TY - JOUR
T1 - Public health risks associated with Salmonella contamination of imported edible betel leaves
T2 - Analysis of results from England, 2011–2017
AU - McLauchlin, James
AU - Aird, Heather
AU - Andrews, Nicholas
AU - Chattaway, Marie Anne
AU - de Pinna, E.
AU - Elviss, Nicola
AU - Jorgensen, Frieda
AU - Larkin, L.
AU - Willis, Caroline
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/6/2
Y1 - 2019/6/2
N2 - Fresh betel leaves (Piper betle L.), imported into the UK are a traditional ready-to-eat food consumed by Asian populations. We report here the consolidation of routinely collected data to model the public health risks from consumption of this food. Amongst 2110 samples collected at Border Inspection, wholesale, catering or retail, Salmonella was detected in 488 (23%) of samples tested between 2011 and 2017 and was the most commonly Salmonella-contaminated ready-to-eat food examined by Public Health England during this period. Using data from multiple samples (usually 5) tested per consignment sampled at Border Inspection, contamination levels were calculated by most probable number: seasonal, temporal and country specific differences were detected. Quantitative contamination data was used to estimate the levels present at retail, and a β-Poisson dose response model the probability of illness was calculated. Using data for products imported from India, the probability of acquiring infection following a single exposure (comprising of a single leaf) was estimated to be between 0.00003 (January–March) and 0.0001 (July–September). Using British Asian population data for individuals over 30 years of age in England in 2011, two estimates of consumption were modelled as 2.1 and 12.8 million servings per annum. Results from the model estimated 160 cases (range 102 to 242) and 960 cases (range 612 to 1456) per year in England for the two consumption estimates and equated to 34 (range 22 to 51) and 204 (range 130 to 310) salmonellosis cases per year reported to national surveillance. Salmonella from 475 of the contaminated samples were further characterised which showed a heterogeneous population structure with 46 S. enterica subsp. Enterica serovars, together with S. enterica subs diarizonae and salamae identified. Isolates from individual consignments were diverse and close genetic relationships between independent isolates were very rare except from within an individual consignment. There were no outbreaks detected as associated with betel leaf consumption. However analysis by whole genome sequencing of the 2014–17 data identified two cases where the clinical isolate had <5 single nucleotide polymorphism differences to isolates from betel leaves which is indicative of a likely epidemiological link and common source of contamination. Due to the diversity of the Salmonella contaminating this product, associations between salmonellosis cases and betel leaf consumption will appear sporadic and unlikely to be detected by current surveillance strategies based on outbreak detection.
AB - Fresh betel leaves (Piper betle L.), imported into the UK are a traditional ready-to-eat food consumed by Asian populations. We report here the consolidation of routinely collected data to model the public health risks from consumption of this food. Amongst 2110 samples collected at Border Inspection, wholesale, catering or retail, Salmonella was detected in 488 (23%) of samples tested between 2011 and 2017 and was the most commonly Salmonella-contaminated ready-to-eat food examined by Public Health England during this period. Using data from multiple samples (usually 5) tested per consignment sampled at Border Inspection, contamination levels were calculated by most probable number: seasonal, temporal and country specific differences were detected. Quantitative contamination data was used to estimate the levels present at retail, and a β-Poisson dose response model the probability of illness was calculated. Using data for products imported from India, the probability of acquiring infection following a single exposure (comprising of a single leaf) was estimated to be between 0.00003 (January–March) and 0.0001 (July–September). Using British Asian population data for individuals over 30 years of age in England in 2011, two estimates of consumption were modelled as 2.1 and 12.8 million servings per annum. Results from the model estimated 160 cases (range 102 to 242) and 960 cases (range 612 to 1456) per year in England for the two consumption estimates and equated to 34 (range 22 to 51) and 204 (range 130 to 310) salmonellosis cases per year reported to national surveillance. Salmonella from 475 of the contaminated samples were further characterised which showed a heterogeneous population structure with 46 S. enterica subsp. Enterica serovars, together with S. enterica subs diarizonae and salamae identified. Isolates from individual consignments were diverse and close genetic relationships between independent isolates were very rare except from within an individual consignment. There were no outbreaks detected as associated with betel leaf consumption. However analysis by whole genome sequencing of the 2014–17 data identified two cases where the clinical isolate had <5 single nucleotide polymorphism differences to isolates from betel leaves which is indicative of a likely epidemiological link and common source of contamination. Due to the diversity of the Salmonella contaminating this product, associations between salmonellosis cases and betel leaf consumption will appear sporadic and unlikely to be detected by current surveillance strategies based on outbreak detection.
KW - Betel leaves
KW - Imported food
KW - Quantitative microbiological risk assessment
KW - Salmonella
KW - Salmonellosis
KW - Whole genome sequencing
UR - http://www.scopus.com/inward/record.url?scp=85062985183&partnerID=8YFLogxK
U2 - 10.1016/j.ijfoodmicro.2019.03.004
DO - 10.1016/j.ijfoodmicro.2019.03.004
M3 - Article
C2 - 30889473
AN - SCOPUS:85062985183
SN - 0168-1605
VL - 298
SP - 1
EP - 10
JO - International Journal of Food Microbiology
JF - International Journal of Food Microbiology
ER -