Health 3011 Midterm
Data distributions
A distribution that has a central location to the left and a tail off to the right is said to be positively skewed or skewed to the right. In Figure 2.6, distribution A is skewed to the right. A distribution that has a central location to the right and a tail to the left is said to be negatively skewed or skewed to the left.
Summarizing data
Data that are normally distributed are usually summarized with the arithmetic mean and standard deviation. Data that are skewed or have a few extreme values are usually summarized with the median and range, or with the median and interquartile range. Data that follow a logarithmic scale and data that span several orders of magnitude are usually summarized with the geometric mean.
Prevalence
Prevalence, sometimes referred to as prevalence rate, is the proportion of persons in a population who have a particular disease or attribute at a specified point in time or over a specified period of time. Prevalence differs from incidence in that prevalence includes all cases, both new and preexisting, in the population at the specified time, whereas incidence is limited to new cases only. All new and pre-existing cases during a given time period ----------------------------------------------- *10^n Population during the same time period EXAMPLE: Calculating Prevalence In a survey of 1,150 women who gave birth in Maine in 2000, a total of 468 reported taking a multivitamin at least 4 times a week during the month before becoming pregnant. Calculate the prevalence of frequent multivitamin use in this group. Numerator = 468 multivitamin users Denominator = 1,150 women Prevalence = (468 / 1,150) x 100 = 0.407 x 100 = 40.7%
functions of epidemiology: public health surveillance
Public health surveillance is the ongoing, systematic collection, analysis, interpretation, and dissemination of health data to help guide public health decision making and action. Surveillance is equivalent to monitoring the pulse of the community. The purpose of public health surveillance, which is sometimes called "information for action," is to portray the ongoing patterns of disease occurrence and disease potential so that investigation, control, and prevention measures can be applied efficiently and effectively. This is accomplished through the systematic collection and evaluation of morbidity and mortality reports and other relevant health information, and the dissemination of these data and their interpretation to those involved in disease control and public health decision making.
Chain of Infection
RESERVOIRS: The reservoir of an infectious agent is the habitat in which the agent normally lives, grows, and multiplies. Reservoirs include humans, animals, and the environment. The reservoir may or may not be the source from which an agent is transferred to a host. For example, the reservoir of Clostridium botulinum is soil. -Human reservoirs: Many common infectious diseases have human reservoirs. Diseases that are transmitted from person to person without intermediaries. -Animal reservoirs: Humans are also subject to diseases that have animal reservoirs. Many of these diseases are transmitted from animal to animal, with humans as incidental hosts. Zoonosis -Environmental reservoirs: Plants, soil, and water in the environment are also reservoirs for some infectious agents. Many fungal agents, such as those that cause histoplasmosis, live and multiply in the soil. PORTAL OF EXIT: Portal of exit is the path by which a pathogen leaves its host. The portal of exit usually corresponds to the site where the pathogen is localized. Examples: urine, blood, feces MODES OF TRANSMISSION: An infectious agent may be transmitted from its natural reservoir to a susceptible host in different ways. There are different classifications for modes of transmission. Here is one classification: •Direct: Direct contact, Droplet spread •Indirect: Airborne (bodily fluids), Vehicleborne (food, water, biologic products), Vectorborne (insect) PORTAL OF ENTRY: The portal of entry refers to the manner in which a pathogen enters a susceptible host. The portal of entry must provide access to tissues in which the pathogen can multiply or a toxin can act. HOST: The final link in the chain of infection is a susceptible host. Susceptibility of a host depends on genetic or constitutional factors, specific immunity, and nonspecific factors that affect an individual's ability to resist infection or to limit pathogenicity.
