Wastewater epidemiology and related uncertainties

Sara Castiglioni Mario Negri Institute

Department of Environmental Health Sciences Unity of Environmental Biomarkers

COST Action ES1307– Malta 27-28 October 2014

COST is supported by the

EU Framework Programme

Horizon 2020

ESF provides the COST

Office through an EC

contract

Rational of the approach

Almost all substances we consume are excreted unchanged or as a mixture of metabolites in urine and/faeces Excreted substances end up in sewer

network

Enter sewage treatment plants

Raw wastewater is containing all the metabolic residues of substances consumed by a defined

population

Raw wastewater contains multiple information on human habits in a defined population

Wastewater-Based Epidemiology Approach

Estimation of illicit drugs consumption cocaine, amphetamines, ecstasy, cannabis, heroin

Monitoring drinking habits ethyl sulphate and ethyl glucuronide

Monitoring smoking habits cotinine and trans-3’-hydroxycotinine

Identify the use of new synthetic recreational drugs synthetic cannabinoids, cathinones (NPS)

Wastewater-Based Epidemiology Current applications

Other potential applications related to lifestyle, health and diet and environment (Thomas and Reid, ES&T, 2011, 45:7611)

Temporal trends in Milan (2005-2012) - Loads g/day Zuccato et al. Drug Alcohol Depend, 2011

5

0

200

400

600

800

1000

1200

1400

Cocaine

0

20

40

60

80

100

120

140

Heroin

0

1000

2000

3000

4000

5000

6000

7000

8000

THC

0

50

100

150

200

250

Metamphetamine

Estimation of Illicit Drugs Consumption

Monitoring of drinking habits Oslo September 2009 (Reid et al., Alcohol Clin. Exp. Res. 2011)

Monitoring of drinking habits Milan (30 September - 03 November 2013)

0

500

1000

1500

2000

2500

3000

3500

40003

0-s

et

01

-ott

02

-ott

03

-ott

04

-ott

05

-ott

06

-ott

07

-ott

08

-ott

09

-ott

10

-ott

11

-ott

12

-ott

13

-ott

14

-ott

15

-ott

16

-ott

17

-ott

18

-ott

19

-ott

20

-ott

21

-ott

22

-ott

23

-ott

24

-ott

25

-ott

26

-ott

27

-ott

28

-ott

29

-ott

30

-ott

31

-ott

01

-no

v

02

-no

v

03

-no

v

Lod

sg

/day

Ethyl Suphate (EtS)

Monitoring of smoking habits Castiglioni et al., Tobacco Control, 2014

0.0

0.5

1.0

1.5

2.0

2.5

Nicotine Cotinine trans-3'-hydroxycotinine

Load

s(g

/day

/10

00

inh

abit

ants

)

North ITALY Centre ITALY South ITALY

***

******

**

****

Number of cigarettes smoked

Wastewater analysis Epidemiological survey data Difference (%)

Northern Italy 1695538 1701190 +0.3

Central Italy 2987243 3114850 +4

Southern Italy 1207092 1112987 -8%

Back-calculation using cotinine + trans-3’-hydroxycotinine

Monitoring of new synthetic recreational drugs Reid et al., Drug Anal Test. 2013

0

10

20

30

40

50

60

70

Oslo Hamar Bergen

mg

/1

00

0 i

nh

./d

ay

BE

THC-COOH

JWH 018-5OHP

Cathine

Monitoring of new synthetic recreational drugs

Ketamine is a dissociative

anaesthetic drug...

