Analysis by other personal attributes in descriptive epidemiology involves comparing rates or other numeric data by different classes of the attribute. Summarize with average rates, average counts, or totals for all the Januarys, Februarys, and so on for each of the 12 months. Scatter plots are versatile instruments for exploring and communicating data. In arranging analytical tables, you should begin with the arrangement of the data space by following a simple set of guidelines (Box 6.3) (1). Often, a periodicity equivalent to the generation period for the agent might be obvious during the initial stages of the outbreak. In Figure 6.15, a distinctive pattern of rapidly increasing cholera death rates is apparent as the altitude approaches the level of the River Thames. Compare the association of cases during these pre-and post-epidemic periods with the main outbreak. Provides timely information for decision-makers, the media, the public, and others about ongoing investigations. Epidemic curves for large geographic areas might not reveal the early periodicity or the characteristic increase and decrease of a propagated outbreak. For certain conditions, a description by season, month, day of the week, or even time of day can be revealing. Surveillance Reports These reports provide alcohol-related trend data in the U.S. for: The x-axis represents a period of interest. Second, age is a strong independent determinant for many causes of morbidity and mortality. Different types of data joins for health analysis. Secular trends of invasive cervical cancer (Figure 6.11) reveal steady decreases over 37 years (11). This task, called descriptive epidemiology, answers the following questions about disease, injury, or environmental hazard occurrence: The first question is answered with a description of the disease or health condition. Never mix incident with prevalent cases in epidemiologic analyses. Thus, incidence divided by an appropriate estimation of the population yields several versions of incidence rates. o r g / t o o l s / r e f _ t u t o r / e p i d e m / f o u r . Dots, onset times, case identification numbers for indexing with a line listing, or other symbols might represent disease cases (Box 6.10). For example, overweight prevalence in the Ajloun data can be compared by using different education levels. Outbreaks can arise from common sources that continue over time. These are widely dispersed, indicating that they did not acquire their infection from their local environs. Decrease the time interval size as case numbers increase. A propagated pattern arises with agents that are communicable between persons, usually directly but sometimes through an intermediate vehicle. For example, the map of spotted fever rickettsioses in the United States effectively displays multiple levels of risk for human infection (Figure 6.14) (15). Onset might not always be available. These distance associations of cases or rates are best understood on maps. Types of epidemiological studiesa I. Rates, Ratios, and Alternative Denominators. For prevalence, this fluctuation amplifies the statistical error. Check back in April 2021 for the next application opportunity. Indicate the data range in the legend; do not leave it open-ended. Ecological studies are generally used in public health research. Supports decisions for initiating or modifying control and prevention measures. The epidemic curve accompanying the severe acute respiratory syndrome (SARS) contact diagram (Figure 6.2, panel B) illustrates these features, including waves with an approximate 1-week periodicity. For example, the consistent time interval between rotavirus vaccination and onset of intussusception (Table 6.1) helped build the hypothesis that the vaccine precipitated the disease (1). Dot plots, box plots, and bar charts are easier to understand and read if aligned horizontally (with the numeric axis horizontal). Traditionally, a GIS stores spatial data as a feature by location. Epidemiology is the branch of medical science that investigates all the factors that determine the presence or absence of diseases and disorders. Days (2-day intervals) between onset of a case of severe acute respiratory syndrome and onset of the corresponding source case: Beijing, China, March–April 2003. Random or uniform distributions indicate that the exposure lies outside the group. Epidemic Curves. In most descriptive analyses, the epidemiologist will determine disease rates by age. Make sure overlapping plotting symbols are distinguishable. Guidelines for Graphical Data Presentation, Characteristics of Propagated Epidemic Curves, Factors Affecting Patterns of Human–Vector–Human Transmission Across Time, Guidelines Regarding Data Display Area Of Epidemiologic Maps, Three General Interpretations of Age Distributions, Centers for Disease Control and Prevention. p h p 3 o c c u p a t i o n a l ñ D ĞÉêyùºÎŒ‚ ª K© àÉêyùºÎŒ‚ ª K©p h t t p : / / w w w . ÷% ´' ¨, ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı M… ş ³' ´' §, ¨, ¾, ¿, Ÿ.  . Use the most important epidemiologic features on which to sort the data. For example, initial respiratory symptoms might indicate exposure through the upper airways, as in Table 6.2. The y-axis represents the rate of the health event. A statistical data display should include, at a minimum, F, female; M, male. These graphs can include line graphs, histograms (epidemic curves), and scatter diagrams (see Box 6.4 for general guidelines in construction of epidemiologic graphs). Minimize frames, gridlines, and tick marks (6–10/axis is sufficient) to avoid interference with the data. Avoid using dividing lines, grids, and other embellishments within the data space. In the example diagram, closeness and quality of relationships, timing between onsets, and places of contact are all displayed through different symbols and shading (Figure 6.2) (5). The choice between tables and charts depends on the purpose, the audience, and the complexity of the data. When the row or column headings are numeric (e.g., age groups), they should govern the order of the data. Use the most important epidemiologic features on which to sort the data. In creating epidemiologic maps, you should follow certain basic guidelines (Box 6.9). Recognizing disease patterns by personal attributes (e.g., age, sex, education, income, or immunization status) constitutes the fifth element in descriptive epidemiology. Experimental A. Indicate underpopulated or depopulated areas. Organizing descriptive data into tables, graphs, diagrams, maps, or charts provides a rapid, objective, and coherent grasp of the data. The map is divided into population enumeration areas for which rates or ratios can be computed. These case counts are valid for epidemiologic comparisons only when they come from a population of the same or approximately the same size. Strictly speaking, in computing rates, the disease or health event you have counted should have been derived from the specific population used as the denominator. Epidemiologists fulfill a broad spectrum of duties that vary depending on the type of disease and the purpose of the study. A first and simple step in determining how much is to count the cases in the population of interest. The Four Most Common Types of Epidemiological Studies. The worldwide prevalence of overweight and obesity has doubled since 1980 to an extent that nearly a third of the world's population is now classified as overweight or obese. As a field epidemiologist, you will collect and assess data from field investigations, surveillance systems, vital statistics, or other sources. First, determining rates is more often necessary than for time and place. For rates that vary more widely, a logarithmic scale for the y-axis is recommended for epidemiologic purposes (Figure 6.10) (10). An underrecognized value of epidemiological … Compute and plot rates for the smallest area possible. Use spot maps to reveal spatial associations between cases and between cases and geographic features. At each location there may be one or more associated pieces of information (for example, population by administrative area). Finding such information can be a minefield. It provides a way of organizing and analyzing these data to describe the variations in disease frequency among populations by geographical areas and over time (i.e., person, place, and time). A moving average line underlying the data markers. éæé >*B*aJ ph ğ wh ğ CJ aJ CJ aJ �já U�jâ U�jó U�j U j UaJ aJ 5�>*CJ OJ QJ aJ0 5�>*CJ aJ0 C 6 s Î - ¤ š Ô “ ÿ aRotaShield®, Wyeth-Lederle, Collegeville, Pennsylvania Population II. This propagated pattern has four principal characteristics (Box 6.6). f a c s n e t . Each spot in the plotting area represents the joint magnitude of the two variables. Aspect ratios (data space width to height) of approximately 2:1 work well. The science of epidemiology has matured significantly from the times of Hippocrates, Semmelweis and John Snow.The techniques for gathering and analyzing epidemiological data vary depending on the type of disease being monitored but each study will have overarching similarities. o r g / t o o l s / r e f _ t u t o r / e p i d e m / f o u r . Your analytic findings must explain the observed patterns by time, place, and person. This will be reflected by an instability of the epidemic curve. They begin with a single or limited number of cases and increase with a gradually increasing upslope. p h p 3 c o h o r t ï D ĞÉêyùºÎŒ‚ ª K© àÉêyùºÎŒ‚ ª K©p h t t p : / / w w w . Include a legend or key to clarify map features (e.g., disease cases, rates, and exposures). After the outbreak peaks, the exhaustion of susceptible hosts usually results in a rapid downslope. With Epi Info™ and a personal computer, epidemiologists and other public health and medical professionals can rapidly develop a questionnaire or form, customize the data entry process, and enter and analyze data. However, a person’s measurements can fluctuate above or below these cutoff values. As an alternative to plotting onset by calendar