Abbreviations
Ameli-EAUR Amélioration de l'accès
à l'Eau potable et à l'Assainissement en milieu Urbain et
Rural
C+TW Compost and Top Water
C+U+GW Compost, Urine and Greywater
DALY Disability Adjusted Life Years
DW Dry weight
EPA Environment Protection Agency
FAO Food and Agriculture Organization of
United Nations
FW Fresh weight
GW Greywater
JICA Japanese International Cooperation
Agency
NoF Non Fertilizer
Pinf Probability of infection
PPPY Per Person Per Year
Pyr Annual Probability risk infection
QMRA Quantitative Microbial Risks Analysis
UNICEF United Nations Organization for Child
and Education Found
U+TW Urine and Top Water
W/V Weight/Volume
List of tables
Table 1: Different routes of exposure of farmers by
irrigation with greywater
2
Table 2: Different parameters which are analyzed in
the matrix
15
Table 3: Different exposure scenarios and pathways
which farmers and consumers can be exposed in different cases
21
Table 4: Summary of dose-response parameters for
exponential and beta-Poisson models from various enteric pathogen ingestion
studies
23
Table 5: Annual probabilities of
Salmonella and Ascaris infection associated with the
ingestion of soil combined with compost and consumption of lettuce
25
Table 6: Annual probabilities of
Salmonella infection associated with the ingestion of soil combined
with urine and consumption of lettuce
26
Table 7: Annual probabilities of
Salmonella infection associated with the soil and greywater ingestion
combined with greywater and lettuce consumption
27
Table 8: Annual probabilities of Salmonella
and Ascaris infection associated with the soil and greywater
ingestion combined with compost, urine and greywater and lettuce
consumption
28
Table 9 : Probabilistic values of different
treatments compared with the WHO guideline values of the risk.
29
Table 10: Probabilistic values of Greywater and
Compost, Urine and Greywater treatments compared with the WHO guideline values
of the risk.
30
Table 11: Probabilistic values of different
treatments compared with the WHO guideline values of the risk.
31
List of figures
Figure 1: Experimental site of Kamboinsé
(source Google earth)
2
Figure
2: Experimental design in the site
14
Figure
3: Illustration of step of Salmonella analysis
18
Figure
4: Steps of calculation of Monte Carlo Method
23
Figure 5: Annual infection risks of
Salmonella and Ascaris in function of scenarios compared with
WHO guideline value.
25
Figure 6 : Annual infection risks of
Salmonella in function of scenarios compared with WHO guideline
value.
26
Figure 7 : Annual infection risks of
Salmonella in function of scenarios compared with WHO guideline value.
27
Figure 8: Annual infection risks of
Salmonella and Ascaris in function of scenarios compared with
WHO guideline value.
28
Figure 9 : Probabilistic values of all
treatments compared with the WHO guideline values of risk for soil ingestion
scenario
29
Figure 10 : Probabilistic values of Greywater
and Compost, Urine and Greywater treatments compared with the WHO guideline
values
30
Figure 11: Probabilistic values of all treatments
compared with the WHO guideline values of risk for lettuce consumption
scenario
31
Table of contains
Dedication
i
Acknowledgements
ii
Abstract
iii
Résumé
iv
Abbreviations
vi
List of tables
vii
List of figures
viii
I. Introduction
1
II. LITERATURE REVIEW
3
1. Generalities on health risk assessment
4
1.1. Health risk assessment
4
1.2. Steps of health risk assessment
5
1.3. Microbial risk assessment
6
2. Health risk assessment for farmers
6
2.1. Spreading compost
6
2.2. Spreading urine
7
2.3. Watering greywater
8
3. Health risk assessment for consumers
10
III. MATERIAL AND METHODS
12
1. Experimental site
13
2. Sampling and data collection
15
2.1. Initial statement of the experimental site
15
2.2. Microbiological analysis of matrix (soil,
compost, urine, and greywater)
15
2.3. Following up indicators of pathogen on lettuce
leave
19
3. Quantitative Microbial Risk Analysis (QMRA)
methods
19
3.1. Hazard identification
19
3.2. Exposure assessment
19
3.3. Dose-response assessment
21
3.4. Risk characterization
23
IV. RESULTS AND DISCUSSION
24
1. Results
25
1.1. Quantitative Microbial Risk Assessment from
different treatments
25
1.2. Comparison of the probabilistic values of
different treatments related with the scenarios
29
2. Discussion
32
2.1. Quantitative Microbial Risk Assessment from
each treatment.
32
2.2. Comparison of the probabilistic values of
different treatments related with the scenarios
35
IV. Conclusion and perspectives
38
V. References
39
Annex
i
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