...with documented increase in its use

as a recreational drug

Increased use in Milan from 2008 to 2013 4-5 weeks investigated per year

Profile of KETAMINE use in Milan in a six-year study

Wastewater – based epidemiology

To produce reliable data:

• identify gaps or uncertainty

• minimize or control uncertainties when possible

• improve our method

1. Are these data reliable? 2. Wastewater analysis can be used to integrate epidemiological data?

Best practice protocol

Identification of uncertainties associated with all the steps of the methodology

Evaluation of uncertainties Castiglioni et al., ES&T, 2013

Sampling of untreated wastewater

Sampling mode, frequency and catchments characteristics

Crucial to obtain representative samples

Sections Description

1 General information

2 Catchment properties

3-4 Sewer system

5 Lift stations in sewer system

6-8 STP influent data

9-11 Sampling point, mode and frequency

12 Calibration of flow meter

• Establish a good connection with STPs personnel

•A questionnaire was developed by Christoph Ort to collect the required information

Ort and Gujer Water Sci. Technol. 2006

Ort et al., ES&T, 2010

Castiglioni et al. ES&T. 2013

Selection of Target Residues

Excreted in consistent amounts

Detectable in wastewater

Stable in wastewater

Unique source: human

metabolism

Drug Target Residue

Analysis of Target Residues

High sensitivity (Low ng/L range) High selectivity

(unambiguous identification of an analyte)

WASTEWATER: Complex matrix Mass spectrometry allows the contemporaneous analysis of tens

of substances

Mandatory to follow quality criteria

Use of labelled compounds as internal standards

Use of at least two transitions for positives confirmation

Harmonize methods to estimate limits of detection and quantification

Stability of drug biomarkers in sewage

1. Stability in sewer systems 2. Stability during sampling, storage and analysis

Resident time in sewer 0.5-15 hours the variability is <10% Samples collection at refrigerated conditions, storage at -20°C and use of internal standards as soon as possible

References

(Castiglioni

et al., 2006)

(Gonzalez-

Marino et al.,

2010)

(Bisceglia,

2010;Bisceglia

and Lippa,

2014)

(Baker and

Kasprzyk-

Hordern, 2011)

(Castiglioni et

al., 2011)

(van Nuijs et

al., 2012)

(Plosz et

al., 2013)

(Thai et al.,

2014)

(Chen et

al., 2013)

(Senta et

al., 2014)

72 h

4 °C

pH 7.5

24 h

4 °C

pH 7.5

12 h

23 °C

pH 7.4

12 h

19 °C

pH 7.4

24 h

4 °C

pH 7.5

12 h

20 °C

pH 7.5

7 h

21 °C

pH 7.4

12 h

20 °C

pH 7.5

24 h

20 °C

pH 7.0

24 h

20 °C

pH 7.5

COC -36% -7% -50% -8% -25% -40% -60% -20% -9% -35%

BE +14% +7% +10-14% +7% +20% +6% +18% +14% NA +15%

EME* NA NA -40% NA -50% -20% -29% NA NA NA

AMP +5% +0% -15% +47% NA +3% NA NA NA -5%

METH +0% NA +0% +8% NA +2% NA 0% -5% -10%

MDMA +1% NA +0% +1% NA +3% NA 0% +1% -10%

THC-COOH -8% +2% NA NA NA NA NA NA NA 0%

6-MAM -14% NA -15% -42% NA -20% NA -25% -53% -15%

Back-calculation of consumption

Loads of target residues entering the plant

(g/day)

Amounts of the selected substance consumed by the population served

by the plant

Human metabolism

Correction factors

Zuccato et al. Environ. Health Perspect. 2008

Main uncertainty factor: lack of pharmacokinetic studies

Back-calculation of consumption

Illicit drugs Drug Target Residue

measured in

wastewater

Mean % of

excretion

selected

Correction

factor used for

back-calculation

Cocaine Cocaine 7.5 13

Benzoylecgonine 45

35

32.5

29

2.3

3

3.2

3.59

Amphetamine Amphetamine 30 3.3

Methamphetamine Methamphetamine 43

39

33

2.3

2.6

4.06

3,4-methylenedioxy-

methamphetamine

(MDMA)

MDMA 65

26

20

15

1.5

3.9

5

6.7

Cannabis 11-nor-9-carboxy-

delta9-

tetrahydrocannabin

ol (THC-COOH)