time, plotting the time between suspected exposures and onset can help you understand the epidemiologic situation. Use alternating light shading of rows to assist readers in following data across a table. Linking to a non-federal website does not constitute an endorsement by CDC or any of its employees of the sponsors or the information and products presented on the website. Of note, administration of antimicrobials, immunoglobulins, antitoxins, or other quickly acting drugs can lead to a shorter than expected outbreak with a curtailed downslope. Accordingly, less efficient and inaccurate displays, although common, were avoided or noted as not recommended. A rapid decrease in dengue cases follows this decrease in vector density. Plotting only numerators loses the advantage of both the spot map (indicating exact location and detailed background features) and the area map (indicating rates). This reveals that factor and that an environmental exposure also related to low altitude (e.g., poor drainage of sewage) might have contributed to cholera incidence. When using transformed data (e.g., logarithmic, normalized, or ranked), represent equal units of the transformed data with equal distances on the axis. Cases are customarily organized in a table called a line-listing (Table 6.1) (2). Ajloun Non-Communicable Disease Project, Jordan, Unpublished data, 2017. Bar charts usually need a zero level because viewers judge magnitude by the length of the bar. Use visually prominent symbols to plot and emphasize the data. Our new CrystalGraphics Chart and Diagram Slides for PowerPoint is a collection of over 1000 impressively designed data-driven chart and editable diagram s guaranteed to impress any audience. They indicate the association between two numerically scaled variables (Figure 6.15) (16). Similarly, when the incubation period is known, you can estimate a time window of exposure and identify exposures to potential causative agents during that window. The last three questions are assessed as patterns of these data in terms of time, place, and person. In surveillance systems, you might have only the report date or another onset surrogate. cDefined as current use of asthma medicine or one or more of the following symptoms during the previous 12 months: wheezing or whistling in the chest, awakening with a feeling of chest tightness, or attack of asthma. Use columns for most crucial data comparisons. To indicate divergence from an average range, use white for the center range and deepening intensities of two different hues for divergent strata on opposite extremes. More than that becomes confusing clutter. As a convention in plotting epidemiologic or geographic association, the explanatory variable (exposure, environmental, or geographic) is plotted on the x-axis, and the outcome (rate or individual health measurement [e.g., BMI]) is plotted on the y-axis. This type of curve can be made for any time cycle (e.g., time of day, day of week, or week of influenza season). For most conditions, when the rates vary over one or two orders of magnitude, an arithmetic scale is recommended. Whether the tables or graphs help the investigator understand the data or explain the data in a report or to an audience, their organization should quickly reveal the principal patterns and the exceptions to those patterns. As an alternative to using tables, charts (Box 6.12) (e.g., dot charts) (Figure 6.16, panel A) or horizontal cluster bar charts (Figure 6.16, panel B) improve perception of the patterns in the data, compared with a table. Types of Bias in Epidemiology Any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically different from the truth can be termed as bias. Consequently, they also accelerate and amplify epidemic development. New health policies in 1970 and 1995 that broadened coverage of Papanicolaou smear screenings for women were initially followed by steeper decreases and subsequent leveling off of the downward trend. The data may be raster, using regular cells, or vector, using points, lines or polygons (areas). You should include on the epidemic curve a representation of the suspected environmental factor (e.g., rainfall connected with leptospirosis in Figure 6.7 [9]). Case Control Study. Data presentation is interchangeable with tables. f a c s n e t . Use an overlaid line graph, labels, markers, and reference lines to indicate suspected exposures, interventions, special cases, or other key features. Other relevant events supplementing a chronologic framework of a health problem include underlying environmental conditions, changes in health policy, and application of control and prevention measures. To calculate incidence, special care therefore is needed to avoid counting the same person every time a fluctuation occurs above or below the cutoff point. An outbreak of dengue arising from a single imported case in a South China town reveals several of these features (Figure 6.6) (8). Source: Adapted from: Ajloun Non-Communicable Disease Project, Jordan, unpublished data, 