly assigned to the experimental group to obtain the new drug while the control group receives a placebo or alternative. The changes in blood cholesterol level would then be measured.
Nutritional deficiencies are included under agent factors. Although too much of an agent can cause disease (such as obesity related to diabetes), so can too little of an agent.
As treatment was knowingly withheld over many years resulting in incredible harm to the subjects and their families, public outrage over unethical, racist, and discriminatory behavior of the researchers continues today.
The person-place-time model suggests epidemiologists examine demographic characteristics of the community (person characteristics), geographic or environmental factors (place), and common time factors (time—or when the disease struck).
The epidemiological triangle includes the agent (pathogen), host (people who are susceptible and become ill), and environment (the geographic area where people became ill). These three areas allow for an explanation of disease.
The ecosocial approach challenges both the individually focused risk factor approach and molecular epidemiology (sequencing of genes to improve individual susceptibility), as it emphasizes the role of macro-level socioenvironmental factors, especially complex political and economic forces in health and illness.
There are six criteria for assuming possible causation including strength of the association, dose-response relationship, temporarily correct relationship, biological plausibility, consistency among studies, and specificity. Only the “easy-to-understand,” consistent research studies and the increased dose leading to increased illness are consistent with those six criteria.
Such a test may have lower specificity, so some persons with the disease are told they are disease free and hence do not receive care.
The problem with very sensitive tests is that the test picks up almost all people with the disease but also many others who do not have the disease. These “false positives” result in persons needing follow-up diagnostic tests. Additional time, effort, and expense, as well as worry, result until the negative test results are obtained. There is no problem with persons receiving true negative test results and celebrating that knowledge or with persons having their condition correctly diagnosed and treated.