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The epi curve is represented by a graph with two axes that intersect at right angles. Each axis is divided into equally spaced intervals, although the intervals for the two axes may differ. An epi curve is a visual display of the onset of illness among cases associated with an outbreak. The magnitude of an outbreak can be assessed easily with a glance of the epi curve.

Are there many cases or just a few? The time trend , or the distribution of cases over time, will give an indication of where the outbreak is in its course. Are cases still rising or has the outbreak already peaked?

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An epidemic curve epi curve shows progression of illnesses in an outbreak over time. Epi curves depict when people became ill by day, week, or month. In foodborne outbreak investigations, this information is often shown by the week people became ill.

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A critical but often overlooked question in the study of ligands binding to proteins is whether the parameters obtained from analyzing binding data are practically identifiable PI , i. Here we report a general approach to assess and understand binding parameter identifiability, which provides a toolkit to assist experimentalists in the design of binding studies and in the analysis of binding data.

The partial fraction PF expansion technique is used to decompose binding curves for proteins with n ligand-binding sites exactly and uniquely into n components, each of which has the form of a one-site binding curve. The association constants of the PF component curves, being the roots of an n -th order polynomial, may be real or complex. We demonstrate a fundamental connection between binding parameter identifiability and the nature of these one-site association constants: all binding parameters are identifiable if the constants are all real and distinct; otherwise, at least some of the parameters are not identifiable.

The theory is used to construct identifiability maps from which the practical identifiability of binding parameters for any two-, three-, or four-site binding curve can be assessed. Instructions for extending the method to generate identifiability maps for proteins with more than four binding sites are also given. Further analysis of the identifiability maps leads to the simple rule that the maximum number of structurally identifiable binding parameters shown in the previous paper to be equal to n will also be PI only if the binding curve line shape contains n resolved components.

The thermodynamic theory of ligands binding to macromolecules containing multiple binding sites is reviewed in several monographs Poland, ; Hill, ; Wyman and Gill, ; Ben-Naim, A remarkable feature of the theory is that the mathematical form of the partition function for these systems also known as the binding polynomial is conserved for virtually all physically reasonable binding models Wyman and Gill,

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of sites per surface or the number of lichens per site employed in its construction. Nine lichenometry curves of exponential form are constructed from largest.

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