functions of epidemiology: analytic studies
Surveillance and field investigations are usually sufficient to identify causes, modes of transmission, and appropriate control and prevention measures. But sometimes analytic studies employing more rigorous methods are needed. Often the methods are used in combination — with surveillance and field investigations providing clues or hypotheses about causes and modes of transmission, and analytic studies evaluating the credibility of those hypotheses. Clusters or outbreaks of disease frequently are investigated initially with descriptive epidemiology. Epidemiologists must be skilled in all aspects of such studies, including design, conduct, analysis, interpretation, and communication of findings. •Design includes determining the appropriate research strategy and study design, writing justifications and protocols, calculating sample sizes, deciding on criteria for subject selection (e.g., developing case definitions), choosing an appropriate comparison group, and designing questionnaires. •Conduct involves securing appropriate clearances and approvals, adhering to appropriate ethical principles, abstracting records, tracking down and interviewing subjects, collecting and handling specimens, and managing the data. •Analysis begins with describing the characteristics of the subjects. It progresses to calculation of rates, creation of comparative tables (e.g., two-by-two tables), and computation of measures of association (e.g., risk ratios or odds ratios), tests of significance (e.g., chi-square test), confidence intervals, and the like. Many epidemiologic studies require more advanced analytic techniques such as stratified analysis, regression, and modeling. •Finally, interpretation involves putting the study findings into perspective, identifying the key take-home messages, and making sound recommendations. Doing so requires that the epidemiologist be knowledgeable about the subject matter and the strengths a nd weaknesses of the study.
Descriptive Epidemiology
TIME: The occurrence of disease changes over time. Some of these changes occur regularly, while others are unpredictable. Two diseases that occur during the same season each year include influenza (winter) and West Nile virus infection (August-September). In contrast, diseases such as hepatitis B and salmonellosis can occur at any time. Time data are usually displayed with a two-dimensional graph. The vertical or y-axis usually shows the number or rate of cases; the horizontal or x-axis shows the time periods such as years, months, or days. The number or rate of cases is plotted over time. Graphs of disease occurrence over time are usually plotted as line graphs or histograms. PLACE: Describing the occurrence of disease by place provides insight into the geographic extent of the problem and its geographic variation. Characterization by place refers not only to place of residence but to any geographic location relevant to disease occurrence. Such locations include place of diagnosis or report, birthplace, site of employment, school district, hospital unit, or recent travel destinations. The unit may be as large as a continent or country or as small as a street address, hospital wing, or operating room. Sometimes place refers not to a specific location at all but to a place category such as urban or rural, domestic or foreign, and institutional or noninstitutional. PERSON: Because personal characteristics may affect illness, organization and analysis of data by "person" may use inherent characteristics of people (for example, age, sex, race), biologic characteristics (immune status), acquired characteristics (marital status), activities (occupation, leisure activities, use of medications/tobacco/drugs), or the conditions under which they live (socioeconomic status, access to medical care). Age and sex are included in almost all data sets and are the two most commonly analyzed "person" characteristics.
History of epidemiology
-Circa 400 B.C.: Epidemiology's roots are nearly 2500 years old. Hippocrates attempted to explain disease occurrence from a rational rather than a supernatural viewpoint. In his essay entitled "On Airs, Waters, and Places," Hippocrates suggested that environmental and host factors such as behaviors might influence the development of disease. -1662: Another early contributor to epidemiology was John Graunt, a London haberdasher and councilman who published a landmark analysis of mortality data in 1662. This publication was the first to quantify patterns of birth, death, and disease occurrence, noting disparities between males and females, high infant mortality, urban/rural differences, and seasonal variations. -1800: William Farr built upon Graunt's work by systematically collecting and analyzing Britain's mortality statistics. Farr, considered the father of modern vital statistics and surveillance, developed many of the basic practices used today in vital statistics and disease classification. He concentrated his efforts on collecting vital statistics, assembling and evaluating those data, and reporting to responsible health authorities and the general public. -1854: In the mid-1800s, an anesthesiologist named John Snow was conducting a series of investigations in London that warrant his being considered the "father of field epidemiology." Twenty years before the development of the microscope, Snow conducted studies of cholera outbreaks both to discover the cause of disease and to prevent its recurrence. Snow conducted one of his now famous studies in 1854 when an epidemic of cholera erupted in the Golden Square of London. He Introduction to began his investigation by determining where in this area persons with cholera lived and worked. He marked each residence on a map of the area (spot graph). To confirm that the Broad Street pump was the source of the epidemic, Snow gathered information on where persons with cholera had obtained their water. Consumption of water from the Broad Street pump was the one common factor among the cholera patients. After Snow presented his findings to municipal officials, the handle of the pump was removed and the outbreak ended. -19th and 20th centuries: In the mid- and late-1800s, epidemiological methods began to be applied in the investigation of disease occurrence. At that time, most investigators focused on acute infectious diseases. In the 1930s and 1940s, epidemiologists extended their methods to noninfectious diseases.