2.5

0.6

36.4

152

Heroin Morphine 42 3.1

6-acetylmorphine 1.3 86.9

Ketamine Ketamine

Norketamine

30

1.6

3.3

65

• Great variability among correction factors

• Lack of reliable comparison between results from different studies

1. Refine correction factors properly

2. Adoption of an homogeneous panel of correction factors

Back-calculation of consumption

Routes of

administration

Number of

studies

Number of

subjects

(range per study)

Mean Excretion

weighted by

subjects (%)

Mean

excretion

(%)

Mean

weighted

by RoA

Intranasal (IN) 9 56 (2-7) 29.4 ± 7.4

27.1 ± 11.4

29.2 ± 7.8 Intravenous (IV) 7 28 (1-7) 37.3 ± 9.6

Smoked (SM) 3 20 (5-9) 14.8 ± 5.8

Oral (O) 1 2 55 ± 7.1

New method proposed for cocaine

Study of benzoylecgonine metabolism

• Excretion profile for different route of administration • Number of subjects involved in each study • Frequency of use for each route of administration

Novel correction factor considering this mean excretion rate of BE: 3.59

Castiglioni et al. ES&T. 2013

Estimation of population size

• Population equivalents from hydro-chemical parameters BOD5, COD, total N and P, ammonium which depend from sewage composition (urban or industrial)

• Population leaving in the area (census data)

• Analysis of specific substances that can indicate univocally the persons served by a STP on the base of their known consumption/excretion

Pharmaceuticals Creatinine Cotinine and trans-3’-hydroxycotinine Cholesterol Coprostanol Caffeine Cortisol Androstenedione 5-hydroxyindoleacetic acid

Conclusions

Evaluate uncertainty associated to estimation of drug use

Identify a best practice procedure to reduce or keep minimal the uncertainty of the entire procedure

Steps considered “Best practice” requirements Uncertainty (%)

Sampling Sampling mode: a) flow-proportional; b) volume proportional;

c) time-proportional (only for small flow variations)

Sampling frequency: depending on SDBs concentration variations

(population size, number of users, pharmacokinetics, operation of pump

stations)

Catchment characteristics: exfiltration, special events, layout of

STPs and sewer catchment affecting mass flux of SDBs

5-10

Chemical analysis Analytical quality: use of labelled IS, use of internal quality controls,

estimation of comparable LODs and LOQs, confirmation of positives

Interlaboratory variability and laboratory performance:

interlaboratory study (ILS) are mandatory on standards and real samples,

assessment of accuracy and biases

1-34 samples

6-26 ILS

Conclusions

Steps considered “Best practice” requirements Uncertainty (%)

Stability in sewage Sewage system: resident time of wastewater in sewer before sampling

During sampling, storage, analysis: 24h collection at refrigerated

conditions, samples acidification (pH 2), freeze samples (-20°C) or stabilize on

SPE cartridges immediately after collection

< 10

Back-calculation

of consumption

Selection of proper SDBs

Collection of excretion profiles for all the routes of administration,

weight for the number of subjects and the frequency of use

26 (cocaine case)

Estimation of

population size

Collection of all available data: estimates from hydrochemical

parameters, census data

Choose the most adequate (combination of) value case by case

with expert knowledge from experienced STP staff. Although widely available,

design capacities are not recommended, as design rules in different countries

vary and, furthermore, without knowing the planning horizon and actual

loading (recent hydro-chemical parameters), it is unknown, whether the STP

runs above or below design capacity.

7-55

Thanks

Thanks for your attention!

Paper published in ES&T

Co-authors

Sara Castiglioni

Lubertus Bijlsma,

Adrian Covaci,

Erik Emke

Félix Hernández,

Malcolm Reid,

Christoph Ort,

Kevin V Thomas,

Alexander LN van Nuijs,

Pim de Voogt,

Ettore Zuccato

EMCDDA

Paul Griffith,

Jane Mounteney,

Danica Thanki,

Liesbeth Vandam

COST Action ES1307

Potentials of the approach

Ability to provide:

Objective estimates

Qualitative and quantitative evaluation

Real-time estimates

Updated information on substance use

Be complementary to epidemiological surveys

Wastewater-Based Epidemiology