

@article {15246,
	title = {A probabilistic model of gastroenteritis risks associated with consumption of street food salads in {Kumasi}, {Ghana}: evaluation of methods to estimate pathogen dose from water, produce or food quality.},
	journal = {Science of the Total Environment},
	volume = {487},
	year = {2014},
	pages = {130{\textendash}142},
	abstract = {With a rapidly growing urban population in Kumasi, Ghana, the consumption of street food is increasing. Raw salads, which often accompany street food dishes, are typically composed of perishable vegetables that are grown in close proximity to the city using poor quality water for irrigation. This study assessed the risk of gastroenteritis illness (caused by rotavirus, norovirus and Ascaris lumbricoides) associated with the consumption of street food salads using Quantitative Microbial Risk Assessment (QMRA). Three different risk assessment models were constructed, based on availability of microbial concentrations: 1) Water - starting from irrigation water quality, 2) Produce - starting from the quality of produce at market, and 3) Street - using microbial quality of street food salad. In the absence of viral concentrations, published ratios between faecal coliforms and viruses were used to estimate the quality of water, produce and salad, and annual disease burdens were determined. Rotavirus dominated the estimates of annual disease burden (\~{}10(-3)Disability Adjusted Life Years per person per year (DALYs pppy)), although norovirus also exceeded the 10(-4)DALY threshold for both Produce and Street models. The Water model ignored other on-farm and post-harvest sources of contamination and consistently produced lower estimates of risk; it likely underestimates disease burden and therefore is not recommended. Required log reductions of up to 5.3 (95th percentile) for rotavirus were estimated for the Street model, demonstrating that significant interventions are required to protect the health and safety of street food consumers in Kumasi. Estimates of virus concentrations were a significant source of model uncertainty and more data on pathogen concentrations is needed to refine QMRA estimates of disease burden.},
	keywords = {drinking water, Drinking Water: parasitology, Food Contamination, Food Contamination: statistics \& numerical data, Gastroenteritis, Gastroenteritis: epidemiology, Ghana, Ghana: epidemiology, Humans, Kumasi, Models, QMRA, Risk Assessment, Statistical, Vegetables, Vegetables: parasitology, Water quality},
	author = {S F Barker and Amoah, Philip and Drechsel, Pay}
}