Variable types
-Discrete variables: have values that are integers (e.g., number of ill persons who were exposed to a risk factor). -Continuous variables: can have any value in a range (e.g., amount of time between meal being served and onset of gastro-intestinal symptoms; infant mortality rate). •A nominal-scale variable is one whose values are categories without any numerical ranking, such as county of residence. In epidemiology, nominal variables with only two categories are very common: alive or dead, ill or well, vaccinated or unvaccinated, or did or did not eat the potato salad. A nominal variable with two mutually exclusive categories is sometimes called a dichotomous variable. •An ordinal-scale variable has values that can be ranked but are not necessarily evenly spaced, such as stage of cancer. Examples of ordinal variables are "low, medium, high" or perhaps categories of other variables (e.g., age ranges). •An interval-scale variable is measured on a scale of equally spaced units, but without a true zero point, such as date of birth. •A ratio-scale variable is an interval variable with a true zero point, such as height in centimeters or duration of illness.
Frequency distribution
A frequency distribution displays the values a variable can take and the number of persons or records with each value. For example, suppose you have data from a study of women with ovarian cancer and wish to look at parity, that is, the number of times each woman has given birth. To construct a frequency distribution that displays these data: •First, list all the values that the variable parity can take, from the lowest possible value to the highest. •Then, for each value, record the number of women who had that number of births (twins and other multiple-birth pregnancies count only once).
Measures of Association
A measure of association quantifies the relationship between exposure and disease among the two groups. Exposure is used loosely to mean not only exposure to foods, mosquitoes, a partner with a sexually transmissible disease, or a toxic waste dump, but also inherent characteristics of persons (for example, age, race, sex), biologic characteristics (immune status), acquired characteristics (marital status), activities (occupation, leisure activities), or conditions under which they live (socioeconomic status or access to medical care). The measures of association described in the following section compare disease occurrence among one group with disease occurrence in another group. Examples of measures of association include risk ratio (relative risk), rate ratio, odds ratio, and proportionate mortality ratio.
Frequency Measures
A measure of central location provides a single value that summarizes an entire distribution of data. In contrast, a frequency measure characterizes only part of the distribution. Frequency measures compare one part of the distribution to another part of the distribution, or to the entire distribution. Common frequency measures are ratios, proportions, and rates. All three frequency measures have the same basic form: (N/D)*10^n
Proportions
A proportion is the comparison of a part to the whole. It is a type of ratio in which the numerator is included in the denominator. You might use a proportion to describe what fraction of clinic patients tested positive for HIV, or what percentage of the population is younger than 25 years of age. A proportion may be expressed as a decimal, a fraction, or a percentage. Method for calculating a proportion: Number of persons or events with a particular characteristic ----------------------------------------------- *10^n Total number of persons or events, of which the numerator is a subset For a proportion, 10^n is usually 100 (or n=2) and is often expressed as a percentage.
Ratios
A ratio is the relative magnitude of two quantities or a comparison of any two values. It is calculated by dividing one interval- or ratio-scale variable by the other. The numerator and denominator need not be related. Therefore, one could compare apples with oranges or apples with number of physician visits. Method for calculating a ratio: Number or rate of events, items, persons, etc. in one group --------------------------------------------------- Number or rate of events, items, persons, etc. in another group After the numerator is divided by the denominator, the result is often expressed as the result "to one" or written as the result ":1."
Risk Ratio
A risk ratio (RR), also called relative risk, compares the risk of a health event (disease, injury, risk factor, or death) among one group with the risk among another group. It does so by dividing the risk (incidence proportion, attack rate) in group 1 by the risk (incidence proportion, attack rate) in group 2 . The two groups are typically differentiated by such demographic factors as sex (e.g., males versus females) or by exposure to a suspected risk factor (e.g., did or did not eat potato salad). Often, the group of primary interest is labeled the exposed group, and the comparison group is labeled the unexposed group. Risk of disease (incidence proportion, attack rate) in group of primary interest -------------------------------------------------------------- Risk of disease (incidence proportion, attack rate) in comparison group A risk ratio of 1.0 indicates identical risk among the two groups. A risk ratio greater than 1.0 indicates an increased risk for the group in the numerator, usually the exposed group. A risk ratio less than 1.0 indicates a decreased risk for the exposed group, indicating that perhaps exposure actually protects against disease occurrence.
