Risk Assessment for Safe Drinking Water Supplies - Global Drinking Water Management and Conservation - page 129

7. In QMRA, the probability of infection, given a particular density of a pathogen,
in turn depends on the probability of exposure to the organism. But the rate of
infection depends on the individual

' s capacity of immune response. The only

known “ outcome ” is “ illness, ” but the illness intensity and duration are very

variable.
8. The estimation of the probability of infection depends on “ dose-response

A critique of such models is outside the scope of this chapter.
9. Infection is a necessary condition for a disease, but not all infections result in
symptoms of illness. This still leaves the problem of the severity and duration
of illness.
10. The risk of disease burden is measured in DALYs. DALY is a good mea-
surement as it is calculated as a product of the probability of each illness
outcome with a severity factor and the duration in years. But what is an
“

models. ”

DALY is a political judgment. Many jurisdictions (for example,
Canada and the US) accept the WHO recommended acceptable level of risk as
10 − 6 DALY/person per year.
11. The

acceptable ”

final outcome in the formula of DALY is a social cost of pathogens; it is a
social opportunity cost. Instead of spending effort and money to implement
QMRA, the same effort could be more effectively used to increase treatment
effectiveness and thereby raise log reduction to 4 or 5. This can be done cheaply
with the newer UV modules that can inactivate a large spectrum of pathogens.
Thus, instead of using QMRA, incorporating an UV module in every treatment
train would be more cost-effective. It will certainly reduce the mean concen-
tration of pathogens in the treated water and thereby reduce the probability of
infection and illness.
12. Smeets et al. ( 2010 ) show that an application of QMRA can be used to
determine the ef

ciency of treatment under the WSP system. Their study (a)
helps to determine the acceptable time of system failure during the treatment
process by setting critical limits and taking corrective actions when necessary,
for example, the 2.5-log reduction of pathogens requires that the system failure
time is not more than 6 h per year; and (b) shows that high frequency of
physical and microbial monitoring can improve treatment effectiveness, i.e.
conducting the microbial monitoring every 15 min can increase the reduction of
pathogens by 2 logs compared to daily monitoring (Smeets et al. 2010 ).Thus,
the application of QMRA helps to reduce the likelihood of uncertainty in the
management of microbial drinking water safety (Smeets et al. 2010 ). Never-
theless, the computation burden is enormous.