Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose
Introduction
To secure and increase crop production, irrigation has become a principal water use in many countries, where it has traditionally been dependent on rain water (Anonymous, 2014, Jiménez, 2006). In developing countries, the increase in wastewater usage has ensured that farmers produce adequate food throughout the year, and millions of small-scale farmers in urban and peri-urban areas are dependent on irrigation to grow high-value edible crops for urban markets (Qadir et al., 2010); irrigation has also contributed to improved nutrition and employment opportunities for farmers. The use of wastewater provides nutrients needed for plant growth and reduces the costs of using fertilizer on plants (Jiménez, 2006). It permits higher crop yields, year-round production, and enlarges the range of crops that can be grown, particularly in (but not limited to) arid and semi-arid areas.
In Ghana, the use of wastewater for vegetable farming is widespread, particularly in and around the more populated cities, where safe water is scarce (Seidu et al., 2008, Keraita et al., 2013). This places Ghana among the countries with the highest volume of raw wastewater usage worldwide, and represents an appropriate study area in relation to wastewater usage in agriculture within developing countries (Amoah et al., 2005, Jiménez, 2006, Amoah et al., 2006, WHO, 2006, Amoah et al., 2007, Raschid-sally and Jayakody, 2008, Hall et al., 2009, Mara and Sleigh, 2009, Drechsel et al., 2009, Mara and Sleigh, 2010a, Mara and Sleigh, 2010b, Labite et al., 2010, Fung, 2011, Ackerson and Awuah, 2012, Tiimub et al., 2012; Lundqvist and Raschid-Sally, 2013, Mok and Hamilton, 2014).
The use of raw wastewater for irrigation is, however, not without public health risks. Quantitative Microbial Risk Assessment (QMRA) has over the years become a powerful tool for estimating health risk through the use of probabilistic modelling. Recent studies estimating the risks of gastroenteritis applied the QMRA methodology to determine the disease burden associated with the consumption of vegetables irrigated with wastewater (Barker et al., 2014; Barker et al., 2013a, Barker et al., 2013b, Mok et al., 2014). Barker (2014) has indicated that the common challenge to conduct such QMRA has been the limited availability of input data on an actual pathogen, in particular virus concentrations as well as virus dose response models. To establish virus concentration, a fecal indicator conversion ratio has therefore been used to express the relationship between the occurrence of fecal indicators (typically E. coli) and the virus. This approach is also used in the current WHO guidelines (WHO, 2006), and has been adopted by subsequent QMRA studies (Barker et al., 2014, Barker et al., 2013a, Barker et al., 2013b, Mara and Hamilton, 2010, Mara and Sleigh, 2010a, Mara and Sleigh, 2010b, Travis et al., 2010, Mok and Hamilton, 2014, Ackerson and Awuah, 2012).
In this study, QMRA model is developed that uses the conversion ratio based on E. coli and norovirus genome copies data that was measured in wastewater to estimate final dose. The model employs a parametric approach to characterize the distribution of norovirus genomic copies to estimate the dose. The study further assesses the impact and likelihood of underestimating or overestimating the health risk (DALY) as a result of using the fecal indicator conversion ratio to estimate the dose of norovirus for risk assessment, when compared to using the genome copies data.
Section snippets
Exposure assessment model
The objective of the exposure assessment model was to estimate the dose of norovirus that consumers are exposed to through the consumption of wastewater-irrigated lettuce and cabbage. Lettuce and cabbage were selected as the main vegetables to represent crops commonly consumed raw in Ghana and other African countries as main ingredients in street foods (Fung, 2011). Water types used for irrigation in developing countries typically include wastewater from streams, drain-water and partially
Estimation of annual probability of infection and illness of norovirus gastroenteritis
The annual probability of norovirus infection ranged from 9.2 × 10− 1 to 9.4 × 10− 1 for all norovirus genome copies while the ratio conversion method provided a similar range from 8.8 × 10− 1 to 9.1 × 10− 1. These findings are supported by the estimation of the annual probability of diseases at a given infection that ranged from 8.6 × 10− 1 to 9.0 × 10− 1 for the norovirus genome copies and 8.1 × 10− 1 to 8.3 × 10− 1 for E. coli ratio conversion (Table 4). Using the USEPA's threshold of 1 × 10− 4 annual probability of
Discussion
The disease burden of the different model scenarios was found to be acceptable under different thresholds of DALY. Nevertheless, it should be noted that the DALY figures are conservative estimates and might in reality be a few orders higher due to the challenges of recovering and enumerating norovirus from sample material as discussed in Papafragkou et al., 2013, Schrader et al., 2012, Laverick et al., 2004. This means, the true disease burden (DALY) from stream wastewater and drain wastewater
Conclusion
We estimated the risk of illness and the disease burden expressed in DALYs with the use of fecal indicator ratio conversion or genome copies of norovirus for the consumption of vegetables irrigated with wastewater in Ghana. A QMRA model was developed to estimate the differences in diseases burden, and the results showed that:
- 1.
All model scenarios for consuming vegetables irrigated with wastewater (stream or drain) met the 1 × 10− 4 DALY pppy threshold for norovirus. However, models using genome
Acknowledgement
We want to appreciate the help of the following people and their contribution, Rejoice Ametepey, Prof Anders Permin (Technical Univ. of Denmark), Dr Torben Schou (DHI Denmark) and also to faculty members of National Food Institute Soborg, Technical Univ. of Denmark for their critique. This work was supported by DANIDA project Safe Water for Food (11-058DHI).
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