2017. Contact between severe acute respiratory syndrome (SARS) cases among a group of relatives and health care workers: Beijing, China, 2003. They are often different and have distinct epidemiologic implications. To avoid clutter and maintain undistorted comparisons, consider using two or more separate panels for different strata on the same graph. Helps validate the eventual incrimination of causes or risk factors. Consider indicating the zero-level separately. Within this framework, the most fundamental distinction is between studies of disease ‘incidence’ and studies of disease ‘prevalence’. To approximate the time of exposure, count backward to the average incubation period before the peak, the minimum incubation period from the initial cases, and the maximum incubation period from the last cases. p h p 3 c r o s s í D ĞÉêyùºÎŒ‚ ª K© àÉêyùºÎŒ‚ ª K©p h t t p : / / w w w . Epidemic curves often have patterns that reveal likely transmission modes. To indicate nominative (non-numeric) qualities, use different hues or fill patterns. The last two factors listed in the box will lead to irregular peaks during the progression of the outbreak and precipitous decreases. Clustered distributions might result from common exposures of group members, an agent that is transmissible through personal contact, an environmental exposure in the living or meeting areas, or localization of houses near or within an environmental area of high risk. Seasonal patterns might be summarized in a seasonal curve (Box 6.8). Summary – Descriptive vs Analytic Epidemiology. Below are links to statistical summaries of data collected or compiled by NIAAA on alcohol consumption, alcohol-related mortality and morbidity, and other alcohol-related problems and consequences. 68 TYPES OF EPIDEMIOLOGIC STUDIES variability of extraneous factors (i.e., those factors other than the key study variables) was too small to affect the outcome under study to an important extent. Identifies populations at increased risk for the health problem under investigation. This will be modified by the variability of contact between humans and the reservoir animal and, for vectorborne zoonoses, contact with the arthropod vector. Keep keys, legends, markers, and other annotations out of the data space. When the row or column headings are numeric (e.g., age groups), they should govern the order of the data. Represent dependent variables on the vertical scale and independent variables on the horizontal scale. Deputy Director for Public Health Science and Surveillance, Center for Surveillance, Epidemiology, and Laboratory Services, Division of Scientific Education and Professional Development, U.S. Department of Health & Human Services. Descriptive and Analytic Epidemiology are the two main branches of epidemiology which define disease or an infection and its various aspects. Implicit in any epidemiological investigation is the notion of a target populationabout which conclusions are to be drawn. In this example, nearly every peak of rainfall precedes a peak in leptospirosis, supporting the hypothesis regarding the importance of water and mud in transmission. Use graphic designs that reveal the data from the broad overview to the fine detail. Occupational Epidemiological Study. p h p 3 t o p Date of onset of 185 cases of dengue in a fishing port: Guangdong Province, China, 2007. An analysis of BMI by age from Ajloun and Jerash Governorates, Jordan, draws attention to increasing BMI and accumulating overweight prevalence for persons aged 18–75 years (Table 6.3) (Ajloun Non-Communicable Disease Project, Jordan, unpublished data, 2017). To indicate no data, use a different hue or fill pattern. Returning now to counts, you can calculate expected case counts for a population by multiplying an expected (e.g., historical counts, increased surveillance, or output from prevention and control programs) or a target rate by the population total. Spot maps that plot cases have a general weakness. The dot chart is the most versatile and the easier to understand, particularly as categories increase in number. Avoid using area maps to display case counts. Epidemiological data from cohorts of occupationally exposed people or atomic bomb survivors demonstrate that ionizing radiation is capable of inducing many types of cancer. However, being aware of what kind of data you need is only useful if you can find accurate, reliable and up to date sources. Seasonal distribution of malaria cases, by month of detection by voluntary collaborators in four villages: El Salvador, 1970–1977. ¡1 !3 "3 Q3 R3 4 4 4 œ4 56 |9 : : ': Ë; ğ> Ç@ È@ Ú@ 'C İD 7G 8G DG kH ‚J ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ‚J �M [O \O rO Q aS bS ŠS ‹S U U nW oW ’W ^X øZ O] å^ °_ ±_ º_ Ô` ïb ğb c 'd .g ´i µi ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı µi ài ái ¥j ¦j Ëj ’m ‘o Ûp Üp øp s u u 1u ‰v ‰w rz é| Ã~ Y Z e ä€ qƒ K… L… M… ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı °Ğ/ °à=!°"°#� $� %° ó D ĞÉêyùºÎŒ‚ ª K© àÉêyùºÎŒ‚ ª K©p h t t p : / / w w w .