Application Of Quantitative Risk Analysis Methods To Improving Microbial Food Safety In The U.S. And Kenya

Abstract

Risk analysis is an approach that guides efforts to reduce foodborne disease risk through the distinct activities of risk assessment, risk management, and risk communication. In three projects, I improve two categories of risk analysis tools for two distinct food safety risks in two distinct geographic regions: risk assessment of the bacterial pathogen Listeria monocytogenes in the United States and risk management of the mycotoxins aflatoxin and fumonisin in Kenya. First, I use quantitative microbial risk assessment to show increasing high temperature, short time (HTST) pasteurization temperatures to respond to a bioterror threat would increase the risk of listeriosis from consuming pasteurized fluid milk. I incorporate experimental findings that increased HTST pasteurization temperatures (from 72°C to 82°C) increase outgrowth of L. monocytogenes following post-pasteurization contamination of fluid milk. Conservative estimates show annual listeriosis deaths would increase from 18 to 670, a 38-fold increase, if all U.S. fluid milk were pasteurized at the higher temperature. Second, I apply whole genome sequence technology to identify which repeatedly observed strains of L. monocytogenes are more likely persistent within individual delicatessens or are repeatedly reintroduced from outside sources. Phylogenetic analyses of whole genome single nucleotide polymorphisms (SNPs) distinguish populations of L. monocytogenes that are identical by pulsed field gel electrophoresis. Isolates of persistent strains most often differ by less than 10 individual SNPs and diverge from a most recent common ancestor within the plausible lifetime of the delis. Third, I adapt a multi-spectral optical sorter to remove individual maize kernels that are contaminated with aflatoxin above 10 ppb or fumonisin above 1,000 ppb from maize samples collected from open air markets in Eastern Kenya. Sorting kernels by linear discriminant analysis achieved an 83.3% and 83.7% mean reduction in aflatoxin and fumonisin, respectively, while removing 0 to 25% of a maize sample. The technology has the potential to empower Kenyan maize consumers to manage mycotoxin exposure while subjecting them to minimal food losses. My dissertation reports improved quantitative tools and techniques to assess and manage microbial food safety risks. Improved risk analysis tools will allow for more efficient, efficacious interventions to improve food safety.