Measures of spread
A second property of frequency distribution is spread (also called variation or dispersion). Spread refers to the distribution out from a central value. Two measures of spread commonly used in epidemiology are range and standard deviation. For most distributions seen in epidemiology, the spread of a frequency distribution is independent of its central location. Figure 2.4 illustrates three theoretical frequency distributions that have the same central location but different amounts of spread.
Attack Rate
An alternative and more accurate phrase for attack rate is incidence proportion. The term attack rate is often used as a synonym for risk. It is the risk of getting the disease during a specified period, such as the duration of an outbreak. A variety of attack rates can be calculated. -Overall attack rate is the total number of new cases divided by the total population. -A food-specific attack rate is the number of persons who ate a specified food and became ill divided by the total number of persons who ate that food, as illustrated in the previous potato salad example. -A secondary attack rate is sometimes calculated to document the difference between community transmission of illness versus transmission of illness in a household, barracks, or other closed population. Number of cases among contacts of primary cases ---------------------------------------- *10^n Total number of contacts
Epidemiological Approach
As with all scientific endeavors, the practice of epidemiology relies on a systematic approach. In very simple terms, the epidemiologist: •Counts cases or health events, and describes them in terms of time, place, and person; •Divides the number of cases by an appropriate denominator to calculate rates; and •Compares these rates over time or for different groups of people. Defining a case: Before counting cases, the epidemiologist must decide what to count, that is, what to call a case. For that, the epidemiologist uses a case definition. A case definition is a set of standard criteria for classifying whether a person has a particular disease, syndrome, or other health condition.
Uses and major tasks of epidemiology
Assessing the community's health: Public health officials responsible for policy development, implementation, and evaluation use epidemiologic information as a factual framework for decision making. To assess the health of a population or community, relevant sources of data must be identified and analyzed by person, place, and time (descriptive epidemiology). More detailed data may need to be collected and analyzed to determine whether health services are available, accessible, effective, and efficient. For example, public health officials used epidemiologic data and methods to identify baselines, to set health goals for the nation in 2000 and 2010, and to monitor progress toward these goals. Making individual decisions: Many individuals may not realize that they use epidemiologic information to make daily decisions affecting their health. When persons decide to quit smoking, climb the stairs rather than wait for an elevator, eat a salad rather than a cheeseburger with fries for lunch, or use a condom, they may be influenced, consciously or unconsciously, by epidemiologists' assessment of risk. Completing the clinical picture: When investigating a disease outbreak, epidemiologists rely on health-care providers and laboratorians to establish the proper diagnosis of individual patients. But epidemiologists also contribute to physicians' understanding of the clinical picture and natural history of disease. Searching for causes: Much epidemiologic research is devoted to searching for causal factors that influence one's risk of disease. Ideally, the goal is to identify a cause so that appropriate public health action might be taken. One can argue that epidemiology can never prove a causal relationship between an exposure and a disease, since much of epidemiology is based on ecologic reasoning. Nevertheless, epidemiology often provides enough information to support effective action.
functions of epidemiology: linkages
During an investigation an epidemiologist usually participates as either a member or the leader of a multidisciplinary team. To promote current and future collaboration, the epidemiologists need to maintain relationships with staff of other agencies and institutions. Mechanisms for sustaining such linkages include official memoranda of understanding, sharing of published or on-line information for public health audiences and outside partners, and informal networking that takes place at professional meetings.
Analytical Epidemiology
Epidemiologists can use descriptive epidemiology to generate hypotheses, but only rarely to test those hypotheses. For that, epidemiologists must turn to analytic epidemiology. When investigators find that persons with a particular characteristic are more likely than those without the characteristic to contract a disease, the characteristic is said to be associated with the disease. The characteristic may be a: •Demographic factor such as age, race, or sex; •Constitutional factor such as blood group or immune status; •Behavior or act such as smoking or having eaten salsa; or •Circumstance such as living near a toxic waste site.
