A Genomic Model for Predicting the Ultraviolet Susceptibility of Viruses and Bacteria Wladyslaw J. Kowalski 1 , William P. Bahnfleth 2 , Mark T. Hernandez 3 1 Immune Building Systems, Inc., 575 Madison Ave., New York, NY10022, email: drkowalski@ibsix.com 2 The Pennsylvania State University, Department of Architectural Engineering, University Park, PA 16802 3 University of Colorado, UCB 428, Department of Civil, Environmental, and Architectural Engineering, 1111 Engineering Drive #441, Boulder, CO 80309 Abstract A mathematical model is presented for the ultraviolet susceptibility of microbes based on evaluation of complete genomes. The genomes of 49 animal viruses and bacteriophages, and 33 bacteria, were analyzed using base-counting software to establish the frequencies of potential dimers. A total of 71 data sets represented 27 ssRNA viruses, while 77 data sets represented 22 dsDNA viruses, and 64 data sets represented the bacteria. UV susceptibility (D 90 ) was correlated with the genomic model and produced R 2 values of 79%, 87%, and 70% for RNA viruses, DNA viruses and bacteria respectively. Predictions of UV susceptibility are provided for dozens of microbes important to human health. Key words: Ultraviolet Radiation; Ultraviolet Susceptibility; Ultraviolet Inactivation; Genomic Modeling; Viruses; Bacteria; Photodimerization; UV Rate Constants; UV D90 Values; UV Inactivation, Predictive UV Modeling. Introduction In previous publications a genomic model was presented for single stranded RNA and double stranded DNA viruses which achieved UV susceptibility correlations of 67% and 62% respectively (Kowalski et al 2009, 2009a, Kowalski 2009). In this paper an improved genomic model is presented and applied to the same viruses and to bacteria. The model consists of three interacting components – 1) a base-counting algorithm that evaluates the genome for dimerizable pyrimidine and purine bases, 2) a UV scattering model that is a function of the physical size of the microorganism and, and 3) the G+C content of the genome. Various intrinsic factors determine the sensitivity of a microbe to UV exposure under any set of constant ambient conditions of temperature and humidity including 1