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      Choosing a future for epidemiology: I. Eras and paradigms.

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      American Journal of Public Health
      American Public Health Association

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          Abstract

          To inform choices about the future of epidemiology, the present condition of epidemiology is examined, in terms of its evolution through three eras, each demarcated by its own paradigm: (1) the era of sanitary statistics with its paradigm, miasma; (2) the era of infectious disease epidemiology with its paradigm, the germ theory; and (3) the era of chronic disease epidemiology with its paradigm, the black box. The historical context in which these eras arose is briefly described. In each era, the public health was at the center of the concerns of the founders and early protagonists of the prevailing paradigm. Around this intellectual development we weave a further theme. We argue that in the present era, the public health has become less central a concern. At the same time, in epidemiology today the dominant black box paradigm is of declining utility and is likely soon to be superseded.

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          Most cited references22

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              Estimability and estimation in case-referent studies.

              The concepts that case-referent studies provide for the estimation of "relative risk" only if the illness is "rare", and that the rates and risks themselves are inestimable, are overly superficial and restrictve. The ratio of incidence densities (forces of morbidity)-and thereby the instantaneous risk-ratio-is estimable without any rarity-assumption. Long-term risk-ratio can be computed through the coupling of case-referent data on exposure rates for various age-categories with estimates, possibly from the study itself, or the corresponding age-specific incidence-densities for the exposed and nonexposed combined-but again, no rarity-assumption is involved. Such data also provide for the assessment of exposure-specific absolute incidence-rates and risks. Point estimation of the various parameters can be based on simple relationships among them, and in interval estimation it is sufficient simply to couple the point estimate with the value of the chi square statistic used in significance testing.
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                Author and article information

                Journal
                American Journal of Public Health
                Am J Public Health
                American Public Health Association
                0090-0036
                1541-0048
                May 1996
                May 1996
                : 86
                : 5
                : 668-673
                Article
                10.2105/AJPH.86.5.668
                1380474
                8629717
                898e93cd-ea0c-4c11-8968-1dbd26ddd55f
                © 1996
                History

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