types of epidemiological data

Use the table layout to guide the eye. Consider instead. Cases of typhoid fever by date of onset: Tabuk, Saudi Arabia, April–June 1992. 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. Types of epidemiological studiesa I. For example. For most conditions, a time characteristic of interest is the secular trend—the rate of disease over multiple years or decades. The downslope can be precipitous if the common source is removed or gradual if it exhausts itself. A propagated pattern arises with agents that are communicable between persons, usually directly but sometimes through an intermediate vehicle. However, the use of the graphs is based on the type … Cases not included in clusters are marked with smaller dots. 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. Tables are commonly used for characterizing disease cases or other health events and are ideal for displaying numeric values. In creating epidemiologic maps, you should follow certain basic guidelines (Box 6.9). In classical epidemiology, researchers investigate the factors behind what causes diseases among key populations and how they are distributed. Cases can be plotted on a base map (Figure 6.13 [14]), a satellite view of the area, a floor plan, or other accurately scaled diagram to create a spot map. Ecological studies are generally used in public health research. Cases of leptospirosis by week of hospitalization and rainfall in Salvador, Brazil, March 10–November 2, 1996. If the disease cause is unknown, this arrangement can assist the epidemiologist in developing hypotheses regarding possible exposures. Use the most important epidemiologic features on which to sort the data. A more precise approach to estimating how much for measurements on a continuous scale, discussed earlier in this chapter, might be to compute the average and dispersion of the individual BMI measurements, as shown on a box-and-whisker plot (Figure 6.1). The line indicates the rapid decrease in Aedes-infested houses (house index). Similarly, times of suspected exposures vary in their precision. f a c s n e t . A well-structured analytical table that is organized to focus on comparisons will help you understand the data and explain the data to others. Through this process of organization, inspection, and interpretation of data, descriptive epidemiology serves multiple purposes (Box 6.1). Measures the progress of control and prevention programs. After the outbreak peaks, the exhaustion of susceptible hosts usually results in a rapid downslope. Accordingly, less efficient and inaccurate displays, although common, were avoided or noted as not recommended. Provide marginal averages, rates, totals, or other summary statistics for rows and columns whenever possible. The observed pattern might represent variability in the distribution of the underlying population. Analysis by other personal attributes in descriptive epidemiology involves comparing rates or other numeric data by different classes of the attribute. 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. Private sources are more expensive but can contain more specific, detailed data on devices … Do not stack columns for different groups atop one another in the same graph. Thus, incidence divided by an appropriate estimation of the population yields several versions of incidence rates. This type of curve can be made for any time cycle (e.g., time of day, day of week, or week of influenza season). 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. Epidemic curves for large geographic areas might not reveal the early periodicity or the characteristic increase and decrease of a propagated outbreak. This count of incident cases over time in a population is called incidence. Different types of data joins for health analysis. ÷% ´' ¨, 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.  . Indicate underpopulated or depopulated areas. Source: Ajloun Non-Communicable Disease Project, Jordan, Unpublished data, 2017. Second, the study of populations enables the identification of the causes and preventive factors associated with disease. Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in defined populations.. Age-adjusted rates can be used for comparing populations from different areas, from the same area at different times, and among other characteristics (e.g., ethnicity or socioeconomic status). Use columns for most crucial data comparisons. Finding such information can be a minefield. Seasonal patterns might be summarized in a seasonal curve (Box 6.8). Cases of Salmonella enterica serovar Heidelberg infection, by illness onset date: Colorado, July 10– August 17, 1976. o r g / t o o l s / r e f _ t u t o r / e p i d e m / d a t a . With diseases of shorter incubation and lower rates of secondary spread, the secondary wave might appear only as a more prolonged downslope. Ajloun Non-Communicable Disease Project, Jordan, Unpublished data, 2017. The choice between tables and charts depends on the purpose, the audience, and the complexity of the data. Identifies populations at increased risk for the health problem under investigation. A moving average line underlying the data markers. Obesity is a complex multifactorial disease. Use an overlaid line graph, labels, markers, and reference lines to indicate suspected exposures, interventions, special cases, or other key features. Organizing descriptive data into tables, graphs, diagrams, maps, or charts provides a rapid, objective, and coherent grasp of the data. f a c s n e t . 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). 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. After the initial case, 15 days elapsed until the peak of the first generation of new cases. With acute infections, poisonings, and injuries, you will often have precise exposure times to different suspected agents. The epidemiology of human communication is a –Single item, multiple items, new/previously validated measure In addition to the previously mentioned elements in common to all data displays (Box 6.2), tables have column and row headings that identify the data type and any units of measurement that apply to all data in that column or row. Secular trends of invasive cervical cancer (Figure 6.11) reveal steady decreases over 37 years (11). Onset might not always be available. Two important qualifications apply to person data assessments. The areas are then ranked into strata by the rates, and the strata are shaded (Box 6.10) according to the magnitude of the rate. Plot the rate, average, or total for each interval on a histogram or line graph. Tables, graphs, maps, and charts all have four elements in common: a title, data, footnotes, and text (Box 6.2). 