Definition of epidemiology
Epidemiology is 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.
functions of epidemiology: evaluation
Evaluation is the process of determining the relevance, effectiveness, efficiency, and impact of activities with respect to established goals. •Effectiveness refers to the ability of a program to produce the intended or expected results in the field; effectiveness differs from efficacy, which is the ability to produce results under ideal conditions. •Efficiency refers to the ability of the program to produce the intended results with a minimum expenditure of time and resources. The evaluation itself may focus on plans (formative evaluation), operations (process evaluation), impact (summative evaluation), or outcomes — or any combination of these.
Types of epidemiology studies: Experimental
In an experimental study, the investigator determines through a controlled process the exposure for each individual (clinical trial) or community (community trial), and then tracks the individuals or communities over time to detect the effects of the exposure. For example, in a clinical trial of a new vaccine, the investigator may randomly assign some of the participants to receive the new vaccine, while others receive a placebo shot. The investigator then tracks all participants, observes who gets the disease that the new vaccine is intended to prevent, and compares the two groups (new vaccine vs. placebo) to see whether the vaccine group has a lower rate of disease.
Types of epidemiology studies: Observational
In an observational study, the epidemiologist simply observes the exposure and disease status of each study participant. John Snow's studies of cholera in London we re observational studies. The two most common types of observational studies are cohort studies and case-control studies; a third type is cross-sectional studies. -Cohort study: A cohort study is similar in concept to the experimental study. In a cohort study the epidemiologist records whether each study participant is exposed or not, and then tracks the participants to see if they develop the disease of interest. Note that this differs from an experimental study because, in a cohort study, the investigator observes rather than determines the participants' exposure status. After a period of time, the investigator compares the disease rate in the exposed group with the disease rate in the unexposed group. The unexposed group serves as the comparison group, providing an estimate of the baseline or expected amount of disease occurrence in the community. If the disease rate is substantively different in the exposed group compared to the unexposed group, the exposure is said to be associated with illness. -Case-control study: In a case-control study, investigators start by enrolling a group of people with disease (at CDC such persons are called case-patients rather than cases, because case refers to occurrence of disease, not a person). As a comparison group, investigator then enrolls a group of people without disease (controls). Investigator s then compare previous exposures between the two groups. The control group provides an estimate of the baseline or expected amount of exposure in that population. If the amount of exposure among the case group is substantially higher than the amount you would expect based on the control group, then illness is said to be associated with that exposure. -Cross-sectional study: In this third type of observational study, a sample of persons from a population is enrolled and their exposures and health outcomes are measured simultaneously. The cross-sectional study tends to asse ss the presence (prevalence) of the health outcome at that point of time without regard to duration. For example, in a cross-sectional study of diabetes, some of the enrollees with diabetes may have lived with their diabetes for many years, while others may have been recently diagnosed. From an analytic viewpoint the cross-sectional study is weaker than either a cohort or a case-control study because a cross-sectional study usually cannot disentangle risk factors for occurrence of disease (incidence) from risk factors for survival with the disease.
Rates
In epidemiology, a rate is a measure of the frequency with which an event occurs in a defined population over a specified period of time. Because rates put disease frequency in the perspective of the size of the population, rates are particularly useful for comparing disease frequency in different locations, at different times, or among different groups of persons with potentially different sized populations; that is, a rate is a measure of risk.
Incidence
Incidence refers to the occurrence of new cases of disease or injury in a population over a specified period of time. Although some epidemiologists use incidence to mean the number of new cases in a community, others use incidence to mean the number of new cases per unit of population. EXAMPLES: Calculating Incidence Proportion (Risk) In the study of diabetics, 100 of the 189 diabetic men died during the 13-year follow-up period. Calculate the risk of death for these men. Numerator = 100 deaths among the diabetic men Denominator = 189 diabetic men 10^n= 10^2= 100 Risk = (100 / 189) x 100 = 52.9%
functions of epidemiology: policy development
Indeed, epidemiologists who understand a problem and the population in which it occurs are often in a uniquely qualified position to recommend appropriate interventions. As a result, epidemiologists working in public health regularly provide input, testimony, and recommendations regarding disease control strategies, reportable disease regulations, and health-care policy.
