P. Teunis et al., RISK ASSESSMENT OF CAMPYLOBACTER SPECIES IN SHELLFISH - IDENTIFYING THE UNKNOWN, Water science and technology, 35(11-12), 1997, pp. 29-34
Citations number
8
Categorie Soggetti
Water Resources","Environmental Sciences","Engineering, Civil
Shellfish are frequently contaminated by Campylobacter spp, presumably
originating from faeces from gulls feeding in the growing or relaying
waters. The possible health effects of eating contaminated shellfish
were estimated by quantitative risk assessment. A paucity of data was
encountered necessitating many assumptions to complete the risk estima
te. The level of Campylobacter spp in shellfish meat was calculated on
the basis of a five-tube, single dilution MPN and was strongly season
-dependent. The contamination level of mussels (<1/g) appeared to be h
igher than in oysters. The usual steaming process of mussels was found
to completely inactivate Campylobacter spp so that risks are restrict
ed To raw/undercooked shellfish. Consumption data were estimated on th
e basis of the usual size of a portion of raw shellfish and the weight
of meat/individual animal. Using these data, season-dependent dose-di
stributions could be estimated. The dominant species in Dutch shellfis
h is C. lari but little is known on its infectivity for man. As a wors
t case assumption, it was assumed that the infectivity was similar to
C. jejuni. A published dose-response model for Campylobacter-infection
of volunteers is available but with considerable uncertainty in the l
ow dose region. Using Monte Carlo simulation, risk estimates were cons
tructed. The consumption of a single portion of raw shellfish resulted
in a risk of infection of 5-20% for mussels (depending on season; 95%
CI 0.01-60%). Repeated (e.g. monthly) exposures throughout a year res
ulted in an infection risk of 60% (95% CI 7-99%). Risks for oysters we
re slightly lower than for mussels. It can be concluded that, under th
e assumptions made, the risk of infection with Campylobacter spp by ea
ting of raw shellfish is substantial. Quantitative risk estimates are
highly demanding for the availability and quality of experimental data
, and many research needs were identified. (C) 1997 IAWQ. Published by
Elsevier Science Ltd.