Literature DB >> 28618661

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.

Emmanuel de-Graft Johnson Owusu-Ansah1, Angelina Sampson2, Samuel K Amponsah3, Robert C Abaidoo4, Anders Dalsgaard5, Tine Hald6.   

Abstract

The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10-5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data. In some cases the difference was >2 orders of magnitude. All scenarios using genome copies met the 10-4 DALY per person per year for consumption of vegetables irrigated with wastewater, although these results are considered to be highly conservative risk estimates. The fecal indicator conversion ratio model of stream-water and drain-water sources of wastewater achieved the 10-6 DALY per person per year threshold, which tends to indicate an underestimation of health risk when compared to using genome copies for estimating the dose.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Disability Adjusted Life Years; Fecal indicator; Norovirus; Probabilistic model; Public health; QMRA

Mesh:

Substances:

Year:  2017        PMID: 28618661     DOI: 10.1016/j.scitotenv.2017.05.168

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

Review 1.  Quantitative Microbial Risk Assessment and Infectious Disease Transmission Modeling of Waterborne Enteric Pathogens.

Authors:  Andrew F Brouwer; Nina B Masters; Joseph N S Eisenberg
Journal:  Curr Environ Health Rep       Date:  2018-06

2.  Assessment of rotavirus and norovirus emitted from water spray park: QMRA, diseases burden and sensitivity analysis.

Authors:  Hasan Pasalari; Hesam Akbari; Angila Ataei-Pirkooh; Amir Adibzadeh; Hamed Akbari
Journal:  Heliyon       Date:  2022-10-07

3.  Groundwater use and diarrhoea in urban Nepal: novel application of a geostatistical interpolation technique linking environmental and epidemiologic survey data.

Authors:  Sadhana Shrestha; Takashi Nakamura; Jun Magome; Yoko Aihara; Naoki Kondo; Eiji Haramoto; Bikash Malla; Junko Shindo; Kei Nishida
Journal:  Int Health       Date:  2018-09-01       Impact factor: 2.473

4.  Quantitative assessment of exposure to fecal contamination in urban environment across nine cities in low-income and lower-middle-income countries and a city in the United States.

Authors:  Yuke Wang; Wolfgang Mairinger; Suraja J Raj; Habib Yakubu; Casey Siesel; Jamie Green; Sarah Durry; George Joseph; Mahbubur Rahman; Nuhu Amin; Md Zahidul Hassan; James Wicken; Dany Dourng; Eugene Larbi; Lady Asantewa B Adomako; Ato Kwamena Senayah; Benjamin Doe; Richard Buamah; Joshua Nii Noye Tetteh-Nortey; Gagandeep Kang; Arun Karthikeyan; Sheela Roy; Joe Brown; Bacelar Muneme; Seydina O Sene; Benedict Tuffuor; Richard K Mugambe; Najib Lukooya Bateganya; Trevor Surridge; Grace Mwanza Ndashe; Kunda Ndashe; Radu Ban; Alyse Schrecongost; Christine L Moe
Journal:  Sci Total Environ       Date:  2021-10-28       Impact factor: 7.963

  4 in total

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