A Bayesian inference approach to quantify average pathogen loads in farmyard manure and slurry using open-source Irish datasets

Farm-to-fork quantitative microbial risk assessments (QMRA) typically start with a preliminary estimate of initial concentration (Cinitial) of microorganism loading at farm level, consisting of an initial estimate of prevalence (P) and the resulting pathogen levels in animal faeces. An average estimation of the initial concentration of pathogens can be achieved by combining P estimates in animal populations and the levels of pathogens in colonised animals' faeces and resulting cumulative levels in herd farmyard manure and slurry (FYM&S). In the present study, 14 years of data were collated and assessed using a Bayesian inference loop to assess the likely P of pathogens. In this regard, historical and current survey data exists on Pestimates fora number of pathogens, including Cryptosporidium parvum, Mycobacterium avium subspecies paratuberculosis (MAP), Salmonella spp., Clostridium spp., Campylobacter spp., pathogenic E. con. and Listeria monocytogenes in several species (cattle, pigs, and sheep) in Ireland. The results revealed that Cryptosporidium spp. has potentially the highest mean P (P.) (25.93%), followed by MAP (15.68%) and Campylobacter spp. (8.80%) for cattle. The (Pmean) of E. coli is highest (7.42%) in pigs, while the P-mean of Clostridium spp. in sheep was estimated to be 7.94%. C-initial for Cryptosporidium spp., MAP.,Salmonella spp., Clostridium spp., and Campylobacter spp. in cattle faeces were derived with an average of 2.69, 438, 424, 3.46, and 3.84 log(10 )MPN g(-1), respectively. Average C-initial of Cryptospotidium spp., Salmonella spp., Clostridium spp., and E. coli in pig slurry was estimated as 127, 3.12, 3.02, and 4.48 log(10) MPN g(, )(-1) respectively. It was only possible to calculate the average C-initial of Listeria monocytogenes in sheep manure as 1.86 log(10) MPN g(-1). This study creates a basis for future farm-to-fork risk assessment models to base initial pathogen loading values for animal faeces and enhance risk assessment efforts. (C) 2021 The Author(s). Published by Elsevier B.V.

Automated summary

The study in Ireland collected data on prevalence estimates of various pathogens in different animal species, revealing the highest mean P for Cryptosporidium spp., MAP, and Campylobacter spp. in cattle. The study also calculated the initial concentration of pathogens in animal feces and slurry, providing a basis for future farm-to-fork risk assessment models.