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. It reveals the location of the first case in the business district and the large initial cluster surrounding it (Figure 6.13) (14). Epidemiological conclusions (on risk) cannot be drawn from purely clinical data (on the number of sick people seen). Commonly in descriptive epidemiology, you organize cases by frequency of clinical findings (Table 6.2) (3). Second, age is a strong independent determinant for many causes of morbidity and mortality. Because population estimates or censuses follow standard geographic areas (e.g., city, census tract, county, state, or country), determination of rates is also restricted to these same areas. 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). Use alternatives to joining data points with a line. On an arithmetic scale, represent equal numerical units with equal distances on an axis. Implicit in any epidemiological investigation is the notion of a target populationabout which conclusions are to be drawn. Stratifying seasonal curves can further expose key differences by place, person, or other features (Figure 6.12) (12). More than that becomes confusing clutter. Cluster bar charts with more than two bars per cluster (e.g., Figure 6.16, panel B) are not recommended. ¡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 . They begin with a single or limited number of cases and increase with a gradually increasing upslope. Conclusions. 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. These can then be counted and the rates calculated. These three points should bracket the exposure period. Random or uniform distributions indicate that the exposure lies outside the group. They are often different and have distinct epidemiologic implications. Point source outbreaks result in infected persons who might have transmitted the agent directly or through a vehicle to others. Dot plots, box plots, and bar charts are easier to understand and read if aligned horizontally (with the numeric axis horizontal). bDuring the previous 12 months. Include a legend or key to clarify map features (e.g., disease cases, rates, and exposures). Contact diagrams are versatile tools for revealing relationships between individual cases in time. 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. Keep keys, legends, markers, and other annotations out of the data space. Two types of data can be used for epidemiological studies: routine data and data which have been collected specifically for the study. Reported incidence rate of spotted fever rickettsiosis† by county: United States, 2000–2013. The disease or health condition onset time is the preferred statistic for studying time patterns. i 4 @ñÿ 4 N o r m a l CJ aJ mH sH tH. More precision is usually not needed for epidemiologic purposes. Clinical B. For questions about the EIS program, please contact us directly at eis@cdc.gov. Population II. If using color, use increasing intensities of the same hue. Outbreaks can arise from common sources that continue over time. Six biologic differences in human–vector–human propagation affect the size and the shape of the epidemic curve (Box 6.7). 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 . Observational A. Descriptive 1. Rates, Ratios, and Alternative Denominators. Government sources are usually more cost efficient and contain nationally representative populations so that national estimates can be determined. Main Menu. An outbreak of dengue arising from a single imported case in a South China town reveals several of these features (Figure 6.6) (8). Types Of Epidemiologists. To indicate nominative (non-numeric) qualities, use different hues or fill patterns. Provides a systematic approach for dissecting a health problem into its component parts. To indicate no data, use a different hue or fill pattern. 1. 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. Thus epidemiological modeling can be used to identify crucial data that needs to be collected. Avoid using area maps to display case counts. Source: Adapted from Ajloun Non-Communicable Disease Project, Jordan, unpublished data, 2017. The map is divided into population enumeration areas for which rates or ratios can be computed. Significant space–time clustering (assessed by the Knox test) of dengue cases in the city of Cairns, Australia, during January–August 2003. It studies the time, place and person involved in the disease. A more precise approach involves computing the average and dispersion of the individual measurements. 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. Although graphs can be attained from different types of tools and software, the presentation of graphs and usage of data types remain the same. When the agent is unknown, the time interval between presumed exposures and onset of symptoms helps in hypothesizing the etiology. Use time intervals of half an incubation or latency period or less. The epidemic curve for a zoonotic disease among humans typically mirrors the variations in prevalence among the reservoir animal population. Outbreaks that arise from environmental sources usually encompass multiple generations or incubation periods for the agent. The counts of incident or prevalent cases can be compared with their historical norm or another expected or target value. Summary – Descriptive vs Analytic Epidemiology. Model estimates of radiation risk derived from analyzing cancer incidence and mortality in these cohorts are the basis of current radiation protection guidelines. Female ; M, male ; SD, standard deviation usually more efficient. Curve has a plateau are assessed as patterns of these data displays will appear where the specific data display include. Using color, use a different hue or fill pattern current radiation protection guidelines interpreting the total for the event! 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