Epidemic Disease Occurrence
Level of disease: The amount of a particular disease that is usually present in a community is referred to as the baseline or endemic level of the disease. This level is not necessarily the desired level, which may in fact be zero, but rather is the observed level. In the absence of intervention and assuming that the level is not high enough to deplete the pool of susceptible persons, the disease may continue to occur at this level indefinitely. Thus, the baseline level is often regarded as the expected level of the disease. While some diseases are so rare in a given population that a single case warrants an epidemiologic investigation (e.g., rabies, plague, polio), other diseases occur more commonly so that only deviations from the norm warrant investigation. -Sporadic: refers to a disease that occurs infrequently and irregularly. -Endemic: refers to the constant presence and/or usual prevalence of a disease or infectious agent in a population within a geographic area. -Hyperendemic: refers to persistent, high levels of disease occurrence. Occasionally, the amount of disease in a community rises above the expected level. -Epidemic: refers to an increase, often sudden, in the number of cases of a disease above what is normally expected in that population in that area. Occur when an agent and susceptible hosts are present in adequate numbers, and the agent can be effectively conveyed from a source to the susceptible hosts. -Outbreak: carries the same definition of epidemic, but is often used for a more limited geographic area. -Cluster: refers to an aggregation of cases grouped in place and time that are suspected to be < than the # expected, even though the expected number may not be known. -Pandemic: refers to an epidemic that has spread over several countries or continents, usually affecting a large number of people.
Choosing the right measures of central tendency and spread
Measures of central location are single values that summarize the observed values of a distribution. The mode provides the most common value, the median provides the central value, the arithmetic mean provides the average value, the midrange provides the midpoint value, and the geometric mean provides the logarithmic average. The mode and median are useful as descriptive measures. Because epidemiologic data tend not to be normally distributed (incubation periods, doses, ages of patients), the median is often preferred. The geometric mean is used most commonly with laboratory data, particularly dilution titers or assays and environmental sampling data. The arithmetic mean uses all the data, which makes it sensitive to outliers. Although the geometric mean also uses all the data, it is not as sensitive to outliers as the arithmetic mean. The midrange, which is based on the minimum and maximum values, is more sensitive to outliers than any other measures.
Natural History of Disease
Natural history of disease refers to the progression of a disease process in an individual over time, in the absence of treatment. For example, untreated infection with HIV causes a spectrum of clinical problems beginning at the time of seroconversion (primary HIV) and terminating with AIDS and usually death. It is now recognized that it may take 10 years or more for AIDS to develop after seroconversion. The process begins with the appropriate exposure to or accumulation of factors sufficient for the disease process to begin in a susceptible host. For an infectious disease, the exposure is a microorganism. This stage of subclinical disease, extending from the time of exposure to onset of disease symptoms, is usually called the incubation period for infectious diseases, and the latency period for chronic diseases. During this stage, disease is said to be asymptomatic (no symptoms) or inapparent. The onset of symptoms marks the transition from subclinical to clinical disease. Most diagnoses are made during the stage of clinical disease. In some people, however, the disease process may never progress to clinically apparent illness. In others, the disease process may result in illness that ranges from mild to severe or fatal. This range is called the spectrum of disease (the disease process ends in recovery, disability or death.)
Measures of central tendency
The clustering at a particular value is known as the central location or central tendency of a frequency distribution. The central location of a distribution is one of its most important properties. Sometimes it is cited as a single value that summarizes the entire distribution. Three measures of central location are commonly used in epidemiology: arithmetic mean, median, and mode. Depending on the shape of the frequency distribution, all measures of central location can be identical or different. Additionally, measures of central location can be in the middle or off to one side or the other.
functions of epidemiology: field investigation
The investigation may be as limited as a phone call to the health-care provider to confirm or clarify the circumstances of the reported case, or it may involve a field investigation requiring the coordinated efforts of dozens of people to characterize the extent of an epidemic and to identify its cause. The objectives of such investigations also vary. Investigations often lead to the identification of additional unreported or unrecognized ill persons who might otherwise continue to spread infection to others. For example, one of the hallmarks of investigations of persons with sexually transmitted disease is the identification of sexual partners or contacts of patients. When interviewed, many of these contacts are found to be infected without knowing it, and are given treatment they did not realize they needed. Identification and treatment of these contacts prevents further spread.
