Norovirus transmission on farms during produce harvest and packing: A quantitative microbial risk assessment model approach

Purpose: Noroviruses (NoV) are a major cause of acute gastrointestinal illness worldwide. NoV are highly infectious and can withstand chemical and physical stressors. NoV is associated with 40% of all produce outbreaks annually in the US. Quantitative microbial risk assessment (QMRA) is a form of probabilistic modeling that simulates the transmission of microbes in the environment to estimate exposure levels. Methods: We developed a QMRA model of NoV transmission in farms and packing sheds using a multi-stage process beginning with simple deterministic modeling in Microsoft Excel and culminating in a complex stoichiometric model constructed in Oracle Crystal Ball. To enhance the model's data quality, we conducted transfer experiments in the laboratory to estimate NoV transmission to a variety of surfaces under a range of conditions. Results: Based on the deterministic model, fecal hand contamination was the greatest determinant of contamination, followed in importance by NoV excretion level. Key modifiable factors included hand washing and the number of times items are handled. Packer hand washing reduced contamination by 9.0%, and harvester hand washing reduced contamination by 2.5%. When the NoV excretion level was high and produce was handled multiple times during packing, it resulted in an increase of 26 NoV particles/cm^2, nearly twice the ID50. Discussion: QMRA modeling for NoV highlights modifiable factors that contribute to NoV transmission and allows for prioritization by effect size. The model supports agricultural practice guidelines that concentrate on hand washing and field toilet use and suggests that mechanization may reduce the risk of NoV contamination.