The science of sterilization and disinfection has received considerable attention in the last 100 years (10, 11,13,18). Its
importance was initially linked to an understanding of prevention and transmission of disease. Later, the consistent production
of quality products such as wine, milk, and milk products became the emphasis. Significant strides were made in the last century
in defining and predicting rates of microbial inactivation using the concept of decimal reduction values or D-values (18–20).
As the science of sterilization was refined, it became necessary to be able to predict the surviving numbers of microbes as
their population approached zero. Thus the probabilistic nature of microbial lethality and first order kinetics has become
a well recognized applied science. One method of predicting low numbers of surviving microbes is the MPN approach of Halvorson
and Ziegler (16). MPN gives an estimate of the average number of surviving spores per BI.
MPN is calculated using the formula:
MPN = ln (n ÷ r)
where n is the total number of units tested, and r is the number of sterile units.
The MPN approach can be applied to all fraction negative-type data (number tested/number nonsterile) as long as at least one
of the replicate BIs is nonsterile. The MPN approach is generally applied over the range of 1% to 99% sterile BIs. The experimental
design must ensure that all these BIs are statistical replicates.
The validity of the MPN approach for determination of inactivation rates and D-values has been affirmed by comparing results
obtained by the survivor curve method (13, 19). D-values determined by the latter method generally agree well with those determined
by the MPN approach.
The MPN approach is valuable because it allows prediction of the distribution of surviving spores over a wide range of fraction
negative-type data. Table II lists the average number of surviving spores over the range of 99% to 1% nonsterile determined
by the MPN approach. Also listed, for each average number of surviving spores, is the number of nonsterile BIs with 0, 1,2,3,4,5,6,7,8,9,
or 10, surviving spores determined by a Poisson distribution calculation based upon the given average number.
Table II: Most probable number of surviving spores per biological indicator.
For a set of 100 BIs exposed to a sterilization process where only one BI is found to be sterile, the average number of surviving
spores is 4.605 as determined by the MPN calculation. In the cases of 80 and 30 nonsterile BIs out of 100 tested, the average
number of survivors, as would be expected, is lower at 1.609 and 0.357, respectively. The cases of 80 and 30 nonsterile BIs
per 100 tested are particularly relevant to a discussion of the RIT protocol.
If a set of 100 BIs is exposed to a sterilization process and 80 of the BIs are nonsterile, it is clear that 20 of the BIs
have "0" surviving spores. The MPN calculation gives an average number of surviving spores of 1.609 or a total of~161 spores
distributed across the 80 nonsterile BIs. The Poisson distribution analysis shows that ~32 of the BIs would be expected to
have only one surviving spore and ~2 BIs would be expected to have five surviving spores. In the case where only 30 nonsterile
BIs were found after an exposure to a sterilization process, 70 would have 0 spores and ~25 would be expected to have one
surviving spore. In this case, a BI with five surviving spores would be very unlikely.