Manual for the surveillance of vaccine-preventable diseases. Chapter 20: Analysis of surveillance data
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Manual for the surveillance of vaccine-preventable diseases. Chapter 20: Analysis of surveillance data

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  • Alternative Title:
    Analysis of surveillance data
  • Journal Article:
    Manual for the surveillance of vaccine-preventable diseases
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    Chapter 20 of: Manual for the surveillance of vaccine-preventable diseases. 5th edition, 2011.

    Ongoing analysis of surveillance data is important for detecting outbreaks and unexpected increases or decreases in disease occurrence, monitoring disease trends, and evaluating the effectiveness of disease control programs and policies. This information is also needed to determine the most appropriate and efficient allocation of public health resources and personnel.

    Analyses should be performed at regular intervals to identify changes in disease reporting. These analyses can be performed using standard approaches (e.g., running a standard computer program to generate a summary report). Findings of analyses should be reviewed regularly and provided as feedback to medical providers and others in the community who are asked to report cases. Often additional, special analyses are needed to answer specific questions that arise; these analyses may require additional customized approaches beyond what are routinely performed.

    Analyses can be done using any one of a number of database and statistical programs. Systems developed by CDC and others can assist in epidemiologic and laboratory surveillance, outbreak detection, and mapping. Local health departments should contact the state health department for information about recommended software and to identify support for setting up a surveillance database at a local level. The state health department may also give assistance in setting up useful analyses and reports that can be generated as needed.

    However, although computer technology has greatly facilitated collection and analysis of surveillance data, surveillance of most vaccine-preventable diseases in the United States results in small numbers of cases, and data analysis is not complex (see examples included in this chapter). In addition, skillful interpretation of the data is needed to determine why any aberrations may be occurring or decide whether additional action is necessary. Therefore, both technologic and human factors play important roles in analysis of surveillance data. Despite the increased speed and accuracy of a sophisticated trend analysis, it must be supplemented by familiarity with the people and the disease patterns in a community and with the reporting system being used.

    The mistake most commonly made in analysis and use of public health surveillance data is not related to statistical testing, improper presentation of data, or failure to perform complex multivariate analyses; the most common mistake is not looking at the data. Computer hardware and software can facilitate the epidemiologist’s task, but they are no substitute for looking, thinking, discussing, and taking action.


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