# Chick’s Law-Basis of Disinfectant validation and D value

In 1908 a British scientist, Dr. Harriet Chick, described a method for estimating the destruction of microorganisms by chemical disinfectants (Chick 1908). She postulated that the microbial mortality would follow what in physical chemistry would be called “first-order kinetics”—that is, mortality vs time data plots as a straight line on a semilogarithmic graph. In practice, her postulate was correct and the law works for all liquid disinfectants and for many sterilization processes (for example, Chick’s Law has evolved into what is now referred to as D-value in autoclave sterilization).

This simple “Law” (actually an equation) was modified quickly to account for varying disinfectant concentrations, and the pH of the disinfectant solution (Watson 1908) and the modified equation is now commonly called the “Chick-Watson Law”. In 1908 Chicago and Jersey City were the first U.S. cities to use chlorine disinfection to supplement drinking water filtration based on the work of Chick. By 1918, more than 1,000 U.S. cities were disinfecting water using this method—and, ofcourse, the method is still in use today. So although the Chick-Watson Law is over 100 years old, it’s very applicable to modern disinfection practices.

[b][COLOR=“blue”]Chick-Watson equation is:

C to power of Eta(η) x t = a constant

Where:
C = concentration of disinfectant (mg/L)
t = contact time (min)
η = a constant that is different for each different disinfectant[/color][/b]

Another way of writing the Chick-Watson equation is:

[b][COLOR=“darkred”]ηlogC + logt = a constant

so that a log-log plot of C vs t yields a straight line.[/color][/b]

The above equations are telling us that if η has a large numerical value for a particular disinfectant for a specific microbial species, dilution has a large effect and therefore longer exposures to the diluted disinfectant are required to kill the same number of that species. On the other hand if the numerical value of η is small, dilution has a lesser effect.