Quantitative microbial risk assessment of enteroviruses in raw-eatable vegetables irrigated by wastewater: examining different scenarios of washing

Abstract

Due to the increasing water crisis, the reuse of wastewater deserves attention as a method to reduce the pressure of the water crisis, especially in developing countries. The application of health risk assessment models is a way to estimate disease burdens associated with crop irrigation by wastewater effluents. In this study, a quantitative microbial risk assessment (QMRA) with probabilistic Monte-Carlo simulation was used to estimate the annual risk of enteroviruses (EVs) infection and disease burden for consumers of effluent-irrigated raw vegetables in Tehran, the capital of Iran. Wastewater effluent samples were collected over two seasons: summer and winter. EVs were analyzed in three stages, concentration and separation, cell culture, and real-time PCR (RT-PCR). A questionnaire was used to determine the dominant patterns of vegetable washing by consumers. There were 4 vegetable washing steps: wiping away mud (A), rinsing (B), using detergents (C), using disinfectants (D). 5 patterns of washing were examined in the laboratory and the concentration of enteroviruses was measured in every pattern. pattern 1: just wiping away mud (A), pattern 2: wiping away mud and rinsing (AB), pattern 3: wiping away mud by using detergents and rinsing (ABCB), pattern 4: wiping away mud by using disinfectants and rinsing (ABDB), and pattern 5: wiping away mud by using detergents and disinfectants and rinsing (ABCBDB). For washing pattern 1, pattern 2, and pattern 3, the estimated annual infection risk of EVs was estimated to be 5.6 × 10^-1, 3.6 × 10^-1, 1.7 × 10^-1 (risk/per.day), and burden of disease was calculated as 3 × 10^-2, 2 × 10^-2, and 9 × 10^-3 (burden/year), respectively. The results showed that if vegetables are washed according to method 5, the microbial risk will be minimized and the excess prevalence of viral infections will be eliminated.

Keywords: Enterovirus infection; QMRA; Real-time PCR; Vegetables; Wastewater effluents.

Fig. 1

The studying area location (WWTPs and downstream farmlands)

Fig. 2

Frequency of vegetable consumption in the community

Fig. 3

Amount of vegetable consumption in a meal per person

Fig. 4

Vegetable washing patterns

Fig. 5

The comparison of EVs and total coliforms (TC) concentrations in two seasons

Fig. 6

The box plots. (A): estimated annual probability of infection risk (Pi (A)) (pppy) and

Fig. 7

Variability cumulative distribution plots of the EV burden of disease for every washing scenario. A: pattern 1, B: pattern 2 and C: pattern 3. Y-axis is the percentile of variability and the X-axis is the point estimate of the burden of disease. Light gray bands correspond to the 95% uncertainty range on each quantile of variability and the 50% uncertainty range on each quantile of variability is corresponded by dark gray bands

Fig. 8

Burden of disease sensitive analysis